what is a limitation in a research paper

How to Write Limitations of the Study (with examples)

This blog emphasizes the importance of recognizing and effectively writing about limitations in research. It discusses the types of limitations, their significance, and provides guidelines for writing about them, highlighting their role in advancing scholarly research.

Updated on August 24, 2023

No matter how well thought out, every research endeavor encounters challenges. There is simply no way to predict all possible variances throughout the process.

These uncharted boundaries and abrupt constraints are known as limitations in research . Identifying and acknowledging limitations is crucial for conducting rigorous studies. Limitations provide context and shed light on gaps in the prevailing inquiry and literature.

This article explores the importance of recognizing limitations and discusses how to write them effectively. By interpreting limitations in research and considering prevalent examples, we aim to reframe the perception from shameful mistakes to respectable revelations.

What are limitations in research?

In the clearest terms, research limitations are the practical or theoretical shortcomings of a study that are often outside of the researcher’s control . While these weaknesses limit the generalizability of a study’s conclusions, they also present a foundation for future research.

Sometimes limitations arise from tangible circumstances like time and funding constraints, or equipment and participant availability. Other times the rationale is more obscure and buried within the research design. Common types of limitations and their ramifications include:

• Theoretical: limits the scope, depth, or applicability of a study.
• Methodological: limits the quality, quantity, or diversity of the data.
• Empirical: limits the representativeness, validity, or reliability of the data.
• Analytical: limits the accuracy, completeness, or significance of the findings.
• Ethical: limits the access, consent, or confidentiality of the data.

Regardless of how, when, or why they arise, limitations are a natural part of the research process and should never be ignored . Like all other aspects, they are vital in their own purpose.

Why is identifying limitations important?

Whether to seek acceptance or avoid struggle, humans often instinctively hide flaws and mistakes. Merging this thought process into research by attempting to hide limitations, however, is a bad idea. It has the potential to negate the validity of outcomes and damage the reputation of scholars.

By identifying and addressing limitations throughout a project, researchers strengthen their arguments and curtail the chance of peer censure based on overlooked mistakes. Pointing out these flaws shows an understanding of variable limits and a scrupulous research process.

Showing awareness of and taking responsibility for a project’s boundaries and challenges validates the integrity and transparency of a researcher. It further demonstrates the researchers understand the applicable literature and have thoroughly evaluated their chosen research methods.

Presenting limitations also benefits the readers by providing context for research findings. It guides them to interpret the project’s conclusions only within the scope of very specific conditions. By allowing for an appropriate generalization of the findings that is accurately confined by research boundaries and is not too broad, limitations boost a study’s credibility .

Limitations are true assets to the research process. They highlight opportunities for future research. When researchers identify the limitations of their particular approach to a study question, they enable precise transferability and improve chances for reproducibility. 

Simply stating a project’s limitations is not adequate for spurring further research, though. To spark the interest of other researchers, these acknowledgements must come with thorough explanations regarding how the limitations affected the current study and how they can potentially be overcome with amended methods.

How to write limitations

Typically, the information about a study’s limitations is situated either at the beginning of the discussion section to provide context for readers or at the conclusion of the discussion section to acknowledge the need for further research. However, it varies depending upon the target journal or publication guidelines. 

Don’t hide your limitations

It is also important to not bury a limitation in the body of the paper unless it has a unique connection to a topic in that section. If so, it needs to be reiterated with the other limitations or at the conclusion of the discussion section. Wherever it is included in the manuscript, ensure that the limitations section is prominently positioned and clearly introduced.

While maintaining transparency by disclosing limitations means taking a comprehensive approach, it is not necessary to discuss everything that could have potentially gone wrong during the research study. If there is no commitment to investigation in the introduction, it is unnecessary to consider the issue a limitation to the research. Wholly consider the term ‘limitations’ and ask, “Did it significantly change or limit the possible outcomes?” Then, qualify the occurrence as either a limitation to include in the current manuscript or as an idea to note for other projects. 

Writing limitations

Once the limitations are concretely identified and it is decided where they will be included in the paper, researchers are ready for the writing task. Including only what is pertinent, keeping explanations detailed but concise, and employing the following guidelines is key for crafting valuable limitations:

1) Identify and describe the limitations : Clearly introduce the limitation by classifying its form and specifying its origin. For example:

• An unintentional bias encountered during data collection
• An intentional use of unplanned post-hoc data analysis

2) Explain the implications : Describe how the limitation potentially influences the study’s findings and how the validity and generalizability are subsequently impacted. Provide examples and evidence to support claims of the limitations’ effects without making excuses or exaggerating their impact. Overall, be transparent and objective in presenting the limitations, without undermining the significance of the research. 

3) Provide alternative approaches for future studies : Offer specific suggestions for potential improvements or avenues for further investigation. Demonstrate a proactive approach by encouraging future research that addresses the identified gaps and, therefore, expands the knowledge base.

Whether presenting limitations as an individual section within the manuscript or as a subtopic in the discussion area, authors should use clear headings and straightforward language to facilitate readability. There is no need to complicate limitations with jargon, computations, or complex datasets.

Examples of common limitations

Limitations are generally grouped into two categories , methodology and research process .

Methodology limitations

Methodology may include limitations due to:

• Sample size
• Lack of available or reliable data
• Lack of prior research studies on the topic
• Measure used to collect the data
• Self-reported data

The researcher is addressing how the large sample size requires a reassessment of the measures used to collect and analyze the data.

Research process limitations

Limitations during the research process may arise from:

• Access to information
• Longitudinal effects
• Cultural and other biases
• Language fluency
• Time constraints

The author is pointing out that the model’s estimates are based on potentially biased observational studies.

Final thoughts

Successfully proving theories and touting great achievements are only two very narrow goals of scholarly research. The true passion and greatest efforts of researchers comes more in the form of confronting assumptions and exploring the obscure.

In many ways, recognizing and sharing the limitations of a research study both allows for and encourages this type of discovery that continuously pushes research forward. By using limitations to provide a transparent account of the project's boundaries and to contextualize the findings, researchers pave the way for even more robust and impactful research in the future.

Charla Viera, MS

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21 Research Limitations Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Research limitations refer to the potential weaknesses inherent in a study. All studies have limitations of some sort, meaning declaring limitations doesn’t necessarily need to be a bad thing, so long as your declaration of limitations is well thought-out and explained.

Rarely is a study perfect. Researchers have to make trade-offs when developing their studies, which are often based upon practical considerations such as time and monetary constraints, weighing the breadth of participants against the depth of insight, and choosing one methodology or another.

In research, studies can have limitations such as limited scope, researcher subjectivity, and lack of available research tools.

Acknowledging the limitations of your study should be seen as a strength. It demonstrates your willingness for transparency, humility, and submission to the scientific method and can bolster the integrity of the study. It can also inform future research direction.

Typically, scholars will explore the limitations of their study in either their methodology section, their conclusion section, or both.

Research Limitations Examples

Qualitative and quantitative research offer different perspectives and methods in exploring phenomena, each with its own strengths and limitations. So, I’ve split the limitations examples sections into qualitative and quantitative below.

Qualitative Research Limitations

Qualitative research seeks to understand phenomena in-depth and in context. It focuses on the ‘why’ and ‘how’ questions.

It’s often used to explore new or complex issues, and it provides rich, detailed insights into participants’ experiences, behaviors, and attitudes. However, these strengths also create certain limitations, as explained below.

1. Subjectivity

Qualitative research often requires the researcher to interpret subjective data. One researcher may examine a text and identify different themes or concepts as more dominant than others.

Close qualitative readings of texts are necessarily subjective – and while this may be a limitation, qualitative researchers argue this is the best way to deeply understand everything in context.

Suggested Solution and Response: To minimize subjectivity bias, you could consider cross-checking your own readings of themes and data against other scholars’ readings and interpretations. This may involve giving the raw data to a supervisor or colleague and asking them to code the data separately, then coming together to compare and contrast results.

2. Researcher Bias

The concept of researcher bias is related to, but slightly different from, subjectivity.

Researcher bias refers to the perspectives and opinions you bring with you when doing your research.

For example, a researcher who is explicitly of a certain philosophical or political persuasion may bring that persuasion to bear when interpreting data.

In many scholarly traditions, we will attempt to minimize researcher bias through the utilization of clear procedures that are set out in advance or through the use of statistical analysis tools.

However, in other traditions, such as in postmodern feminist research , declaration of bias is expected, and acknowledgment of bias is seen as a positive because, in those traditions, it is believed that bias cannot be eliminated from research, so instead, it is a matter of integrity to present it upfront.

Suggested Solution and Response: Acknowledge the potential for researcher bias and, depending on your theoretical framework , accept this, or identify procedures you have taken to seek a closer approximation to objectivity in your coding and analysis.

3. Generalizability

If you’re struggling to find a limitation to discuss in your own qualitative research study, then this one is for you: all qualitative research, of all persuasions and perspectives, cannot be generalized.

This is a core feature that sets qualitative data and quantitative data apart.

The point of qualitative data is to select case studies and similarly small corpora and dig deep through in-depth analysis and thick description of data.

Often, this will also mean that you have a non-randomized sample size.

While this is a positive – you’re going to get some really deep, contextualized, interesting insights – it also means that the findings may not be generalizable to a larger population that may not be representative of the small group of people in your study.

Suggested Solution and Response: Suggest future studies that take a quantitative approach to the question.

4. The Hawthorne Effect

The Hawthorne effect refers to the phenomenon where research participants change their ‘observed behavior’ when they’re aware that they are being observed.

This effect was first identified by Elton Mayo who conducted studies of the effects of various factors ton workers’ productivity. He noticed that no matter what he did – turning up the lights, turning down the lights, etc. – there was an increase in worker outputs compared to prior to the study taking place.

Mayo realized that the mere act of observing the workers made them work harder – his observation was what was changing behavior.

So, if you’re looking for a potential limitation to name for your observational research study , highlight the possible impact of the Hawthorne effect (and how you could reduce your footprint or visibility in order to decrease its likelihood).

Suggested Solution and Response: Highlight ways you have attempted to reduce your footprint while in the field, and guarantee anonymity to your research participants.

5. Replicability

Quantitative research has a great benefit in that the studies are replicable – a researcher can get a similar sample size, duplicate the variables, and re-test a study. But you can’t do that in qualitative research.

Qualitative research relies heavily on context – a specific case study or specific variables that make a certain instance worthy of analysis. As a result, it’s often difficult to re-enter the same setting with the same variables and repeat the study.

Furthermore, the individual researcher’s interpretation is more influential in qualitative research, meaning even if a new researcher enters an environment and makes observations, their observations may be different because subjectivity comes into play much more. This doesn’t make the research bad necessarily (great insights can be made in qualitative research), but it certainly does demonstrate a weakness of qualitative research.

6. Limited Scope

“Limited scope” is perhaps one of the most common limitations listed by researchers – and while this is often a catch-all way of saying, “well, I’m not studying that in this study”, it’s also a valid point.

No study can explore everything related to a topic. At some point, we have to make decisions about what’s included in the study and what is excluded from the study.

So, you could say that a limitation of your study is that it doesn’t look at an extra variable or concept that’s certainly worthy of study but will have to be explored in your next project because this project has a clearly and narrowly defined goal.

Suggested Solution and Response: Be clear about what’s in and out of the study when writing your research question.

7. Time Constraints

This is also a catch-all claim you can make about your research project: that you would have included more people in the study, looked at more variables, and so on. But you’ve got to submit this thing by the end of next semester! You’ve got time constraints.

And time constraints are a recognized reality in all research.

But this means you’ll need to explain how time has limited your decisions. As with “limited scope”, this may mean that you had to study a smaller group of subjects, limit the amount of time you spent in the field, and so forth.

Suggested Solution and Response: Suggest future studies that will build on your current work, possibly as a PhD project.

8. Resource Intensiveness

Qualitative research can be expensive due to the cost of transcription, the involvement of trained researchers, and potential travel for interviews or observations.

So, resource intensiveness is similar to the time constraints concept. If you don’t have the funds, you have to make decisions about which tools to use, which statistical software to employ, and how many research assistants you can dedicate to the study.

Suggested Solution and Response: Suggest future studies that will gain more funding on the back of this ‘ exploratory study ‘.

9. Coding Difficulties

Data analysis in qualitative research often involves coding, which can be subjective and complex, especially when dealing with ambiguous or contradicting data.

After naming this as a limitation in your research, it’s important to explain how you’ve attempted to address this. Some ways to ‘limit the limitation’ include:

• Triangulation: Have 2 other researchers code the data as well and cross-check your results with theirs to identify outliers that may need to be re-examined, debated with the other researchers, or removed altogether.
• Procedure: Use a clear coding procedure to demonstrate reliability in your coding process. I personally use the thematic network analysis method outlined in this academic article by Attride-Stirling (2001).

Suggested Solution and Response: Triangulate your coding findings with colleagues, and follow a thematic network analysis procedure.

10. Risk of Non-Responsiveness

There is always a risk in research that research participants will be unwilling or uncomfortable sharing their genuine thoughts and feelings in the study.

This is particularly true when you’re conducting research on sensitive topics, politicized topics, or topics where the participant is expressing vulnerability .

This is similar to the Hawthorne effect (aka participant bias), where participants change their behaviors in your presence; but it goes a step further, where participants actively hide their true thoughts and feelings from you.

Suggested Solution and Response: One way to manage this is to try to include a wider group of people with the expectation that there will be non-responsiveness from some participants.

11. Risk of Attrition

Attrition refers to the process of losing research participants throughout the study.

This occurs most commonly in longitudinal studies , where a researcher must return to conduct their analysis over spaced periods of time, often over a period of years.

Things happen to people over time – they move overseas, their life experiences change, they get sick, change their minds, and even die. The more time that passes, the greater the risk of attrition.

Suggested Solution and Response: One way to manage this is to try to include a wider group of people with the expectation that there will be attrition over time.

12. Difficulty in Maintaining Confidentiality and Anonymity

Given the detailed nature of qualitative data , ensuring participant anonymity can be challenging.

If you have a sensitive topic in a specific case study, even anonymizing research participants sometimes isn’t enough. People might be able to induce who you’re talking about.

Sometimes, this will mean you have to exclude some interesting data that you collected from your final report. Confidentiality and anonymity come before your findings in research ethics – and this is a necessary limiting factor.

Suggested Solution and Response: Highlight the efforts you have taken to anonymize data, and accept that confidentiality and accountability place extremely important constraints on academic research.

13. Difficulty in Finding Research Participants

A study that looks at a very specific phenomenon or even a specific set of cases within a phenomenon means that the pool of potential research participants can be very low.

Compile on top of this the fact that many people you approach may choose not to participate, and you could end up with a very small corpus of subjects to explore. This may limit your ability to make complete findings, even in a quantitative sense.

You may need to therefore limit your research question and objectives to something more realistic.

Suggested Solution and Response: Highlight that this is going to limit the study’s generalizability significantly.

14. Ethical Limitations

Ethical limitations refer to the things you cannot do based on ethical concerns identified either by yourself or your institution’s ethics review board.

This might include threats to the physical or psychological well-being of your research subjects, the potential of releasing data that could harm a person’s reputation, and so on.

Furthermore, even if your study follows all expected standards of ethics, you still, as an ethical researcher, need to allow a research participant to pull out at any point in time, after which you cannot use their data, which demonstrates an overlap between ethical constraints and participant attrition.

Suggested Solution and Response: Highlight that these ethical limitations are inevitable but important to sustain the integrity of the research.

For more on Qualitative Research, Explore my Qualitative Research Guide

Quantitative Research Limitations

Quantitative research focuses on quantifiable data and statistical, mathematical, or computational techniques. It’s often used to test hypotheses, assess relationships and causality, and generalize findings across larger populations.

Quantitative research is widely respected for its ability to provide reliable, measurable, and generalizable data (if done well!). Its structured methodology has strengths over qualitative research, such as the fact it allows for replication of the study, which underpins the validity of the research.

However, this approach is not without it limitations, explained below.

1. Over-Simplification

Quantitative research is powerful because it allows you to measure and analyze data in a systematic and standardized way. However, one of its limitations is that it can sometimes simplify complex phenomena or situations.

In other words, it might miss the subtleties or nuances of the research subject.

For example, if you’re studying why people choose a particular diet, a quantitative study might identify factors like age, income, or health status. But it might miss other aspects, such as cultural influences or personal beliefs, that can also significantly impact dietary choices.

When writing about this limitation, you can say that your quantitative approach, while providing precise measurements and comparisons, may not capture the full complexity of your subjects of study.

Suggested Solution and Response: Suggest a follow-up case study using the same research participants in order to gain additional context and depth.

2. Lack of Context

Another potential issue with quantitative research is that it often focuses on numbers and statistics at the expense of context or qualitative information.

Let’s say you’re studying the effect of classroom size on student performance. You might find that students in smaller classes generally perform better. However, this doesn’t take into account other variables, like teaching style , student motivation, or family support.

When describing this limitation, you might say, “Although our research provides important insights into the relationship between class size and student performance, it does not incorporate the impact of other potentially influential variables. Future research could benefit from a mixed-methods approach that combines quantitative analysis with qualitative insights.”

3. Applicability to Real-World Settings

Oftentimes, experimental research takes place in controlled environments to limit the influence of outside factors.

This control is great for isolation and understanding the specific phenomenon but can limit the applicability or “external validity” of the research to real-world settings.

For example, if you conduct a lab experiment to see how sleep deprivation impacts cognitive performance, the sterile, controlled lab environment might not reflect real-world conditions where people are dealing with multiple stressors.

Therefore, when explaining the limitations of your quantitative study in your methodology section, you could state:

“While our findings provide valuable information about [topic], the controlled conditions of the experiment may not accurately represent real-world scenarios where extraneous variables will exist. As such, the direct applicability of our results to broader contexts may be limited.”

Suggested Solution and Response: Suggest future studies that will engage in real-world observational research, such as ethnographic research.

4. Limited Flexibility

Once a quantitative study is underway, it can be challenging to make changes to it. This is because, unlike in grounded research, you’re putting in place your study in advance, and you can’t make changes part-way through.

Your study design, data collection methods, and analysis techniques need to be decided upon before you start collecting data.

For example, if you are conducting a survey on the impact of social media on teenage mental health, and halfway through, you realize that you should have included a question about their screen time, it’s generally too late to add it.

When discussing this limitation, you could write something like, “The structured nature of our quantitative approach allows for consistent data collection and analysis but also limits our flexibility to adapt and modify the research process in response to emerging insights and ideas.”

Suggested Solution and Response: Suggest future studies that will use mixed-methods or qualitative research methods to gain additional depth of insight.

5. Risk of Survey Error

Surveys are a common tool in quantitative research, but they carry risks of error.

There can be measurement errors (if a question is misunderstood), coverage errors (if some groups aren’t adequately represented), non-response errors (if certain people don’t respond), and sampling errors (if your sample isn’t representative of the population).

For instance, if you’re surveying college students about their study habits , but only daytime students respond because you conduct the survey during the day, your results will be skewed.

In discussing this limitation, you might say, “Despite our best efforts to develop a comprehensive survey, there remains a risk of survey error, including measurement, coverage, non-response, and sampling errors. These could potentially impact the reliability and generalizability of our findings.”

Suggested Solution and Response: Suggest future studies that will use other survey tools to compare and contrast results.

6. Limited Ability to Probe Answers

With quantitative research, you typically can’t ask follow-up questions or delve deeper into participants’ responses like you could in a qualitative interview.

For instance, imagine you are surveying 500 students about study habits in a questionnaire. A respondent might indicate that they study for two hours each night. You might want to follow up by asking them to elaborate on what those study sessions involve or how effective they feel their habits are.

However, quantitative research generally disallows this in the way a qualitative semi-structured interview could.

When discussing this limitation, you might write, “Given the structured nature of our survey, our ability to probe deeper into individual responses is limited. This means we may not fully understand the context or reasoning behind the responses, potentially limiting the depth of our findings.”

Suggested Solution and Response: Suggest future studies that engage in mixed-method or qualitative methodologies to address the issue from another angle.

7. Reliance on Instruments for Data Collection

In quantitative research, the collection of data heavily relies on instruments like questionnaires, surveys, or machines.

The limitation here is that the data you get is only as good as the instrument you’re using. If the instrument isn’t designed or calibrated well, your data can be flawed.

For instance, if you’re using a questionnaire to study customer satisfaction and the questions are vague, confusing, or biased, the responses may not accurately reflect the customers’ true feelings.

When discussing this limitation, you could say, “Our study depends on the use of questionnaires for data collection. Although we have put significant effort into designing and testing the instrument, it’s possible that inaccuracies or misunderstandings could potentially affect the validity of the data collected.”

Suggested Solution and Response: Suggest future studies that will use different instruments but examine the same variables to triangulate results.

8. Time and Resource Constraints (Specific to Quantitative Research)

Quantitative research can be time-consuming and resource-intensive, especially when dealing with large samples.

It often involves systematic sampling, rigorous design, and sometimes complex statistical analysis.

If resources and time are limited, it can restrict the scale of your research, the techniques you can employ, or the extent of your data analysis.

For example, you may want to conduct a nationwide survey on public opinion about a certain policy. However, due to limited resources, you might only be able to survey people in one city.

When writing about this limitation, you could say, “Given the scope of our research and the resources available, we are limited to conducting our survey within one city, which may not fully represent the nationwide public opinion. Hence, the generalizability of the results may be limited.”

Suggested Solution and Response: Suggest future studies that will have more funding or longer timeframes.

How to Discuss Your Research Limitations

1. in your research proposal and methodology section.

In the research proposal, which will become the methodology section of your dissertation, I would recommend taking the four following steps, in order:

• Be Explicit about your Scope – If you limit the scope of your study in your research question, aims, and objectives, then you can set yourself up well later in the methodology to say that certain questions are “outside the scope of the study.” For example, you may identify the fact that the study doesn’t address a certain variable, but you can follow up by stating that the research question is specifically focused on the variable that you are examining, so this limitation would need to be looked at in future studies.
• Acknowledge the Limitation – Acknowledging the limitations of your study demonstrates reflexivity and humility and can make your research more reliable and valid. It also pre-empts questions the people grading your paper may have, so instead of them down-grading you for your limitations; they will congratulate you on explaining the limitations and how you have addressed them!
• Explain your Decisions – You may have chosen your approach (despite its limitations) for a very specific reason. This might be because your approach remains, on balance, the best one to answer your research question. Or, it might be because of time and monetary constraints that are outside of your control.
• Highlight the Strengths of your Approach – Conclude your limitations section by strongly demonstrating that, despite limitations, you’ve worked hard to minimize the effects of the limitations and that you have chosen your specific approach and methodology because it’s also got some terrific strengths. Name the strengths.

Overall, you’ll want to acknowledge your own limitations but also explain that the limitations don’t detract from the value of your study as it stands.

2. In the Conclusion Section or Chapter

In the conclusion of your study, it is generally expected that you return to a discussion of the study’s limitations. Here, I recommend the following steps:

• Acknowledge issues faced – After completing your study, you will be increasingly aware of issues you may have faced that, if you re-did the study, you may have addressed earlier in order to avoid those issues. Acknowledge these issues as limitations, and frame them as recommendations for subsequent studies.
• Suggest further research – Scholarly research aims to fill gaps in the current literature and knowledge. Having established your expertise through your study, suggest lines of inquiry for future researchers. You could state that your study had certain limitations, and “future studies” can address those limitations.
• Suggest a mixed methods approach – Qualitative and quantitative research each have pros and cons. So, note those ‘cons’ of your approach, then say the next study should approach the topic using the opposite methodology or could approach it using a mixed-methods approach that could achieve the benefits of quantitative studies with the nuanced insights of associated qualitative insights as part of an in-study case-study.

Overall, be clear about both your limitations and how those limitations can inform future studies.

In sum, each type of research method has its own strengths and limitations. Qualitative research excels in exploring depth, context, and complexity, while quantitative research excels in examining breadth, generalizability, and quantifiable measures. Despite their individual limitations, each method contributes unique and valuable insights, and researchers often use them together to provide a more comprehensive understanding of the phenomenon being studied.

Attride-Stirling, J. (2001). Thematic networks: an analytic tool for qualitative research. Qualitative research , 1 (3), 385-405. ( Source )

Atkinson, P., Delamont, S., Cernat, A., Sakshaug, J., & Williams, R. A. (2021).  SAGE research methods foundations . London: Sage Publications.

Clark, T., Foster, L., Bryman, A., & Sloan, L. (2021).  Bryman’s social research methods . Oxford: Oxford University Press.

Köhler, T., Smith, A., & Bhakoo, V. (2022). Templates in qualitative research methods: Origins, limitations, and new directions.  Organizational Research Methods ,  25 (2), 183-210. ( Source )

Lenger, A. (2019). The rejection of qualitative research methods in economics.  Journal of Economic Issues ,  53 (4), 946-965. ( Source )

Taherdoost, H. (2022). What are different research approaches? Comprehensive review of qualitative, quantitative, and mixed method research, their applications, types, and limitations.  Journal of Management Science & Engineering Research ,  5 (1), 53-63. ( Source )

Walliman, N. (2021).  Research methods: The basics . New York: Routledge.

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What are the limitations in research and how to write them?

Learn about the potential limitations in research and how to appropriately address them in order to deliver honest and ethical research.

It is fairly uncommon for researchers to stumble into the term research limitations when working on their research paper. Limitations in research can arise owing to constraints on design, methods, materials, and so on, and these aspects, unfortunately, may have an influence on your subject’s findings.

In this Mind The Graph’s article, we’ll discuss some recommendations for writing limitations in research , provide examples of various common types of limitations, and suggest how to properly present this information.

What are the limitations in research?

The limitations in research are the constraints in design, methods or even researchers’ limitations that affect and influence the interpretation of your research’s ultimate findings. These are limitations on the generalization and usability of findings that emerge from the design of the research and/or the method employed to ensure validity both internally and externally. 

Researchers are usually cautious to acknowledge the limitations of their research in their publications for fear of undermining the research’s scientific validity. No research is faultless or covers every possible angle. As a result, addressing the constraints of your research exhibits honesty and integrity .

Why should include limitations of research in my paper?

Though limitations tackle potential flaws in research, commenting on them at the conclusion of your paper, by demonstrating that you are aware of these limitations and explaining how they impact the conclusions that may be taken from the research, improves your research by disclosing any issues before other researchers or reviewers do . 

Additionally, emphasizing research constraints implies that you have thoroughly investigated the ramifications of research shortcomings and have a thorough understanding of your research problem. 

Limits exist in any research; being honest about them and explaining them would impress researchers and reviewers more than disregarding them. 

Remember that acknowledging a research’s shortcomings offers a chance to provide ideas for future research, but be careful to describe how your study may help to concentrate on these outstanding problems.

Possible limitations examples

Here are some limitations connected to methodology and the research procedure that you may need to explain and discuss in connection to your findings.

Methodological limitations

Sample size.

The number of units of analysis used in your study is determined by the sort of research issue being investigated. It is important to note that if your sample is too small, finding significant connections in the data will be challenging, as statistical tests typically require a larger sample size to ensure a fair representation and this can be limiting. 

Lack of available or reliable data

A lack of data or trustworthy data will almost certainly necessitate limiting the scope of your research or the size of your sample, or it can be a substantial impediment to identifying a pattern and a relevant connection.

Lack of prior research on the subject

Citing previous research papers forms the basis of your literature review and aids in comprehending the research subject you are researching. Yet there may be little if any, past research on your issue.

The measure used to collect data

After finishing your analysis of the findings, you realize that the method you used to collect data limited your capacity to undertake a comprehensive evaluation of the findings. Recognize the flaw by mentioning that future researchers should change the specific approach for data collection.

Issues with research samples and selection

Sampling inaccuracies arise when a probability sampling method is employed to choose a sample, but that sample does not accurately represent the overall population or the relevant group. As a result, your study suffers from “sampling bias” or “selection bias.”

Limitations of the research

When your research requires polling certain persons or a specific group, you may have encountered the issue of limited access to these interviewees. Because of the limited access, you may need to reorganize or rearrange your research. In this scenario, explain why access is restricted and ensure that your findings are still trustworthy and valid despite the constraint.

Time constraints

Practical difficulties may limit the amount of time available to explore a research issue and monitor changes as they occur. If time restrictions have any detrimental influence on your research, recognize this impact by expressing the necessity for a future investigation.

Due to their cultural origins or opinions on observed events, researchers may carry biased opinions, which can influence the credibility of a research. Furthermore, researchers may exhibit biases toward data and conclusions that only support their hypotheses or arguments.

The structure of the limitations section 

The limitations of your research are usually stated at the beginning of the discussion section of your paper so that the reader is aware of and comprehends the limitations prior to actually reading the rest of your findings, or they are stated at the end of the discussion section as an acknowledgment of the need for further research.

The ideal way is to divide your limitations section into three steps: 

1. Identify the research constraints; 

2. Describe in great detail how they affect your research; 

3. Mention the opportunity for future investigations and give possibilities. 

By following this method while addressing the constraints of your research, you will be able to effectively highlight your research’s shortcomings without jeopardizing the quality and integrity of your research.

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How to present limitations in research

Last updated

30 January 2024

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Limitations don’t invalidate or diminish your results, but it’s best to acknowledge them. This will enable you to address any questions your study failed to answer because of them.

In this guide, learn how to recognize, present, and overcome limitations in research.

• What is a research limitation?

Research limitations are weaknesses in your research design or execution that may have impacted outcomes and conclusions. Uncovering limitations doesn’t necessarily indicate poor research design—it just means you encountered challenges you couldn’t have anticipated that limited your research efforts.

Does basic research have limitations?

Basic research aims to provide more information about your research topic . It requires the same standard research methodology and data collection efforts as any other research type, and it can also have limitations.

• Common research limitations

Researchers encounter common limitations when embarking on a study. Limitations can occur in relation to the methods you apply or the research process you design. They could also be connected to you as the researcher.

Methodology limitations

Not having access to data or reliable information can impact the methods used to facilitate your research. A lack of data or reliability may limit the parameters of your study area and the extent of your exploration.

Your sample size may also be affected because you won’t have any direction on how big or small it should be and who or what you should include. Having too few participants won’t adequately represent the population or groups of people needed to draw meaningful conclusions.

Research process limitations

The study’s design can impose constraints on the process. For example, as you’re conducting the research, issues may arise that don’t conform to the data collection methodology you developed. You may not realize until well into the process that you should have incorporated more specific questions or comprehensive experiments to generate the data you need to have confidence in your results.

Constraints on resources can also have an impact. Being limited on participants or participation incentives may limit your sample sizes. Insufficient tools, equipment, and materials to conduct a thorough study may also be a factor.

Common researcher limitations

Here are some of the common researcher limitations you may encounter:

Time: some research areas require multi-year longitudinal approaches, but you might not be able to dedicate that much time. Imagine you want to measure how much memory a person loses as they age. This may involve conducting multiple tests on a sample of participants over 20–30 years, which may be impossible.

Bias: researchers can consciously or unconsciously apply bias to their research. Biases can contribute to relying on research sources and methodologies that will only support your beliefs about the research you’re embarking on. You might also omit relevant issues or participants from the scope of your study because of your biases.

Limited access to data : you may need to pay to access specific databases or journals that would be helpful to your research process. You might also need to gain information from certain people or organizations but have limited access to them. These cases require readjusting your process and explaining why your findings are still reliable.

• Why is it important to identify limitations?

Identifying limitations adds credibility to research and provides a deeper understanding of how you arrived at your conclusions.

Constraints may have prevented you from collecting specific data or information you hoped would prove or disprove your hypothesis or provide a more comprehensive understanding of your research topic.

However, identifying the limitations contributing to your conclusions can inspire further research efforts that help gather more substantial information and data.

• Where to put limitations in a research paper

A research paper is broken up into different sections that appear in the following order:

Introduction

Methodology

The discussion portion of your paper explores your findings and puts them in the context of the overall research. Either place research limitations at the beginning of the discussion section before the analysis of your findings or at the end of the section to indicate that further research needs to be pursued.

What not to include in the limitations section

Evidence that doesn’t support your hypothesis is not a limitation, so you shouldn’t include it in the limitation section. Don’t just list limitations and their degree of severity without further explanation.

• How to present limitations

You’ll want to present the limitations of your study in a way that doesn’t diminish the validity of your research and leave the reader wondering if your results and conclusions have been compromised.

Include only the limitations that directly relate to and impact how you addressed your research questions. Following a specific format enables the reader to develop an understanding of the weaknesses within the context of your findings without doubting the quality and integrity of your research.

Identify the limitations specific to your study

You don’t have to identify every possible limitation that might have occurred during your research process. Only identify those that may have influenced the quality of your findings and your ability to answer your research question.

Explain study limitations in detail

This explanation should be the most significant portion of your limitation section.

Link each limitation with an interpretation and appraisal of their impact on the study. You’ll have to evaluate and explain whether the error, method, or validity issues influenced the study’s outcome and how.

Propose a direction for future studies and present alternatives

In this section, suggest how researchers can avoid the pitfalls you experienced during your research process.

If an issue with methodology was a limitation, propose alternate methods that may help with a smoother and more conclusive research project . Discuss the pros and cons of your alternate recommendation.

Describe steps taken to minimize each limitation

You probably took steps to try to address or mitigate limitations when you noticed them throughout the course of your research project. Describe these steps in the limitation section.

• Limitation example

“Approaches like stem cell transplantation and vaccination in AD [Alzheimer’s disease] work on a cellular or molecular level in the laboratory. However, translation into clinical settings will remain a challenge for the next decade.”

The authors are saying that even though these methods showed promise in helping people with memory loss when conducted in the lab (in other words, using animal studies), more studies are needed. These may be controlled clinical trials, for example. 

However, the short life span of stem cells outside the lab and the vaccination’s severe inflammatory side effects are limitations. Researchers won’t be able to conduct clinical trials until these issues are overcome.

• How to overcome limitations in research

You’ve already started on the road to overcoming limitations in research by acknowledging that they exist. However, you need to ensure readers don’t mistake weaknesses for errors within your research design.

To do this, you’ll need to justify and explain your rationale for the methods, research design, and analysis tools you chose and how you noticed they may have presented limitations.

Your readers need to know that even when limitations presented themselves, you followed best practices and the ethical standards of your field. You didn’t violate any rules and regulations during your research process.

You’ll also want to reinforce the validity of your conclusions and results with multiple sources, methods, and perspectives. This prevents readers from assuming your findings were derived from a single or biased source.

• Learning and improving starts with limitations in research

Dealing with limitations with transparency and integrity helps identify areas for future improvements and developments. It’s a learning process, providing valuable insights into how you can improve methodologies, expand sample sizes, or explore alternate approaches to further support the validity of your findings.

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• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Limitations of the Study
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research. Study limitations are the constraints placed on the ability to generalize from the results, to further describe applications to practice, and/or related to the utility of findings that are the result of the ways in which you initially chose to design the study or the method used to establish internal and external validity or the result of unanticipated challenges that emerged during the study.

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Theofanidis, Dimitrios and Antigoni Fountouki. "Limitations and Delimitations in the Research Process." Perioperative Nursing 7 (September-December 2018): 155-163. .

Importance of...

Always acknowledge a study's limitations. It is far better that you identify and acknowledge your study’s limitations than to have them pointed out by your professor and have your grade lowered because you appeared to have ignored them or didn't realize they existed.

Keep in mind that acknowledgment of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgment of a study's limitations also provides you with opportunities to demonstrate that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but also to confront assumptions and explore what we don't know.

Claiming limitations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the results and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in the introduction of your paper.

Here are examples of limitations related to methodology and the research process you may need to describe and discuss how they possibly impacted your results. Note that descriptions of limitations should be stated in the past tense because they were discovered after you completed your research.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred. Note that sample size is generally less relevant in qualitative research if explained in the context of the research problem.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but provide cogent reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe a need for future research based on designing a different method for gathering data.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, though, consult with a librarian! In cases when a librarian has confirmed that there is little or no prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design ]. Note again that discovering a limitation can serve as an important opportunity to identify new gaps in the literature and to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need for future researchers to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to the accuracy of what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data can contain several potential sources of bias that you should be alert to and note as limitations. These biases become apparent if they are incongruent with data from other sources. These are: (1) selective memory [remembering or not remembering experiences or events that occurred at some point in the past]; (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency, but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, data, or documents and, for whatever reason, access is denied or limited in some way, the reasons for this needs to be described. Also, include an explanation why being denied or limited access did not prevent you from following through on your study.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single topic, the time available to investigate a research problem and to measure change or stability over time is constrained by the due date of your assignment. Be sure to choose a research problem that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure whether you can complete your research within the confines of the assignment's due date, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, event, or thing is viewed or shown in a consistently inaccurate way. Bias is usually negative, though one can have a positive bias as well, especially if that bias reflects your reliance on research that only support your hypothesis. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places, how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation. NOTE :   If you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating that bias. For example, if a previous study only used boys to examine how music education supports effective math skills, describe how your research expands the study to include girls.
• Fluency in a language -- if your research focuses , for example, on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic or to speak with these students in their primary language. This deficiency should be acknowledged.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods. Powerpoint Presentation. Regent University of Science and Technology; ter Riet, Gerben et al. “All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies.” PLOS One 8 (November 2013): 1-6.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed. January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Writing Tip

Don't Inflate the Importance of Your Findings!

After all the hard work and long hours devoted to writing your research paper, it is easy to get carried away with attributing unwarranted importance to what you’ve done. We all want our academic work to be viewed as excellent and worthy of a good grade, but it is important that you understand and openly acknowledge the limitations of your study. Inflating the importance of your study's findings could be perceived by your readers as an attempt hide its flaws or encourage a biased interpretation of the results. A small measure of humility goes a long way!

Another Writing Tip

Negative Results are Not a Limitation!

Negative evidence refers to findings that unexpectedly challenge rather than support your hypothesis. If you didn't get the results you anticipated, it may mean your hypothesis was incorrect and needs to be reformulated. Or, perhaps you have stumbled onto something unexpected that warrants further study. Moreover, the absence of an effect may be very telling in many situations, particularly in experimental research designs. In any case, your results may very well be of importance to others even though they did not support your hypothesis. Do not fall into the trap of thinking that results contrary to what you expected is a limitation to your study. If you carried out the research well, they are simply your results and only require additional interpretation.

Lewis, George H. and Jonathan F. Lewis. “The Dog in the Night-Time: Negative Evidence in Social Research.” The British Journal of Sociology 31 (December 1980): 544-558.

Yet Another Writing Tip

Sample Size Limitations in Qualitative Research

Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework. However, it remains true that sample sizes that are too small cannot adequately support claims of having achieved valid conclusions and sample sizes that are too large do not permit the deep, naturalistic, and inductive analysis that defines qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be applied and the particular research method and purposeful sampling strategy employed. If the sample size is found to be a limitation, it may reflect your judgment about the methodological technique chosen [e.g., single life history study versus focus group interviews] rather than the number of respondents used.

Boddy, Clive Roland. "Sample Size for Qualitative Research." Qualitative Market Research: An International Journal 19 (2016): 426-432; Huberman, A. Michael and Matthew B. Miles. "Data Management and Analysis Methods." In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 428-444; Blaikie, Norman. "Confounding Issues Related to Determining Sample Size in Qualitative Research." International Journal of Social Research Methodology 21 (2018): 635-641; Oppong, Steward Harrison. "The Problem of Sampling in qualitative Research." Asian Journal of Management Sciences and Education 2 (2013): 202-210.

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Stating the Obvious: Writing Assumptions, Limitations, and Delimitations

During the process of writing your thesis or dissertation, you might suddenly realize that your research has inherent flaws. Don’t worry! Virtually all projects contain restrictions to your research. However, being able to recognize and accurately describe these problems is the difference between a true researcher and a grade-school kid with a science-fair project. Concerns with truthful responding, access to participants, and survey instruments are just a few of examples of restrictions on your research. In the following sections, the differences among delimitations, limitations, and assumptions of a dissertation will be clarified.

Delimitations

Delimitations are the definitions you set as the boundaries of your own thesis or dissertation, so delimitations are in your control. Delimitations are set so that your goals do not become impossibly large to complete. Examples of delimitations include objectives, research questions, variables, theoretical objectives that you have adopted, and populations chosen as targets to study. When you are stating your delimitations, clearly inform readers why you chose this course of study. The answer might simply be that you were curious about the topic and/or wanted to improve standards of a professional field by revealing certain findings. In any case, you should clearly list the other options available and the reasons why you did not choose these options immediately after you list your delimitations. You might have avoided these options for reasons of practicality, interest, or relativity to the study at hand. For example, you might have only studied Hispanic mothers because they have the highest rate of obese babies. Delimitations are often strongly related to your theory and research questions. If you were researching whether there are different parenting styles between unmarried Asian, Caucasian, African American, and Hispanic women, then a delimitation of your study would be the inclusion of only participants with those demographics and the exclusion of participants from other demographics such as men, married women, and all other ethnicities of single women (inclusion and exclusion criteria). A further delimitation might be that you only included closed-ended Likert scale responses in the survey, rather than including additional open-ended responses, which might make some people more willing to take and complete your survey. Remember that delimitations are not good or bad. They are simply a detailed description of the scope of interest for your study as it relates to the research design. Don’t forget to describe the philosophical framework you used throughout your study, which also delimits your study.

Limitations

Limitations of a dissertation are potential weaknesses in your study that are mostly out of your control, given limited funding, choice of research design, statistical model constraints, or other factors. In addition, a limitation is a restriction on your study that cannot be reasonably dismissed and can affect your design and results. Do not worry about limitations because limitations affect virtually all research projects, as well as most things in life. Even when you are going to your favorite restaurant, you are limited by the menu choices. If you went to a restaurant that had a menu that you were craving, you might not receive the service, price, or location that makes you enjoy your favorite restaurant. If you studied participants’ responses to a survey, you might be limited in your abilities to gain the exact type or geographic scope of participants you wanted. The people whom you managed to get to take your survey may not truly be a random sample, which is also a limitation. If you used a common test for data findings, your results are limited by the reliability of the test. If your study was limited to a certain amount of time, your results are affected by the operations of society during that time period (e.g., economy, social trends). It is important for you to remember that limitations of a dissertation are often not something that can be solved by the researcher. Also, remember that whatever limits you also limits other researchers, whether they are the largest medical research companies or consumer habits corporations. Certain kinds of limitations are often associated with the analytical approach you take in your research, too. For example, some qualitative methods like heuristics or phenomenology do not lend themselves well to replicability. Also, most of the commonly used quantitative statistical models can only determine correlation, but not causation.

Assumptions

Assumptions are things that are accepted as true, or at least plausible, by researchers and peers who will read your dissertation or thesis. In other words, any scholar reading your paper will assume that certain aspects of your study is true given your population, statistical test, research design, or other delimitations. For example, if you tell your friend that your favorite restaurant is an Italian place, your friend will assume that you don’t go there for the sushi. It’s assumed that you go there to eat Italian food. Because most assumptions are not discussed in-text, assumptions that are discussed in-text are discussed in the context of the limitations of your study, which is typically in the discussion section. This is important, because both assumptions and limitations affect the inferences you can draw from your study. One of the more common assumptions made in survey research is the assumption of honesty and truthful responses. However, for certain sensitive questions this assumption may be more difficult to accept, in which case it would be described as a limitation of the study. For example, asking people to report their criminal behavior in a survey may not be as reliable as asking people to report their eating habits. It is important to remember that your limitations and assumptions should not contradict one another. For instance, if you state that generalizability is a limitation of your study given that your sample was limited to one city in the United States, then you should not claim generalizability to the United States population as an assumption of your study. Statistical models in quantitative research designs are accompanied with assumptions as well, some more strict than others. These assumptions generally refer to the characteristics of the data, such as distributions, correlational trends, and variable type, just to name a few. Violating these assumptions can lead to drastically invalid results, though this often depends on sample size and other considerations.

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Writing Limitations of Research Study — 4 Reasons Why It Is Important!

It is not unusual for researchers to come across the term limitations of research during their academic paper writing. More often this is interpreted as something terrible. However, when it comes to research study, limitations can help structure the research study better. Therefore, do not underestimate significance of limitations of research study.

Allow us to take you through the context of how to evaluate the limits of your research and conclude an impactful relevance to your results.

Table of Contents

What Are the Limitations of a Research Study?

Every research has its limit and these limitations arise due to restrictions in methodology or research design.  This could impact your entire research or the research paper you wish to publish. Unfortunately, most researchers choose not to discuss their limitations of research fearing it will affect the value of their article in the eyes of readers.

However, it is very important to discuss your study limitations and show it to your target audience (other researchers, journal editors, peer reviewers etc.). It is very important that you provide an explanation of how your research limitations may affect the conclusions and opinions drawn from your research. Moreover, when as an author you state the limitations of research, it shows that you have investigated all the weaknesses of your study and have a deep understanding of the subject. Being honest could impress your readers and mark your study as a sincere effort in research.

Why and Where Should You Include the Research Limitations?

The main goal of your research is to address your research objectives. Conduct experiments, get results and explain those results, and finally justify your research question . It is best to mention the limitations of research in the discussion paragraph of your research article.

At the very beginning of this paragraph, immediately after highlighting the strengths of the research methodology, you should write down your limitations. You can discuss specific points from your research limitations as suggestions for further research in the conclusion of your thesis.

1. Common Limitations of the Researchers

Limitations that are related to the researcher must be mentioned. This will help you gain transparency with your readers. Furthermore, you could provide suggestions on decreasing these limitations in you and your future studies.

2. Limited Access to Information

Your work may involve some institutions and individuals in research, and sometimes you may have problems accessing these institutions. Therefore, you need to redesign and rewrite your work. You must explain your readers the reason for limited access.

3. Limited Time

All researchers are bound by their deadlines when it comes to completing their studies. Sometimes, time constraints can affect your research negatively. However, the best practice is to acknowledge it and mention a requirement for future study to solve the research problem in a better way.

4. Conflict over Biased Views and Personal Issues

Biased views can affect the research. In fact, researchers end up choosing only those results and data that support their main argument, keeping aside the other loose ends of the research.

Types of Limitations of Research

Before beginning your research study, know that there are certain limitations to what you are testing or possible research results. There are different types that researchers may encounter, and they all have unique characteristics, such as:

1. Research Design Limitations

Certain restrictions on your research or available procedures may affect your final results or research outputs. You may have formulated research goals and objectives too broadly. However, this can help you understand how you can narrow down the formulation of research goals and objectives, thereby increasing the focus of your study.

2. Impact Limitations

Even if your research has excellent statistics and a strong design, it can suffer from the influence of the following factors:

• Presence of increasing findings as researched
• Being population specific
• A strong regional focus.

3. Data or statistical limitations

In some cases, it is impossible to collect sufficient data for research or very difficult to get access to the data. This could lead to incomplete conclusion to your study. Moreover, this insufficiency in data could be the outcome of your study design. The unclear, shabby research outline could produce more problems in interpreting your findings.

How to Correctly Structure Your Research Limitations?

There are strict guidelines for narrowing down research questions, wherein you could justify and explain potential weaknesses of your academic paper. You could go through these basic steps to get a well-structured clarity of research limitations:

• Declare that you wish to identify your limitations of research and explain their importance,
• Provide the necessary depth, explain their nature, and justify your study choices.
• Write how you are suggesting that it is possible to overcome them in the future.

In this section, your readers will see that you are aware of the potential weaknesses in your business, understand them and offer effective solutions, and it will positively strengthen your article as you clarify all limitations of research to your target audience.

Know that you cannot be perfect and there is no individual without flaws. You could use the limitations of research as a great opportunity to take on a new challenge and improve the future of research. In a typical academic paper, research limitations may relate to:

1. Formulating your goals and objectives

If you formulate goals and objectives too broadly, your work will have some shortcomings. In this case, specify effective methods or ways to narrow down the formula of goals and aim to increase your level of study focus.

2. Application of your data collection methods in research

If you do not have experience in primary data collection, there is a risk that there will be flaws in the implementation of your methods. It is necessary to accept this, and learn and educate yourself to understand data collection methods.

3. Sample sizes

This depends on the nature of problem you choose. Sample size is of a greater importance in quantitative studies as opposed to qualitative ones. If your sample size is too small, statistical tests cannot identify significant relationships or connections within a given data set.

You could point out that other researchers should base the same study on a larger sample size to get more accurate results.

4. The absence of previous studies in the field you have chosen

Writing a literature review is an important step in any scientific study because it helps researchers determine the scope of current work in the chosen field. It is a major foundation for any researcher who must use them to achieve a set of specific goals or objectives.

However, if you are focused on the most current and evolving research problem or a very narrow research problem, there may be very little prior research on your topic. For example, if you chose to explore the role of Bitcoin as the currency of the future, you may not find tons of scientific papers addressing the research problem as Bitcoins are only a new phenomenon.

It is important that you learn to identify research limitations examples at each step. Whatever field you choose, feel free to add the shortcoming of your work. This is mainly because you do not have many years of experience writing scientific papers or completing complex work. Therefore, the depth and scope of your discussions may be compromised at different levels compared to academics with a lot of expertise. Include specific points from limitations of research. Use them as suggestions for the future.

Have you ever faced a challenge of writing the limitations of research study in your paper? How did you overcome it? What ways did you follow? Were they beneficial? Let us know in the comments below!

Frequently Asked Questions

Setting limitations in our study helps to clarify the outcomes drawn from our research and enhance understanding of the subject. Moreover, it shows that the author has investigated all the weaknesses in the study.

Scope is the range and limitations of a research project which are set to define the boundaries of a project. Limitations are the impacts on the overall study due to the constraints on the research design.

Limitation in research is an impact of a constraint on the research design in the overall study. They are the flaws or weaknesses in the study, which may influence the outcome of the research.

1. Limitations in research can be written as follows: Formulate your goals and objectives 2. Analyze the chosen data collection method and the sample sizes 3. Identify your limitations of research and explain their importance 4. Provide the necessary depth, explain their nature, and justify your study choices 5. Write how you are suggesting that it is possible to overcome them in the future

Excellent article ,,,it has helped me big

This is very helpful information. It has given me an insight on how to go about my study limitations.

Good comments and helpful

the topic is well covered

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Limitations in Research – A Simplified Guide with Examples

Limitations are flaws and shortcomings of your study. It is very important that you discuss the limitations of your study in the discussion section of your research paper. In this blog, we provide tips for presenting study limitations in your paper along with some real-world examples.

1. Should I Report the Limitations of My Work?

Most studies will have some form of limitation. So be honest and don’t hide your limitations. You have to tell your readers how your limitations might influence the outcomes and conclusions of your research.  In reality, your readers and reviewers will be impressed with your paper if you are upfront about your limitations. 

2. Examples

Let’s look at some examples. We have selected a variety of examples from different research topics.

2.1. Limitations Example 1

Following example is from a Medical research paper.

✔ The authors talk about the limitations and emphasis the importance of reconfirming the findings in a much larger study Study design and small sample size are important limitations. This could have led to an overestimation of the effect. Future research should reconfirm these findings by conducting larger-scale studies. _   Limitation s  _   How it might affect the results?   _   How to fix the limitation?

The authors are saying that the main limitations of the study are the small sample size and weak study design. Then they explain how this might have affected their results. They are saying that it is possible that they are overestimating the actual effect they are measuring. Then finally they are telling the readers that more studies with larger sample sizes should be conducted to reconfirm the findings.

As you can see, the authors are clearly explaining three things here: (1) What is the limitation? (2) How it might affect the study outcomes? and (3) What should be done to address the limitation?

2.2. Limitations Example 2

Following example is from an Engineering research paper.

✔ The authors are acknowledging the limitations and warning readers against generalizing the research findings However, some study limitations should be acknowledged. The experiments do not fully consider the problems that can appear in real situations. Hence, caution should be taken with generalizing the findings and applying them to real-life situations. _   Acknowledging limitations   _   Explaining the limitation   _   How it might affect the results?

The authors acknowledge that their study has some limitations. Then they explain what the limitations are. They are saying that their experiments do not consider all problems that might occur in real-life situations. Then they explain how this might affect their research outcomes. They are saying that readers should be careful when generalizing the results to practical real-world situations, because there is a possibility that the methods might fail.

2.3. Limitations Example 3

It is important to remember not to end your paper with limitations. Finish your paper on a positive note by telling your readers about the benefits of your research and possible future directions. In the following example, right after listing the limitations, the authors proceed to talk about the positive aspects of the work.

✔ The authors finish their paper on a positive note by talking about the benefits of their work and possible future work With this limited study, it is not known whether this finding can be applied to all clinical scenarios. Notwithstanding these limitations, this study has proven that Ultrasound can potentially serve as a more efficient alternative to X-rays in diagnosis. Future directions include studying the effects of different ultrasound pulsing schemes on pain relief. Another interesting direction would be to consider applications in nonhuman primates. _   Limitations   _   Benefits of the work   _   Possible future directions

The authors are saying that their experiments were somewhat limited and are not sure if their findings apply to the wider clinical practice. Then the authors highlight the benefits of their research. The authors say that their study has proven that ultrasound can be used instead of X-rays for diagnosis of certain types of diseases. Then they are explaining how future research can extend this work further. The authors are suggesting that it will be interesting to explore if ultrasound can be used for the treatment of chronic pain. And they are also suggesting that future studies can explore treating certain types of animal diseases with ultrasound. This is a very good example of how to finish the discussion section of your paper on a positive note.

Limitations are a vital component of the discussion section of your research paper. Remember, every study has limitations. There is no such thing as a perfect study. One of the major mistakes beginner writers make is hiding the limitations in the paper. Don’t do this, reviewers will reject your paper. Explain clearly how your limitations might have impacted your results, and provide ideas to mitigate them in the future. For further reading, please refer to our blogs on handling negative results and advanced tactics to address study limitations.

If you have any questions, please drop a comment below, and we will answer as soon as possible. We also recommend you to refer to our other blogs on  academic writing tools ,   academic writing resources ,  academic writing phrases  and  research paper examples  which are relevant to the topic discussed in this blog. 

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How to Present the Limitations of a Study in Research?

The limitations of the study convey to the reader how and under which conditions your study results will be evaluated. Scientific research involves investigating research topics, both known and unknown, which inherently includes an element of risk. The risk could arise due to human errors, barriers to data gathering, limited availability of resources, and researcher bias. Researchers are encouraged to discuss the limitations of their research to enhance the process of research, as well as to allow readers to gain an understanding of the study’s framework and value.

Limitations of the research are the constraints placed on the ability to generalize from the results and to further describe applications to practice. It is related to the utility value of the findings based on how you initially chose to design the study, the method used to establish internal and external validity, or the result of unanticipated challenges that emerged during the study. Knowing about these limitations and their impact can explain how the limitations of your study can affect the conclusions and thoughts drawn from your research. 1

Table of Contents

What are the limitations of a study

Researchers are probably cautious to acknowledge what the limitations of the research can be for fear of undermining the validity of the research findings. No research can be faultless or cover all possible conditions. These limitations of your research appear probably due to constraints on methodology or research design and influence the interpretation of your research’s ultimate findings. 2 These are limitations on the generalization and usability of findings that emerge from the design of the research and/or the method employed to ensure validity internally and externally. But such limitations of the study can impact the whole study or research paper. However, most researchers prefer not to discuss the different types of limitations in research for fear of decreasing the value of their paper amongst the reviewers or readers.

Importance of limitations of a study

Writing the limitations of the research papers is often assumed to require lots of effort. However, identifying the limitations of the study can help structure the research better. Therefore, do not underestimate the importance of research study limitations. 3

• Opportunity to make suggestions for further research. Suggestions for future research and avenues for further exploration can be developed based on the limitations of the study.
• Opportunity to demonstrate critical thinking. A key objective of the research process is to discover new knowledge while questioning existing assumptions and exploring what is new in the particular field. Describing the limitation of the research shows that you have critically thought about the research problem, reviewed relevant literature, and correctly assessed the methods chosen for studying the problem.
• Demonstrate Subjective learning process. Writing limitations of the research helps to critically evaluate the impact of the said limitations, assess the strength of the research, and consider alternative explanations or interpretations. Subjective evaluation contributes to a more complex and comprehensive knowledge of the issue under study.

Why should I include limitations of research in my paper

All studies have limitations to some extent. Including limitations of the study in your paper demonstrates the researchers’ comprehensive and holistic understanding of the research process and topic. The major advantages are the following:

• Understand the study conditions and challenges encountered . It establishes a complete and potentially logical depiction of the research. The boundaries of the study can be established, and realistic expectations for the findings can be set. They can also help to clarify what the study is not intended to address.
• Improve the quality and validity of the research findings. Mentioning limitations of the research creates opportunities for the original author and other researchers to undertake future studies to improve the research outcomes.
• Transparency and accountability. Including limitations of the research helps maintain mutual integrity and promote further progress in similar studies.
• Identify potential bias sources.  Identifying the limitations of the study can help researchers identify potential sources of bias in their research design, data collection, or analysis. This can help to improve the validity and reliability of the findings.

Where do I need to add the limitations of the study in my paper

The limitations of your research can be stated at the beginning of the discussion section, which allows the reader to comprehend the limitations of the study prior to reading the rest of your findings or at the end of the discussion section as an acknowledgment of the need for further research.

Types of limitations in research

There are different types of limitations in research that researchers may encounter. These are listed below:

• Research Design Limitations : Restrictions on your research or available procedures may affect the research outputs. If the research goals and objectives are too broad, explain how they should be narrowed down to enhance the focus of your study. If there was a selection bias in your sample, explain how this may affect the generalizability of your findings. This can help readers understand the limitations of the study in terms of their impact on the overall validity of your research.
• Impact Limitations : Your study might be limited by a strong regional-, national-, or species-based impact or population- or experimental-specific impact. These inherent limitations on impact affect the extendibility and generalizability of the findings.
• Data or statistical limitations : Data or statistical limitations in research are extremely common in experimental (such as medicine, physics, and chemistry) or field-based (such as ecology and qualitative clinical research) studies. Sometimes, it is either extremely difficult to acquire sufficient data or gain access to the data. These limitations of the research might also be the result of your study’s design and might result in an incomplete conclusion to your research.

Limitations of study examples

All possible limitations of the study cannot be included in the discussion section of the research paper or dissertation. It will vary greatly depending on the type and nature of the study. These include types of research limitations that are related to methodology and the research process and that of the researcher as well that you need to describe and discuss how they possibly impacted your results.

Common methodological limitations of the study

Limitations of research due to methodological problems are addressed by identifying the potential problem and suggesting ways in which this should have been addressed. Some potential methodological limitations of the study are as follows. 1

• Sample size: The sample size 4 is dictated by the type of research problem investigated. If the sample size is too small, finding a significant relationship from the data will be difficult, as statistical tests require a large sample size to ensure a representative population distribution and generalize the study findings.
• Lack of available/reliable data: A lack of available/reliable data will limit the scope of your analysis and the size of your sample or present obstacles in finding a trend or meaningful relationship. So, when writing about the limitations of the study, give convincing reasons why you feel data is absent or untrustworthy and highlight the necessity for a future study focused on developing a new data-gathering strategy.
• Lack of prior research studies: Citing prior research studies is required to help understand the research problem being investigated. If there is little or no prior research, an exploratory rather than an explanatory research design will be required. Also, discovering the limitations of the study presents an opportunity to identify gaps in the literature and describe the need for additional study.
• Measure used to collect the data: Sometimes, the data gathered will be insufficient to conduct a thorough analysis of the results. A limitation of the study example, for instance, is identifying in retrospect that a specific question could have helped address a particular issue that emerged during data analysis. You can acknowledge the limitation of the research by stating the need to revise the specific method for gathering data in the future.
• Self-reported data: Self-reported data cannot be independently verified and can contain several potential bias sources, such as selective memory, attribution, and exaggeration. These biases become apparent if they are incongruent with data from other sources.

General limitations of researchers

Limitations related to the researcher can also influence the study outcomes. These should be addressed, and related remedies should be proposed.

• Limited access to data : If your study requires access to people, organizations, data, or documents whose access is denied or limited, the reasons need to be described. An additional explanation stating why this limitation of research did not prevent you from following through on your study is also needed.
• Time constraints : Researchers might also face challenges in meeting research deadlines due to a lack of timely participant availability or funds, among others. The impacts of time constraints must be acknowledged by mentioning the need for a future study addressing this research problem.
• Conflicts due to biased views and personal issues : Differences in culture or personal views can contribute to researcher bias, as they focus only on the results and data that support their main arguments. To avoid this, pay attention to the problem statement and data gathering.

Steps for structuring the limitations section

Limitations are an inherent part of any research study. Issues may vary, ranging from sampling and literature review to methodology and bias. However, there is a structure for identifying these elements, discussing them, and offering insight or alternatives on how the limitations of the study can be mitigated. This enhances the process of the research and helps readers gain a comprehensive understanding of a study’s conditions.

• Identify the research constraints : Identify those limitations having the greatest impact on the quality of the research findings and your ability to effectively answer your research questions and/or hypotheses. These include sample size, selection bias, measurement error, or other issues affecting the validity and reliability of your research.
• Describe their impact on your research : Reflect on the nature of the identified limitations and justify the choices made during the research to identify the impact of the study’s limitations on the research outcomes. Explanations can be offered if needed, but without being defensive or exaggerating them. Provide context for the limitations of your research to understand them in a broader context. Any specific limitations due to real-world considerations need to be pointed out critically rather than justifying them as done by some other author group or groups.
• Mention the opportunity for future investigations : Suggest ways to overcome the limitations of the present study through future research. This can help readers understand how the research fits into the broader context and offer a roadmap for future studies.

Frequently Asked Questions

• Should I mention all the limitations of my study in the research report?

Restrict limitations to what is pertinent to the research question under investigation. The specific limitations you include will depend on the nature of the study, the research question investigated, and the data collected.

• Can the limitations of a study affect its credibility?

Stating the limitations of the research is considered favorable by editors and peer reviewers. Connecting your study’s limitations with future possible research can help increase the focus of unanswered questions in this area. In addition, admitting limitations openly and validating that they do not affect the main findings of the study increases the credibility of your study. However, if you determine that your study is seriously flawed, explain ways to successfully overcome such flaws in a future study. For example, if your study fails to acquire critical data, consider reframing the research question as an exploratory study to lay the groundwork for more complete research in the future.

• How can I mitigate the limitations of my study?

Strategies to minimize limitations of the research should focus on convincing reviewers and readers that the limitations do not affect the conclusions of the study by showing that the methods are appropriate and that the logic is sound. Here are some steps to follow to achieve this:

• Use data that are valid.
• Use methods that are appropriate and sound logic to draw inferences.
• Use adequate statistical methods for drawing inferences from the data that studies with similar limitations have been published before.

Admit limitations openly and, at the same time, show how they do not affect the main conclusions of the study.

• Can the limitations of a study impact its publication chances?

Limitations in your research can arise owing to restrictions in methodology or research design. Although this could impact your chances of publishing your research paper, it is critical to explain your study’s limitations to your intended audience. For example, it can explain how your study constraints may impact the results and views generated from your investigation. It also shows that you have researched the flaws of your study and have a thorough understanding of the subject.

• How can limitations in research be used for future studies?

The limitations of a study give you an opportunity to offer suggestions for further research. Your study’s limitations, including problems experienced during the study and the additional study perspectives developed, are a great opportunity to take on a new challenge and help advance knowledge in a particular field.

References:

• Brutus, S., Aguinis, H., & Wassmer, U. (2013). Self-reported limitations and future directions in scholarly reports: Analysis and recommendations.  Journal of Management ,  39 (1), 48-75.
• Ioannidis, J. P. (2007). Limitations are not properly acknowledged in the scientific literature.  Journal of Clinical Epidemiology ,  60 (4), 324-329.
• Price, J. H., & Murnan, J. (2004). Research limitations and the necessity of reporting them.  American Journal of Health Education ,  35 (2), 66.
• Boddy, C. R. (2016). Sample size for qualitative research.  Qualitative Market Research: An International Journal ,  19 (4), 426-432.

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Limitations of the Study – How to Write & Examples

What are the limitations of a study?

The limitations of a study are the elements of methodology or study design that impact the interpretation of your research results. The limitations essentially detail any flaws or shortcomings in your study. Study limitations can exist due to constraints on research design, methodology, materials, etc., and these factors may impact the findings of your study. However, researchers are often reluctant to discuss the limitations of their study in their papers, feeling that bringing up limitations may undermine its research value in the eyes of readers and reviewers.

In spite of the impact it might have (and perhaps because of it) you should clearly acknowledge any limitations in your research paper in order to show readers—whether journal editors, other researchers, or the general public—that you are aware of these limitations and to explain how they affect the conclusions that can be drawn from the research.

In this article, we provide some guidelines for writing about research limitations, show examples of some frequently seen study limitations, and recommend techniques for presenting this information. And after you have finished drafting and have received manuscript editing for your work, you still might want to follow this up with academic editing before submitting your work to your target journal.

Why do I need to include limitations of research in my paper?

Although limitations address the potential weaknesses of a study, writing about them toward the end of your paper actually strengthens your study by identifying any problems before other researchers or reviewers find them.

Furthermore, pointing out study limitations shows that you’ve considered the impact of research weakness thoroughly and have an in-depth understanding of your research topic. Since all studies face limitations, being honest and detailing these limitations will impress researchers and reviewers more than ignoring them.

Where should I put the limitations of the study in my paper?

Some limitations might be evident to researchers before the start of the study, while others might become clear while you are conducting the research. Whether these limitations are anticipated or not, and whether they are due to research design or to methodology, they should be clearly identified and discussed in the discussion section —the final section of your paper. Most journals now require you to include a discussion of potential limitations of your work, and many journals now ask you to place this “limitations section” at the very end of your article. 

Some journals ask you to also discuss the strengths of your work in this section, and some allow you to freely choose where to include that information in your discussion section—make sure to always check the author instructions of your target journal before you finalize a manuscript and submit it for peer review .

Limitations of the Study Examples

There are several reasons why limitations of research might exist. The two main categories of limitations are those that result from the methodology and those that result from issues with the researcher(s).

Common Methodological Limitations of Studies

Limitations of research due to methodological problems can be addressed by clearly and directly identifying the potential problem and suggesting ways in which this could have been addressed—and SHOULD be addressed in future studies. The following are some major potential methodological issues that can impact the conclusions researchers can draw from the research.

Issues with research samples and selection

Sampling errors occur when a probability sampling method is used to select a sample, but that sample does not reflect the general population or appropriate population concerned. This results in limitations of your study known as “sample bias” or “selection bias.”

For example, if you conducted a survey to obtain your research results, your samples (participants) were asked to respond to the survey questions. However, you might have had limited ability to gain access to the appropriate type or geographic scope of participants. In this case, the people who responded to your survey questions may not truly be a random sample.

Insufficient sample size for statistical measurements

When conducting a study, it is important to have a sufficient sample size in order to draw valid conclusions. The larger the sample, the more precise your results will be. If your sample size is too small, it will be difficult to identify significant relationships in the data.

Normally, statistical tests require a larger sample size to ensure that the sample is considered representative of a population and that the statistical result can be generalized to a larger population. It is a good idea to understand how to choose an appropriate sample size before you conduct your research by using scientific calculation tools—in fact, many journals now require such estimation to be included in every manuscript that is sent out for review.

Lack of previous research studies on the topic

Citing and referencing prior research studies constitutes the basis of the literature review for your thesis or study, and these prior studies provide the theoretical foundations for the research question you are investigating. However, depending on the scope of your research topic, prior research studies that are relevant to your thesis might be limited.

When there is very little or no prior research on a specific topic, you may need to develop an entirely new research typology. In this case, discovering a limitation can be considered an important opportunity to identify literature gaps and to present the need for further development in the area of study.

Methods/instruments/techniques used to collect the data

After you complete your analysis of the research findings (in the discussion section), you might realize that the manner in which you have collected the data or the ways in which you have measured variables has limited your ability to conduct a thorough analysis of the results.

For example, you might realize that you should have addressed your survey questions from another viable perspective, or that you were not able to include an important question in the survey. In these cases, you should acknowledge the deficiency or deficiencies by stating a need for future researchers to revise their specific methods for collecting data that includes these missing elements.

Common Limitations of the Researcher(s)

Study limitations that arise from situations relating to the researcher or researchers (whether the direct fault of the individuals or not) should also be addressed and dealt with, and remedies to decrease these limitations—both hypothetically in your study, and practically in future studies—should be proposed.

Limited access to data

If your research involved surveying certain people or organizations, you might have faced the problem of having limited access to these respondents. Due to this limited access, you might need to redesign or restructure your research in a different way. In this case, explain the reasons for limited access and be sure that your finding is still reliable and valid despite this limitation.

Time constraints

Just as students have deadlines to turn in their class papers, academic researchers might also have to meet deadlines for submitting a manuscript to a journal or face other time constraints related to their research (e.g., participants are only available during a certain period; funding runs out; collaborators move to a new institution). The time available to study a research problem and to measure change over time might be constrained by such practical issues. If time constraints negatively impacted your study in any way, acknowledge this impact by mentioning a need for a future study (e.g., a longitudinal study) to answer this research problem.

Conflicts arising from cultural bias and other personal issues

Researchers might hold biased views due to their cultural backgrounds or perspectives of certain phenomena, and this can affect a study’s legitimacy. Also, it is possible that researchers will have biases toward data and results that only support their hypotheses or arguments. In order to avoid these problems, the author(s) of a study should examine whether the way the research problem was stated and the data-gathering process was carried out appropriately.

Steps for Organizing Your Study Limitations Section

When you discuss the limitations of your study, don’t simply list and describe your limitations—explain how these limitations have influenced your research findings. There might be multiple limitations in your study, but you only need to point out and explain those that directly relate to and impact how you address your research questions.

We suggest that you divide your limitations section into three steps: (1) identify the study limitations; (2) explain how they impact your study in detail; and (3) propose a direction for future studies and present alternatives. By following this sequence when discussing your study’s limitations, you will be able to clearly demonstrate your study’s weakness without undermining the quality and integrity of your research.

Step 1. Identify the limitation(s) of the study

• This part should comprise around 10%-20% of your discussion of study limitations.

The first step is to identify the particular limitation(s) that affected your study. There are many possible limitations of research that can affect your study, but you don’t need to write a long review of all possible study limitations. A 200-500 word critique is an appropriate length for a research limitations section. In the beginning of this section, identify what limitations your study has faced and how important these limitations are.

You only need to identify limitations that had the greatest potential impact on: (1) the quality of your findings, and (2) your ability to answer your research question.

Step 2. Explain these study limitations in detail

• This part should comprise around 60-70% of your discussion of limitations.

After identifying your research limitations, it’s time to explain the nature of the limitations and how they potentially impacted your study. For example, when you conduct quantitative research, a lack of probability sampling is an important issue that you should mention. On the other hand, when you conduct qualitative research, the inability to generalize the research findings could be an issue that deserves mention.

Explain the role these limitations played on the results and implications of the research and justify the choice you made in using this “limiting” methodology or other action in your research. Also, make sure that these limitations didn’t undermine the quality of your dissertation .

Step 3. Propose a direction for future studies and present alternatives (optional)

• This part should comprise around 10-20% of your discussion of limitations.

After acknowledging the limitations of the research, you need to discuss some possible ways to overcome these limitations in future studies. One way to do this is to present alternative methodologies and ways to avoid issues with, or “fill in the gaps of” the limitations of this study you have presented.  Discuss both the pros and cons of these alternatives and clearly explain why researchers should choose these approaches.

Make sure you are current on approaches used by prior studies and the impacts they have had on their findings. Cite review articles or scientific bodies that have recommended these approaches and why. This might be evidence in support of the approach you chose, or it might be the reason you consider your choices to be included as limitations. This process can act as a justification for your approach and a defense of your decision to take it while acknowledging the feasibility of other approaches.

P hrases and Tips for Introducing Your Study Limitations in the Discussion Section

The following phrases are frequently used to introduce the limitations of the study:

• “There may be some possible limitations in this study.”
• “The findings of this study have to be seen in light of some limitations.”
•  “The first is the…The second limitation concerns the…”
•  “The empirical results reported herein should be considered in the light of some limitations.”
• “This research, however, is subject to several limitations.”
• “The primary limitation to the generalization of these results is…”
• “Nonetheless, these results must be interpreted with caution and a number of limitations should be borne in mind.”
• “As with the majority of studies, the design of the current study is subject to limitations.”
• “There are two major limitations in this study that could be addressed in future research. First, the study focused on …. Second ….”

For more articles on research writing and the journal submissions and publication process, visit Wordvice’s Academic Resources page.

And be sure to receive professional English editing and proofreading services , including paper editing services , for your journal manuscript before submitting it to journal editors.

Wordvice Resources

Proofreading & Editing Guide

Writing the Results Section for a Research Paper

How to Write a Literature Review

Research Writing Tips: How to Draft a Powerful Discussion Section

How to Captivate Journal Readers with a Strong Introduction

Tips That Will Make Your Abstract a Success!

APA In-Text Citation Guide for Research Writing

Additional Resources

• Diving Deeper into Limitations and Delimitations (PhD student)
• Organizing Your Social Sciences Research Paper: Limitations of the Study (USC Library)
• Research Limitations (Research Methodology)
• How to Present Limitations and Alternatives (UMASS)

Article References

Pearson-Stuttard, J., Kypridemos, C., Collins, B., Mozaffarian, D., Huang, Y., Bandosz, P.,…Micha, R. (2018). Estimating the health and economic effects of the proposed US Food and Drug Administration voluntary sodium reformulation: Microsimulation cost-effectiveness analysis. PLOS. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002551

Xu, W.L, Pedersen, N.L., Keller, L., Kalpouzos, G., Wang, H.X., Graff, C,. Fratiglioni, L. (2015). HHEX_23 AA Genotype Exacerbates Effect of Diabetes on Dementia and Alzheimer Disease: A Population-Based Longitudinal Study. PLOS. Retrieved from https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001853

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• Writing Tips

How to Identify Limitations in Research

4-minute read

• 7th March 2022

Whether you’re a veteran researcher with years of experience under your belt or a novice to the field that’s feeling overwhelmed with where to start, you must understand that every study has its limitations. These are restrictions that arise from the study’s design, or the methodology implemented during the testing phase. Unfortunately, research limitations will always exist due to the subjective nature of testing a hypothesis. We’ve compiled some helpful information below on how to identify and accept research limitations and use them to your advantage. Essentially, we’ll show you how to make lemonade (a brilliant piece of academic work ) from the lemons you receive (the constraints your study reveals).

Research Limitations

So, let’s dive straight in, shall we? It’s always beneficial (and good practice) to disclose your research limitations . A common thought is that divulging these shortcomings will undermine the credibility and quality of your research. However, this is certainly not the case— stating the facts upfront not only reinforces your reputation as a researcher but also lets the assessor or reader know that you’re confident and transparent about the results and relevance of your study, despite these constraints.

Additionally, it creates a gap for more research opportunities, where you can analyze these limitations and determine how to incorporate or address them in a new batch of tests or create a new hypothesis altogether. Another bonus is that it helps readers to understand the optimum conditions for how to apply the results of your testing. This is a win-win, making for a far more persuasive research paper .

Now that you know why you should clarify your research limitations, let’s focus on which ones take precedence and should be disclosed. Any given research project can be vulnerable to various hindrances, so how do you identify them and single out the most significant ones to discuss? Well, that depends entirely on the nature of your study. You’ll need to comb through your research approach, methodology, testing processes, and expected results to identify the type of limitations your study may be exposed to. It’s worth noting that this understanding can only offer a broad idea of the possible restrictions you’ll face and may potentially change throughout the study.

We’ve compiled a list of the most common types of research limitations that you may encounter so you can adequately prepare for them and remain vigilant during each stage of your study.

Sample Size:

It’s critical that you choose a sample size that accurately represents the population you wish to test your theory on. If a sample is too small, the results cannot reliably be generalized across a large population.

Methodology:

The method you choose before you commence testing might seem effective in theory, but too many stumbling blocks during the testing phase can influence the accuracy and reliability of the results.

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Collection of Data:

The methods you utilize to obtain your research—surveys, emails, in-person interviews, phone calls—will directly influence the type of results your study yields.

Age of Data:

The nature of the information—and how far back it goes—affects the type of assumptions you can make. Extrapolating older data for a current hypothesis can significantly change the outcome of your testing.

Time Constraints:

Working within the deadline of when you need to submit your findings will determine the extent of your research and testing and, therefore, can heavily impact your results. Limited time frames for testing might mean not achieving the scope of results you were originally looking for.

Limited Budget:

Your study may require equipment and other resources that can become extremely costly. Budget constraints may mean you cannot acquire advanced software, programs, or travel to multiple destinations to interview participants. All of these factors can substantially influence your results.

So, now that you know how to determine your research limitations and the types you might experience, where should you document it? It’s commonly disclosed at the beginning of your discussion section , so the reader understands the shortcomings of your study before digging into the juicy bit—your findings. Alternatively, you can detail the constraints faced at the end of the discussion section to emphasize the requirements for the completion of further studies.

We hope this post will prepare you for some of the pitfalls you may encounter when conducting and documenting your research. Once you have a first draft ready, consider submitting a free sample to us for proofreading to ensure that your writing is concise and error-free and your results—despite their limitations— shine through.

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Research Limitations & Delimitations

What they are and how they’re different (with examples)

By: Derek Jansen (MBA) | Expert Reviewed By: David Phair (PhD) | September 2022

If you’re new to the world of research, you’ve probably heard the terms “ research limitations ” and “ research delimitations ” being thrown around, often quite loosely. In this post, we’ll unpack what both of these mean, how they’re similar and how they’re different – so that you can write up these sections the right way.

Overview: Limitations vs Delimitations

• Are they the same?
• What are research limitations
• What are research delimitations
• Limitations vs delimitations

First things first…

Let’s start with the most important takeaway point of this post – research limitations and research delimitations are not the same – but they are related to each other (we’ll unpack that a little later). So, if you hear someone using these two words interchangeably, be sure to share this post with them!

Research Limitations

Research limitations are, at the simplest level, the weaknesses of the study , based on factors that are often outside of your control as the researcher. These factors could include things like time , access to funding, equipment , data or participants . For example, if you weren’t able to access a random sample of participants for your study and had to adopt a convenience sampling strategy instead, that would impact the generalizability of your findings and therefore reflect a limitation of your study.

Research limitations can also emerge from the research design itself . For example, if you were undertaking a correlational study, you wouldn’t be able to infer causality (since correlation doesn’t mean certain causation). Similarly, if you utilised online surveys to collect data from your participants, you naturally wouldn’t be able to get the same degree of rich data that you would from in-person interviews .

Simply put, research limitations reflect the shortcomings of a study , based on practical (or theoretical) constraints that the researcher faced. These shortcomings limit what you can conclude from a study, but at the same time, present a foundation for future research . Importantly, all research has limitations , so there’s no need to hide anything here – as long as you discuss how the limitations might affect your findings, it’s all good.

Research Delimitations

Alright, now that we’ve unpacked the limitations, let’s move on to the delimitations .

Research delimitations are similar to limitations in that they also “ limit ” the study, but their focus is entirely different. Specifically, the delimitations of a study refer to the scope of the research aims and research questions . In other words, delimitations reflect the choices you, as the researcher, intentionally make in terms of what you will and won’t try to achieve with your study. In other words, what your research aims and research questions will and won’t include.

As we’ve spoken about many times before, it’s important to have a tight, narrow focus for your research, so that you can dive deeply into your topic, apply your energy to one specific area and develop meaningful insights. If you have an overly broad scope or unfocused topic, your research will often pull in multiple, even opposing directions, and you’ll just land up with a muddy mess of findings .

So, the delimitations section is where you’ll clearly state what your research aims and research questions will focus on – and just as importantly, what they will exclude . For example, you might investigate a widespread phenomenon, but choose to focus your study on a specific age group, ethnicity or gender. Similarly, your study may focus exclusively on one country, city or even organization. As long as the scope is well justified (in other words, it represents a novel, valuable research topic), this is perfectly acceptable – in fact, it’s essential. Remember, focus is your friend.

Need a helping hand?

Conclusion: Limitations vs Delimitations

Ok, so let’s recap.

Research limitations and research delimitations are related in that they both refer to “limits” within a study. But, they are distinctly different. Limitations reflect the shortcomings of your study, based on practical or theoretical constraints that you faced.

Contrasted to that, delimitations reflect the choices that you made in terms of the focus and scope of your research aims and research questions. If you want to learn more about research aims and questions, you can check out this video post , where we unpack those concepts in detail.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

18 Comments

Good clarification of ideas on how a researcher ought to do during Process of choice

Thank you so much for this very simple but explicit explanation on limitation and delimitation. It has so helped me to develop my masters proposal. hope to recieve more from your site as time progresses

Thank you for this explanation – very clear.

Thanks for the explanation, really got it well.

This website is really helpful for my masters proposal

Thank you very much for helping to explain these two terms

I spent almost the whole day trying to figure out the differences

when I came across your notes everything became very clear

thanks for the clearly outlined explanation on the two terms, limitation and delimitation.

Very helpful Many thanks 🙏

Excellent it resolved my conflict .

I would like you to assist me please. If in my Research, I interviewed some participants and I submitted Questionnaires to other participants to answered to the questions, in the same organization, Is this a Qualitative methodology , a Quantitative Methodology or is it a Mixture Methodology I have used in my research? Please help me

How do I cite this article in APA format

Really so great ,finally have understood it’s difference now

Getting more clear regarding Limitations and Delimitation and concepts

I really appreciate your apt and precise explanation of the two concepts namely ; Limitations and Delimitations.

This is a good sources of research information for learners.

thank you for this, very helpful to researchers

Very good explained

Great and clear explanation, after a long confusion period on the two words, i can now explain to someone with ease.

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Organizing Academic Research Papers: Limitations of the Study

• Purpose of Guide
• Design Flaws to Avoid
• Glossary of Research Terms
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Executive Summary
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tertiary Sources
• What Is Scholarly vs. Popular?
• Qualitative Methods
• Quantitative Methods
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Annotated Bibliography
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• How to Manage Group Projects
• Multiple Book Review Essay
• Reviewing Collected Essays
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Research Proposal
• Acknowledgements

The limitations of the study are those characteristics of design or methodology that impacted or influenced the application or interpretation of the results of your study. They are the constraints on generalizability and utility of findings that are the result of the ways in which you chose to design the study and/or the method used to establish internal and external validity.

Importance of...

Always acknowledge a study's limitations. It is far better for you to identify and acknowledge your study’s limitations than to have them pointed out by your professor and be graded down because you appear to have ignored them.

Keep in mind that acknowledgement of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgement of a study's limitations also provides you with an opportunity to demonstrate to your professor that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but also to confront assumptions and explore what we don't know.

Claiming limitiations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the findings and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in your paper.

Here are examples of limitations you may need to describe and to discuss how they possibly impacted your findings. Descriptions of limitations should be stated in the past tense.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but to offer reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe the need for future research.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, consult with a librarian! In cases when a librarian has confirmed that there is a lack of prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design]. Note that this limitation can serve as an important opportunity to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need in future research to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing self-reported data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to take what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data contain several potential sources of bias that should be noted as limitations: (1) selective memory (remembering or not remembering experiences or events that occurred at some point in the past); (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, or documents and, for whatever reason, access is denied or otherwise limited, the reasons for this need to be described.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single research problem, the time available to investigate a research problem and to measure change or stability within a sample is constrained by the due date of your assignment. Be sure to choose a topic that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, or thing is viewed or shown in a consistently inaccurate way. It is usually negative, though one can have a positive bias as well. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places and how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation. Note that if you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating bias.
• Fluency in a language -- if your research focuses on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students, for example, and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic. This deficiency should be acknowledged.

Brutus, Stéphane et al. Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations. Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods . Powerpoint Presentation. Regent University of Science and Technology.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as a pilot study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in later studies.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study  is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to reframe your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to  the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't ask a particular question in a survey that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in any future study. A underlying goal of scholarly research is not only to prove what works, but to demonstrate what doesn't work or what needs further clarification.

Brutus, Stéphane et al. Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations. Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. Limitations are not Properly Acknowledged in the Scientific Literature. Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed . January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Writing Tip

Don't Inflate the Importance of Your Findings! After all the hard work and long hours devoted to writing your research paper, it is easy to get carried away with attributing unwarranted importance to what you’ve done. We all want our academic work to be viewed as excellent and worthy of a good grade, but it is important that you understand and openly acknowledge the limitiations of your study. Inflating of the importance of your study's findings in an attempt hide its flaws is a big turn off to your readers. A measure of humility goes a long way!

Another Writing Tip

Negative Results are Not a Limitation!

Negative evidence refers to findings that unexpectedly challenge rather than support your hypothesis. If you didn't get the results you anticipated, it may mean your hypothesis was incorrect and needs to be reformulated, or, perhaps you have stumbled onto something unexpected that warrants further study. Moreover, the absence of an effect may be very telling in many situations, particularly in experimental research designs. In any case, your results may be of importance to others even though they did not support your hypothesis. Do not fall into the trap of thinking that results contrary to what you expected is a limitation to your study. If you carried out the research well, they are simply your results and only require additional interpretation.

Yet Another Writing Tip

A Note about Sample Size Limitations in Qualitative Research

Sample sizes are typically smaller in qualitative research because, as the study goes on, acquiring more data does not necessarily lead to more information. This is because one occurrence of a piece of data, or a code, is all that is necessary to ensure that it becomes part of the analysis framework. However, it remains true that sample sizes that are too small cannot adequately support claims of having achieved valid conclusions and sample sizes that are too large do not permit the deep, naturalistic, and inductive analysis that defines qualitative inquiry. Determining adequate sample size in qualitative research is ultimately a matter of judgment and experience in evaluating the quality of the information collected against the uses to which it will be applied and the particular research method and purposeful sampling strategy employed. If the sample size is found to be a limitation, it may reflect your judgement about the methodological technique chosen [e.g., single life history study versus focus group interviews] rather than the number of respondents used.

Huberman, A. Michael and Matthew B. Miles. Data Management and Analysis Methods. In Handbook of Qualitative Research. Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 428-444.

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CPS Online Graduate Studies Research Paper (UNH Manchester Library): Limitations of the Study

• Overview of the Research Process for Capstone Projects
• Types of Research Design
• Selecting a Research Problem
• The Title of Your Research Paper
• Before You Begin Writing
• 7 Parts of the Research Paper
• Background Information
• Quanitative and Qualitative Methods
• Qualitative Methods
• Quanitative Methods
• Resources to Help You With the Literature Review
• Non-Textual Elements

Limitations of the Study

• Format of Capstone Research Projects at GSC
• Editing and Proofreading Your Paper
• Acknowledgements
• UNH Scholar's Repository

The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research. They are the constraints on generalizability, applications to practice, and/or utility of findings that are the result of the ways in which you initially chose to design the study and/or the method used to establish internal and external validity.

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67.

Always acknowledge a study's limitations. It is far better that you identify and acknowledge your study’s limitations than to have them pointed out by your professor and be graded down because you appear to have ignored them.

Keep in mind that acknowledgement of a study's limitations is an opportunity to make suggestions for further research. If you do connect your study's limitations to suggestions for further research, be sure to explain the ways in which these unanswered questions may become more focused because of your study.

Acknowledgement of a study's limitations also provides you with an opportunity to demonstrate that you have thought critically about the research problem, understood the relevant literature published about it, and correctly assessed the methods chosen for studying the problem. A key objective of the research process is not only discovering new knowledge but to also confront assumptions and explore what we don't know.

Claiming limitations is a subjective process because you must evaluate the impact of those limitations . Don't just list key weaknesses and the magnitude of a study's limitations. To do so diminishes the validity of your research because it leaves the reader wondering whether, or in what ways, limitation(s) in your study may have impacted the results and conclusions. Limitations require a critical, overall appraisal and interpretation of their impact. You should answer the question: do these problems with errors, methods, validity, etc. eventually matter and, if so, to what extent?

Price, James H. and Judy Murnan. “Research Limitations and the Necessity of Reporting Them.” American Journal of Health Education 35 (2004): 66-67; Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com.

Descriptions of Possible Limitations

All studies have limitations . However, it is important that you restrict your discussion to limitations related to the research problem under investigation. For example, if a meta-analysis of existing literature is not a stated purpose of your research, it should not be discussed as a limitation. Do not apologize for not addressing issues that you did not promise to investigate in the introduction of your paper.

Here are examples of limitations related to methodology and the research process you may need to describe and to discuss how they possibly impacted your results. Descriptions of limitations should be stated in the past tense because they were discovered after you completed your research.

Possible Methodological Limitations

• Sample size -- the number of the units of analysis you use in your study is dictated by the type of research problem you are investigating. Note that, if your sample size is too small, it will be difficult to find significant relationships from the data, as statistical tests normally require a larger sample size to ensure a representative distribution of the population and to be considered representative of groups of people to whom results will be generalized or transferred. Note that sample size is less relevant in qualitative research.
• Lack of available and/or reliable data -- a lack of data or of reliable data will likely require you to limit the scope of your analysis, the size of your sample, or it can be a significant obstacle in finding a trend and a meaningful relationship. You need to not only describe these limitations but to offer reasons why you believe data is missing or is unreliable. However, don’t just throw up your hands in frustration; use this as an opportunity to describe the need for future research.
• Lack of prior research studies on the topic -- citing prior research studies forms the basis of your literature review and helps lay a foundation for understanding the research problem you are investigating. Depending on the currency or scope of your research topic, there may be little, if any, prior research on your topic. Before assuming this to be true, though, consult with a librarian. In cases when a librarian has confirmed that there is no prior research, you may be required to develop an entirely new research typology [for example, using an exploratory rather than an explanatory research design]. Note again that discovering a limitation can serve as an important opportunity to identify new gaps in the literature and to describe the need for further research.
• Measure used to collect the data -- sometimes it is the case that, after completing your interpretation of the findings, you discover that the way in which you gathered data inhibited your ability to conduct a thorough analysis of the results. For example, you regret not including a specific question in a survey that, in retrospect, could have helped address a particular issue that emerged later in the study. Acknowledge the deficiency by stating a need for future researchers to revise the specific method for gathering data.
• Self-reported data -- whether you are relying on pre-existing data or you are conducting a qualitative research study and gathering the data yourself, self-reported data is limited by the fact that it rarely can be independently verified. In other words, you have to take what people say, whether in interviews, focus groups, or on questionnaires, at face value. However, self-reported data can contain several potential sources of bias that you should be alert to and note as limitations. These biases become apparent if they are incongruent with data from other sources. These are: (1) selective memory [remembering or not remembering experiences or events that occurred at some point in the past]; (2) telescoping [recalling events that occurred at one time as if they occurred at another time]; (3) attribution [the act of attributing positive events and outcomes to one's own agency but attributing negative events and outcomes to external forces]; and, (4) exaggeration [the act of representing outcomes or embellishing events as more significant than is actually suggested from other data].

Possible Limitations of the Researcher

• Access -- if your study depends on having access to people, organizations, or documents and, for whatever reason, access is denied or limited in some way, the reasons for this need to be described.
• Longitudinal effects -- unlike your professor, who can literally devote years [even a lifetime] to studying a single topic, the time available to investigate a research problem and to measure change or stability over time is pretty much constrained by the due date of your assignment. Be sure to choose a research problem that does not require an excessive amount of time to complete the literature review, apply the methodology, and gather and interpret the results. If you're unsure whether you can complete your research within the confines of the assignment's due date, talk to your professor.
• Cultural and other type of bias -- we all have biases, whether we are conscience of them or not. Bias is when a person, place, or thing is viewed or shown in a consistently inaccurate way. Bias is usually negative, though one can have a positive bias as well, especially if that bias reflects your reliance on research that only support for your hypothesis. When proof-reading your paper, be especially critical in reviewing how you have stated a problem, selected the data to be studied, what may have been omitted, the manner in which you have ordered events, people, or places, how you have chosen to represent a person, place, or thing, to name a phenomenon, or to use possible words with a positive or negative connotation.

NOTE:   If you detect bias in prior research, it must be acknowledged and you should explain what measures were taken to avoid perpetuating that bias.

• Fluency in a language -- if your research focuses on measuring the perceived value of after-school tutoring among Mexican-American ESL [English as a Second Language] students, for example, and you are not fluent in Spanish, you are limited in being able to read and interpret Spanish language research studies on the topic. This deficiency should be acknowledged.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Senunyeme, Emmanuel K. Business Research Methods . Powerpoint Presentation. Regent University of Science and Technology; ter Riet, Gerben et al. “All That Glitters Isn't Gold: A Survey on Acknowledgment of Limitations in Biomedical Studies.” PLOS One 8 (November 2013): 1-6.

Structure and Writing Style

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section. If you determine that your study is seriously flawed due to important limitations, such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study. But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic. If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study. When discussing the limitations of your research, be sure to: Describe each limitation in detailed but concise terms; Explain why each limitation exists; Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible]; Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and, If appropriate, describe how these limitations could point to the need for further research. Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification. Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed. January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation. Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University.

Information about the limitations of your study are generally placed either at the beginning of the discussion section of your paper so the reader knows and understands the limitations before reading the rest of your analysis of the findings, or, the limitations are outlined at the conclusion of the discussion section as an acknowledgement of the need for further study. Statements about a study's limitations should not be buried in the body [middle] of the discussion section unless a limitation is specific to something covered in that part of the paper. If this is the case, though, the limitation should be reiterated at the conclusion of the section.

If you determine that your study is seriously flawed due to important limitations , such as, an inability to acquire critical data, consider reframing it as an exploratory study intended to lay the groundwork for a more complete research study in the future. Be sure, though, to specifically explain the ways that these flaws can be successfully overcome in a new study.

But, do not use this as an excuse for not developing a thorough research paper! Review the tab in this guide for developing a research topic . If serious limitations exist, it generally indicates a likelihood that your research problem is too narrowly defined or that the issue or event under study is too recent and, thus, very little research has been written about it. If serious limitations do emerge, consult with your professor about possible ways to overcome them or how to revise your study.

When discussing the limitations of your research, be sure to:

• Describe each limitation in detailed but concise terms;
• Explain why each limitation exists;
• Provide the reasons why each limitation could not be overcome using the method(s) chosen to acquire or gather the data [cite to other studies that had similar problems when possible];
• Assess the impact of each limitation in relation to the overall findings and conclusions of your study; and,
• If appropriate, describe how these limitations could point to the need for further research.

Remember that the method you chose may be the source of a significant limitation that has emerged during your interpretation of the results [for example, you didn't interview a group of people that you later wish you had]. If this is the case, don't panic. Acknowledge it, and explain how applying a different or more robust methodology might address the research problem more effectively in a future study. A underlying goal of scholarly research is not only to show what works, but to demonstrate what doesn't work or what needs further clarification.

Aguinis, Hermam and Jeffrey R. Edwards. “Methodological Wishes for the Next Decade and How to Make Wishes Come True.” Journal of Management Studies 51 (January 2014): 143-174; Brutus, Stéphane et al. "Self-Reported Limitations and Future Directions in Scholarly Reports: Analysis and Recommendations." Journal of Management 39 (January 2013): 48-75; Ioannidis, John P.A. "Limitations are not Properly Acknowledged in the Scientific Literature." Journal of Clinical Epidemiology 60 (2007): 324-329; Pasek, Josh. Writing the Empirical Social Science Research Paper: A Guide for the Perplexed . January 24, 2012. Academia.edu; Structure: How to Structure the Research Limitations Section of Your Dissertation . Dissertations and Theses: An Online Textbook. Laerd.com; What Is an Academic Paper? Institute for Writing Rhetoric. Dartmouth College; Writing the Experimental Report: Methods, Results, and Discussion . The Writing Lab and The OWL. Purdue University.

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• GETTING STARTED
• Introduction
• FUNDAMENTALS
• Acknowledgements
• Research questions & hypotheses
• Concepts, constructs & variables
• Research limitations
• Getting started
• Sampling Strategy
• Research Quality
• Research Ethics
• Data Analysis

How to structure the Research Limitations section of your dissertation

There is no "one best way" to structure the Research Limitations section of your dissertation. However, we recommend a structure based on three moves : the announcing , reflecting and forward looking move. The announcing move immediately allows you to identify the limitations of your dissertation and explain how important each of these limitations is. The reflecting move provides greater depth, helping to explain the nature of the limitations and justify the choices that you made during the research process. Finally, the forward looking move enables you to suggest how such limitations could be overcome in future. The collective aim of these three moves is to help you walk the reader through your Research Limitations section in a succinct and structured way. This will make it clear to the reader that you recognise the limitations of your own research, that you understand why such factors are limitations, and can point to ways of combating these limitations if future research was carried out. This article explains what should be included in each of these three moves :

• THE ANNOUNCING MOVE: Identifying limitations and explaining how important they are
• THE REFLECTING MOVE: Explaining the nature of the limitations and justifying the choices you made
• THE FORWARD LOOKING MOVE: Suggesting how such limitations could be overcome in future

THE ANNOUNCING MOVE Identifying limitations, and explaining how important they are

There are many possible limitations that your research may have faced. However, is not necessary for you to discuss all of these limitations in your Research Limitations section. After all, you are not writing a 2000 word critical review of the limitations of your dissertation, just a 200-500 word critique that is only one section long (i.e., the Research Limitations section within your Conclusions chapter). Therefore, in this first announcing move , we would recommend that you identify only those limitations that had the greatest potential impact on: (a) the quality of your findings; and (b) your ability to effectively answer your research questions and/or hypotheses.

We use the word potential impact because we often do not know the degree to which different factors limited our findings or our ability to effectively answer our research questions and/or hypotheses. For example, we know that when adopting a quantitative research design, a failure to use a probability sampling technique significantly limits our ability to make broader generalisations from our results (i.e., our ability to make statistical inferences from our sample to the population being studied). However, the degree to which this reduces the quality of our findings is a matter of debate. Also, whilst the lack of a probability sampling technique when using a quantitative research design is a very obvious example of a research limitation, other limitations are far less clear. Therefore, the key point is to focus on those limitations that you feel had the greatest impact on your findings, as well as your ability to effectively answer your research questions and/or hypotheses.

Overall, the announcing move should be around 10-20% of the total word count of the Research Limitations section.

THE REFLECTING MOVE Explaining the nature of the limitations and justifying the choices you made

Having identified the most important limitations to your dissertation in the announcing move , the reflecting move focuses on explaining the nature of these limitations and justifying the choices that you made during the research process. This part should be around 60-70% of the total word count of the Research Limitations section.

It is important to remember at this stage that all research suffers from limitations, whether it is performed by undergraduate and master's level dissertation students, or seasoned academics. Acknowledging such limitations should not be viewed as a weakness, highlighting to the person marking your work the reasons why you should receive a lower grade. Instead, the reader is more likely to accept that you recognise the limitations of your own research if you write a high quality reflecting move . This is because explaining the limitations of your research and justifying the choices you made during the dissertation process demonstrates the command that you had over your research.

We talk about explaining the nature of the limitations in your dissertation because such limitations are highly research specific. Let's take the example of potential limitations to your sampling strategy. Whilst you may have a number of potential limitations in sampling strategy, let's focus on the lack of probability sampling ; that is, of all the different types of sampling technique that you could have used [see Types of probability sampling and Types of non-probability sampling ], you choose not to use a probability sampling technique (e.g., simple random sampling , systematic random sampling , stratified random sampling ). As mentioned, if you used a quantitative research design in your dissertation, the lack of probability sampling is an important, obvious limitation to your research. This is because it prevents you from making generalisations about the population you are studying (e.g. Facebook usage at a single university of 20,000 students) from the data you have collected (e.g., a survey of 400 students at the same university). Since an important component of quantitative research is such generalisation, this is a clear limitation. However, the lack of a probability sampling technique is not viewed as a limitation if you used a qualitative research design. In qualitative research designs, a non-probability sampling technique is typically selected over a probability sampling technique.

And this is just part of the puzzle?

Even if you used a quantitative research design, but failed to employ a probability sampling technique, there are still many perfectly justifiable reasons why you could have made such a choice. For example, it may have been impossible (or near on impossible) to get a list of the population you were studying (e.g., a list of all the 20,000 students at the single university you were interested in). Since probability sampling is only possible when we have such a list, the lack of such a list or inability to attain such a list is a perfectly justifiable reason for not using a probability sampling technique; even if such a technique is the ideal.

As such, the purpose of all the guides we have written on research limitations is to help you: (a) explain the nature of the limitations in your dissertation; and (b) justify the choices you made.

In helping you to justifying the choices that you made, these articles explain not only when something is, in theory , an obvious limitation, but how, in practice , such a limitation was not necessarily so damaging to the quality of your dissertation. This should significantly strengthen the quality of your Research Limitations section.

THE FORWARD LOOKING MOVE Suggesting how such limitations could be overcome in future

Finally, the forward looking move builds on the reflecting move by suggesting how the limitations you have discuss could be overcome through future research. Whilst a lot could be written in this part of the Research Limitations section, we would recommend that it is only around 10-20% of the total word count for this section.

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Delimitations in Research – Types, Examples and Writing Guide

Table of Contents

Delimitations

Definition:

Delimitations refer to the specific boundaries or limitations that are set in a research study in order to narrow its scope and focus. Delimitations may be related to a variety of factors, including the population being studied, the geographical location, the time period, the research design , and the methods or tools being used to collect data .

The Importance of Delimitations in Research Studies

Here are some reasons why delimitations are important in research studies:

• Provide focus : Delimitations help researchers focus on a specific area of interest and avoid getting sidetracked by tangential topics. By setting clear boundaries, researchers can concentrate their efforts on the most relevant and significant aspects of the research question.
• Increase validity : Delimitations ensure that the research is more valid by defining the boundaries of the study. When researchers establish clear criteria for inclusion and exclusion, they can better control for extraneous variables that might otherwise confound the results.
• Improve generalizability : Delimitations help researchers determine the extent to which their findings can be generalized to other populations or contexts. By specifying the sample size, geographic region, time frame, or other relevant factors, researchers can provide more accurate estimates of the generalizability of their results.
• Enhance feasibility : Delimitations help researchers identify the resources and time required to complete the study. By setting realistic parameters, researchers can ensure that the study is feasible and can be completed within the available time and resources.
• Clarify scope: Delimitations help readers understand the scope of the research project. By explicitly stating what is included and excluded, researchers can avoid confusion and ensure that readers understand the boundaries of the study.

Types of Delimitations in Research

Here are some types of delimitations in research and their significance:

Time Delimitations

This type of delimitation refers to the time frame in which the research will be conducted. Time delimitations are important because they help to narrow down the scope of the study and ensure that the research is feasible within the given time constraints.

Geographical Delimitations

Geographical delimitations refer to the geographic boundaries within which the research will be conducted. These delimitations are significant because they help to ensure that the research is relevant to the intended population or location.

Population Delimitations

Population delimitations refer to the specific group of people that the research will focus on. These delimitations are important because they help to ensure that the research is targeted to a specific group, which can improve the accuracy of the results.

Data Delimitations

Data delimitations refer to the specific types of data that will be used in the research. These delimitations are important because they help to ensure that the data is relevant to the research question and that the research is conducted using reliable and valid data sources.

Scope Delimitations

Scope delimitations refer to the specific aspects or dimensions of the research that will be examined. These delimitations are important because they help to ensure that the research is focused and that the findings are relevant to the research question.

How to Write Delimitations

In order to write delimitations in research, you can follow these steps:

• Identify the scope of your study : Determine the extent of your research by defining its boundaries. This will help you to identify the areas that are within the scope of your research and those that are outside of it.
• Determine the time frame : Decide on the time period that your research will cover. This could be a specific period, such as a year, or it could be a general time frame, such as the last decade.
• I dentify the population : Determine the group of people or objects that your study will focus on. This could be a specific age group, gender, profession, or geographic location.
• Establish the sample size : Determine the number of participants that your study will involve. This will help you to establish the number of people you need to recruit for your study.
• Determine the variables: Identify the variables that will be measured in your study. This could include demographic information, attitudes, behaviors, or other factors.
• Explain the limitations : Clearly state the limitations of your study. This could include limitations related to time, resources, sample size, or other factors that may impact the validity of your research.
• Justify the limitations : Explain why these limitations are necessary for your research. This will help readers understand why certain factors were excluded from the study.

When to Write Delimitations in Research

Here are some situations when you may need to write delimitations in research:

• When defining the scope of the study: Delimitations help to define the boundaries of your research by specifying what is and what is not included in your study. For instance, you may delimit your study by focusing on a specific population, geographic region, time period, or research methodology.
• When addressing limitations: Delimitations can also be used to address the limitations of your research. For example, if your data is limited to a certain timeframe or geographic area, you can include this information in your delimitations to help readers understand the limitations of your findings.
• When justifying the relevance of the study : Delimitations can also help you to justify the relevance of your research. For instance, if you are conducting a study on a specific population or region, you can explain why this group or area is important and how your research will contribute to the understanding of this topic.
• When clarifying the research question or hypothesis : Delimitations can also be used to clarify your research question or hypothesis. By specifying the boundaries of your study, you can ensure that your research question or hypothesis is focused and specific.
• When establishing the context of the study : Finally, delimitations can help you to establish the context of your research. By providing information about the scope and limitations of your study, you can help readers to understand the context in which your research was conducted and the implications of your findings.

Examples of Delimitations in Research

Examples of Delimitations in Research are as follows:

Research Title : “Impact of Artificial Intelligence on Cybersecurity Threat Detection”

Delimitations :

• The study will focus solely on the use of artificial intelligence in detecting and mitigating cybersecurity threats.
• The study will only consider the impact of AI on threat detection and not on other aspects of cybersecurity such as prevention, response, or recovery.
• The research will be limited to a specific type of cybersecurity threats, such as malware or phishing attacks, rather than all types of cyber threats.
• The study will only consider the use of AI in a specific industry, such as finance or healthcare, rather than examining its impact across all industries.
• The research will only consider AI-based threat detection tools that are currently available and widely used, rather than including experimental or theoretical AI models.

Research Title: “The Effects of Social Media on Academic Performance: A Case Study of College Students”

Delimitations:

• The study will focus only on college students enrolled in a particular university.
• The study will only consider social media platforms such as Facebook, Twitter, and Instagram.
• The study will only analyze the academic performance of students based on their GPA and course grades.
• The study will not consider the impact of other factors such as student demographics, socioeconomic status, or other factors that may affect academic performance.
• The study will only use self-reported data from students, rather than objective measures of their social media usage or academic performance.

Purpose of Delimitations

Some Purposes of Delimitations are as follows:

• Focusing the research : By defining the scope of the study, delimitations help researchers to narrow down their research questions and focus on specific aspects of the topic. This allows for a more targeted and meaningful study.
• Clarifying the research scope : Delimitations help to clarify the boundaries of the research, which helps readers to understand what is and is not included in the study.
• Avoiding scope creep : Delimitations help researchers to stay focused on their research objectives and avoid being sidetracked by tangential issues or data.
• Enhancing the validity of the study : By setting clear boundaries, delimitations help to ensure that the study is valid and reliable.
• Improving the feasibility of the study : Delimitations help researchers to ensure that their study is feasible and can be conducted within the time and resources available.

Applications of Delimitations

Here are some common applications of delimitations:

• Geographic delimitations : Researchers may limit their study to a specific geographic area, such as a particular city, state, or country. This helps to narrow the focus of the study and makes it more manageable.
• Time delimitations : Researchers may limit their study to a specific time period, such as a decade, a year, or a specific date range. This can be useful for studying trends over time or for comparing data from different time periods.
• Population delimitations : Researchers may limit their study to a specific population, such as a particular age group, gender, or ethnic group. This can help to ensure that the study is relevant to the population being studied.
• Data delimitations : Researchers may limit their study to specific types of data, such as survey responses, interviews, or archival records. This can help to ensure that the study is based on reliable and relevant data.
• Conceptual delimitations : Researchers may limit their study to specific concepts or variables, such as only studying the effects of a particular treatment on a specific outcome. This can help to ensure that the study is focused and clear.

Advantages of Delimitations

Some Advantages of Delimitations are as follows:

• Helps to focus the study: Delimitations help to narrow down the scope of the research and identify specific areas that need to be investigated. This helps to focus the study and ensures that the research is not too broad or too narrow.
• Defines the study population: Delimitations can help to define the population that will be studied. This can include age range, gender, geographical location, or any other factors that are relevant to the research. This helps to ensure that the study is more specific and targeted.
• Provides clarity: Delimitations help to provide clarity about the research study. By identifying the boundaries and limitations of the research, it helps to avoid confusion and ensures that the research is more understandable.
• Improves validity: Delimitations can help to improve the validity of the research by ensuring that the study is more focused and specific. This can help to ensure that the research is more accurate and reliable.
• Reduces bias: Delimitations can help to reduce bias by limiting the scope of the research. This can help to ensure that the research is more objective and unbiased.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Limited by our limitations

Paula t. ross.

Medical School, University of Michigan, Ann Arbor, MI USA

Nikki L. Bibler Zaidi

Study limitations represent weaknesses within a research design that may influence outcomes and conclusions of the research. Researchers have an obligation to the academic community to present complete and honest limitations of a presented study. Too often, authors use generic descriptions to describe study limitations. Including redundant or irrelevant limitations is an ineffective use of the already limited word count. A meaningful presentation of study limitations should describe the potential limitation, explain the implication of the limitation, provide possible alternative approaches, and describe steps taken to mitigate the limitation. This includes placing research findings within their proper context to ensure readers do not overemphasize or minimize findings. A more complete presentation will enrich the readers’ understanding of the study’s limitations and support future investigation.

Introduction

Regardless of the format scholarship assumes, from qualitative research to clinical trials, all studies have limitations. Limitations represent weaknesses within the study that may influence outcomes and conclusions of the research. The goal of presenting limitations is to provide meaningful information to the reader; however, too often, limitations in medical education articles are overlooked or reduced to simplistic and minimally relevant themes (e.g., single institution study, use of self-reported data, or small sample size) [ 1 ]. This issue is prominent in other fields of inquiry in medicine as well. For example, despite the clinical implications, medical studies often fail to discuss how limitations could have affected the study findings and interpretations [ 2 ]. Further, observational research often fails to remind readers of the fundamental limitation inherent in the study design, which is the inability to attribute causation [ 3 ]. By reporting generic limitations or omitting them altogether, researchers miss opportunities to fully communicate the relevance of their work, illustrate how their work advances a larger field under study, and suggest potential areas for further investigation.

Goals of presenting limitations

Medical education scholarship should provide empirical evidence that deepens our knowledge and understanding of education [ 4 , 5 ], informs educational practice and process, [ 6 , 7 ] and serves as a forum for educating other researchers [ 8 ]. Providing study limitations is indeed an important part of this scholarly process. Without them, research consumers are pressed to fully grasp the potential exclusion areas or other biases that may affect the results and conclusions provided [ 9 ]. Study limitations should leave the reader thinking about opportunities to engage in prospective improvements [ 9 – 11 ] by presenting gaps in the current research and extant literature, thereby cultivating other researchers’ curiosity and interest in expanding the line of scholarly inquiry [ 9 ].

Presenting study limitations is also an ethical element of scientific inquiry [ 12 ]. It ensures transparency of both the research and the researchers [ 10 , 13 , 14 ], as well as provides transferability [ 15 ] and reproducibility of methods. Presenting limitations also supports proper interpretation and validity of the findings [ 16 ]. A study’s limitations should place research findings within their proper context to ensure readers are fully able to discern the credibility of a study’s conclusion, and can generalize findings appropriately [ 16 ].

Why some authors may fail to present limitations

As Price and Murnan [ 8 ] note, there may be overriding reasons why researchers do not sufficiently report the limitations of their study. For example, authors may not fully understand the importance and implications of their study’s limitations or assume that not discussing them may increase the likelihood of publication. Word limits imposed by journals may also prevent authors from providing thorough descriptions of their study’s limitations [ 17 ]. Still another possible reason for excluding limitations is a diffusion of responsibility in which some authors may incorrectly assume that the journal editor is responsible for identifying limitations. Regardless of reason or intent, researchers have an obligation to the academic community to present complete and honest study limitations.

A guide to presenting limitations

The presentation of limitations should describe the potential limitations, explain the implication of the limitations, provide possible alternative approaches, and describe steps taken to mitigate the limitations. Too often, authors only list the potential limitations, without including these other important elements.

Describe the limitations

When describing limitations authors should identify the limitation type to clearly introduce the limitation and specify the origin of the limitation. This helps to ensure readers are able to interpret and generalize findings appropriately. Here we outline various limitation types that can occur at different stages of the research process.

Study design

Some study limitations originate from conscious choices made by the researcher (also known as delimitations) to narrow the scope of the study [ 1 , 8 , 18 ]. For example, the researcher may have designed the study for a particular age group, sex, race, ethnicity, geographically defined region, or some other attribute that would limit to whom the findings can be generalized. Such delimitations involve conscious exclusionary and inclusionary decisions made during the development of the study plan, which may represent a systematic bias intentionally introduced into the study design or instrument by the researcher [ 8 ]. The clear description and delineation of delimitations and limitations will assist editors and reviewers in understanding any methodological issues.

Data collection

Study limitations can also be introduced during data collection. An unintentional consequence of human subjects research is the potential of the researcher to influence how participants respond to their questions. Even when appropriate methods for sampling have been employed, some studies remain limited by the use of data collected only from participants who decided to enrol in the study (self-selection bias) [ 11 , 19 ]. In some cases, participants may provide biased input by responding to questions they believe are favourable to the researcher rather than their authentic response (social desirability bias) [ 20 – 22 ]. Participants may influence the data collected by changing their behaviour when they are knowingly being observed (Hawthorne effect) [ 23 ]. Researchers—in their role as an observer—may also bias the data they collect by allowing a first impression of the participant to be influenced by a single characteristic or impression of another characteristic either unfavourably (horns effect) or favourably (halo effort) [ 24 ].

Data analysis

Study limitations may arise as a consequence of the type of statistical analysis performed. Some studies may not follow the basic tenets of inferential statistical analyses when they use convenience sampling (i.e. non-probability sampling) rather than employing probability sampling from a target population [ 19 ]. Another limitation that can arise during statistical analyses occurs when studies employ unplanned post-hoc data analyses that were not specified before the initial analysis [ 25 ]. Unplanned post-hoc analysis may lead to statistical relationships that suggest associations but are no more than coincidental findings [ 23 ]. Therefore, when unplanned post-hoc analyses are conducted, this should be clearly stated to allow the reader to make proper interpretation and conclusions—especially when only a subset of the original sample is investigated [ 23 ].

Study results

The limitations of any research study will be rooted in the validity of its results—specifically threats to internal or external validity [ 8 ]. Internal validity refers to reliability or accuracy of the study results [ 26 ], while external validity pertains to the generalizability of results from the study’s sample to the larger, target population [ 8 ].

Examples of threats to internal validity include: effects of events external to the study (history), changes in participants due to time instead of the studied effect (maturation), systematic reduction in participants related to a feature of the study (attrition), changes in participant responses due to repeatedly measuring participants (testing effect), modifications to the instrument (instrumentality) and selecting participants based on extreme scores that will regress towards the mean in repeat tests (regression to the mean) [ 27 ].

Threats to external validity include factors that might inhibit generalizability of results from the study’s sample to the larger, target population [ 8 , 27 ]. External validity is challenged when results from a study cannot be generalized to its larger population or to similar populations in terms of the context, setting, participants and time [ 18 ]. Therefore, limitations should be made transparent in the results to inform research consumers of any known or potentially hidden biases that may have affected the study and prevent generalization beyond the study parameters.

Explain the implication(s) of each limitation

Authors should include the potential impact of the limitations (e.g., likelihood, magnitude) [ 13 ] as well as address specific validity implications of the results and subsequent conclusions [ 16 , 28 ]. For example, self-reported data may lead to inaccuracies (e.g. due to social desirability bias) which threatens internal validity [ 19 ]. Even a researcher’s inappropriate attribution to a characteristic or outcome (e.g., stereotyping) can overemphasize (either positively or negatively) unrelated characteristics or outcomes (halo or horns effect) and impact the internal validity [ 24 ]. Participants’ awareness that they are part of a research study can also influence outcomes (Hawthorne effect) and limit external validity of findings [ 23 ]. External validity may also be threatened should the respondents’ propensity for participation be correlated with the substantive topic of study, as data will be biased and not represent the population of interest (self-selection bias) [ 29 ]. Having this explanation helps readers interpret the results and generalize the applicability of the results for their own setting.

Provide potential alternative approaches and explanations

Often, researchers use other studies’ limitations as the first step in formulating new research questions and shaping the next phase of research. Therefore, it is important for readers to understand why potential alternative approaches (e.g. approaches taken by others exploring similar topics) were not taken. In addition to alternative approaches, authors can also present alternative explanations for their own study’s findings [ 13 ]. This information is valuable coming from the researcher because of the direct, relevant experience and insight gained as they conducted the study. The presentation of alternative approaches represents a major contribution to the scholarly community.

Describe steps taken to minimize each limitation

No research design is perfect and free from explicit and implicit biases; however various methods can be employed to minimize the impact of study limitations. Some suggested steps to mitigate or minimize the limitations mentioned above include using neutral questions, randomized response technique, force choice items, or self-administered questionnaires to reduce respondents’ discomfort when answering sensitive questions (social desirability bias) [ 21 ]; using unobtrusive data collection measures (e.g., use of secondary data) that do not require the researcher to be present (Hawthorne effect) [ 11 , 30 ]; using standardized rubrics and objective assessment forms with clearly defined scoring instructions to minimize researcher bias, or making rater adjustments to assessment scores to account for rater tendencies (halo or horns effect) [ 24 ]; or using existing data or control groups (self-selection bias) [ 11 , 30 ]. When appropriate, researchers should provide sufficient evidence that demonstrates the steps taken to mitigate limitations as part of their study design [ 13 ].

In conclusion, authors may be limiting the impact of their research by neglecting or providing abbreviated and generic limitations. We present several examples of limitations to consider; however, this should not be considered an exhaustive list nor should these examples be added to the growing list of generic and overused limitations. Instead, careful thought should go into presenting limitations after research has concluded and the major findings have been described. Limitations help focus the reader on key findings, therefore it is important to only address the most salient limitations of the study [ 17 , 28 ] related to the specific research problem, not general limitations of most studies [ 1 ]. It is important not to minimize the limitations of study design or results. Rather, results, including their limitations, must help readers draw connections between current research and the extant literature.

The quality and rigor of our research is largely defined by our limitations [ 31 ]. In fact, one of the top reasons reviewers report recommending acceptance of medical education research manuscripts involves limitations—specifically how the study’s interpretation accounts for its limitations [ 32 ]. Therefore, it is not only best for authors to acknowledge their study’s limitations rather than to have them identified by an editor or reviewer, but proper framing and presentation of limitations can actually increase the likelihood of acceptance. Perhaps, these issues could be ameliorated if academic and research organizations adopted policies and/or expectations to guide authors in proper description of limitations.

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Title: wiping out the limitations of large language models -- a taxonomy for retrieval augmented generation.

Abstract: Current research on RAGs is distributed across various disciplines, and since the technology is evolving very quickly, its unit of analysis is mostly on technological innovations, rather than applications in business contexts. Thus, in this research, we aim to create a taxonomy to conceptualize a comprehensive overview of the constituting characteristics that define RAG applications, facilitating the adoption of this technology in the IS community. To the best of our knowledge, no RAG application taxonomies have been developed so far. We describe our methodology for developing the taxonomy, which includes the criteria for selecting papers, an explanation of our rationale for employing a Large Language Model (LLM)-supported approach to extract and identify initial characteristics, and a concise overview of our systematic process for conceptualizing the taxonomy. Our systematic taxonomy development process includes four iterative phases designed to refine and enhance our understanding and presentation of RAG's core dimensions. We have developed a total of five meta-dimensions and sixteen dimensions to comprehensively capture the concept of Retrieval-Augmented Generation (RAG) applications. When discussing our findings, we also detail the specific research areas and pose key research questions to guide future information system researchers as they explore the emerging topics of RAG systems.

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• Published: 07 August 2024

Highest ocean heat in four centuries places Great Barrier Reef in danger

• Benjamin J. Henley   ORCID: orcid.org/0000-0003-3940-1963 1 , 2 , 3 ,
• Helen V. McGregor   ORCID: orcid.org/0000-0002-4031-2282 1 , 2 ,
• Andrew D. King   ORCID: orcid.org/0000-0001-9006-5745 4 , 5 ,
• Ove Hoegh-Guldberg   ORCID: orcid.org/0000-0001-7510-6713 6 ,
• Ariella K. Arzey 1 , 2 ,
• David J. Karoly 4 ,
• Janice M. Lough 7 ,
• Thomas M. DeCarlo   ORCID: orcid.org/0000-0003-3269-1320 8 , 9 &
• Braddock K. Linsley   ORCID: orcid.org/0000-0003-2085-0662 10  

Nature volume  632 ,  pages 320–326 ( 2024 ) Cite this article

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• Climate change
• Environmental impact
• Palaeoclimate

Mass coral bleaching on the Great Barrier Reef (GBR) in Australia between 2016 and 2024 was driven by high sea surface temperatures (SST) 1 . The likelihood of temperature-induced bleaching is a key determinant for the future threat status of the GBR 2 , but the long-term context of recent temperatures in the region is unclear. Here we show that the January–March Coral Sea heat extremes in 2024, 2017 and 2020 (in order of descending mean SST anomalies) were the warmest in 400 years, exceeding the 95th-percentile uncertainty limit of our reconstructed pre-1900 maximum. The 2016, 2004 and 2022 events were the next warmest, exceeding the 90th-percentile limit. Climate model analysis confirms that human influence on the climate system is responsible for the rapid warming in recent decades. This attribution, together with the recent ocean temperature extremes, post-1900 warming trend and observed mass coral bleaching, shows that the existential threat to the GBR ecosystem from anthropogenic climate change is now realized. Without urgent intervention, the iconic GBR is at risk of experiencing temperatures conducive to near-annual coral bleaching 3 , with negative consequences for biodiversity and ecosystems services. A continuation on the current trajectory would further threaten the ecological function 4 and outstanding universal value 5 of one of Earth’s greatest natural wonders.

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Like many coral reefs globally, the World Heritage-listed GBR in Australia is under threat 4 , 6 . Mass coral bleaching, declining calcification rates 5 , 7 , outbreaks of crown-of-thorns starfish ( Acanthaster spp.) 8 , severe tropical cyclones 9 and overfishing 10 have placed compounding detrimental pressures on the reef ecosystem. Coral bleaching typically occurs when heat stress triggers the breakdown of the symbiosis between corals and their symbiotic dinoflagellates 11 . Although coral bleaching can occur locally as a result of low salinity, cold waters or pollution, regional and global mass bleaching events, in which the majority of corals in one or more regions bleach at once, are strongly associated with increasing SST linked to global warming 2 .

The first modern observations of mass coral bleaching on the GBR occurred in the 1980s, but these events were less widespread and generally less severe 3 than the bleaching events in the twenty-first century 4 . Stress bands in coral skeletal cores have provided potential evidence for pre-1980s bleaching in the GBR and Coral Sea, such as during the 1877–78 El Niño 12 . However, stress bands are evident in relatively few cores before 1980 (ref. 12 ),  suggesting that severe mass bleaching did not occur in the 1800s and most of the 1900s.

As the oceans have warmed, however, mass coral bleaching events have become increasingly lethal to corals 4 . Coral bleaching on the GBR 1 in 1998 coincided with a strong eastern-Pacific El Niño, and in 2002 with a weak El Niño. El Niño events can induce lower cloud cover and increased solar irradiance over the GBR 13 , increasing the risk of thermal stress and mass bleaching events 14 . In 2004, water temperatures were anomalously warm, and although bleaching occurred in the Coral Sea 15 , it was not widespread in the GBR, probably because there was reduced upwelling and an associated reduced influence of nutrients on symbiotic dinoflagellate expulsion 16 .

However, in the nine January–March periods from 2016 to 2024 (inclusive) there were five mass coral bleaching events on the GBR. Each was associated with high SSTs and affected large sections of the reef. GBR mass bleaching occurred in both 2016 and 2017, influenced by the presence of an El Niño event in 2016, and led to the death of at least 50% of shallow-water (depths of 5–10 m) reef-building corals 4 . Major bleaching events occurred again in quick succession in 2020 and 2022, with the accumulated heat stress for large sections of the GBR reaching levels conducive to widespread bleaching but lower levels of coral mortality 1 . The bleaching event in 2022 occurred, unusually, during a La Niña event, which is typically associated with cooler summer SSTs, higher than average rainfall and higher cloud cover on the GBR 1 . At the time of writing, researchers are assessing the impacts of the 2024 mass bleaching event.

The frequency of recent mass coral bleaching and mortality on the GBR is cause for concern. In 2021, the World Heritage Committee of the United Nations Educational, Scientific and Cultural Organization (UNESCO) drafted 17 a decision to inscribe the GBR on the List of World Heritage in Danger, stating that the reef is “facing ascertained danger”, citing recent mass coral bleaching events and insufficient progress by the State Party (Australia) in countering climate change, improving water quality and land management issues. The committee’s adopted decisions 18 have not included inscription of the ‘in danger’ status, but the draft inscription highlights the seriousness of the recent mass coral bleaching events. Authorities in Australia 5 have noted that climate change and coral bleaching have deteriorated the integrity of the outstanding universal value of the GBR, a defining feature of its World Heritage status.

Although rapidly rising SSTs are attributed to human activities with virtual certainty 19 , understanding the multi-century SST history of the GBR is critical to understanding the influence of SST on mass coral bleaching and mortality in recent decades. Putting aside a problematic attempt to do this 20 , which was discredited 21 , 22 , knowledge of the long-term context for GBR SSTs comes primarily from two multi-century reconstructions based on the geochemistry of coral cores collected from the inner shelf 23 and outer shelf 24 (Flinders Reef) in the central GBR. These reconstructions showed that SSTs in the early 2000s were not unusually high relative to levels in the past three centuries, with five-year mean SSTs (and salinities) estimated to be higher in the 1700s than in the 1900s. However, these records were limited by their relatively coarse five-year sampling resolution and their most recent data point being from the early 2000s. After these studies were published, SSTs in the GBR have continued to rise. Updated analysis of coral data from Flinders Reef provides valuable improved temporal resolution 25 , but interpretations of these records remain limited spatially.

Here, we investigate the recent high SST events in the GBR region in the context of the past four centuries. We combine a network of 22 coral Sr/Ca and δ 18 O palaeothermometer series (Supplementary Tables 1 and 2 ) located in and near to the Coral Sea region to infer spatial mean SST anomalies (SSTAs) for January–March, the months when maximum SST and thermal bleaching are most likely to occur in the Coral Sea 16 , 26 , each year from 1618 to 1995 ( Methods and Supplementary Information ). Anthropogenic climate change began and proceeded entirely within the multi-century lives of some of these massive coral colonies, offering a continuous multi-century record covering the industrial era. We use this 1618–1995 reconstruction and the available 1900–2024 instrumental data to contextualize the modern trend and rank four centuries of January–March SSTAs with greater precision than was previously possible. We then assess the degree of human influence on ocean temperatures in the region using climate model simulations run both with and without anthropogenic forcing.

The instrumental period (1900–present)

Mass coral bleaching on the GBR in 2016, 2017, 2020, 2022 and 2024 during January–March coincided with widespread warm SSTAs in the surrounding seas 1 , including the Coral Sea (Fig. 1a–e , using ERSSTv5 data 27 ). The Coral Sea and GBR have experienced a strong warming trend since 1900 (Fig. 1f ). January–March SSTAs averaged over the GBR are strongly correlated ( ρ  = 0.84, P   ≪  0.01) with those in the broader Coral Sea (Fig. 1f ), including when the long-term warming trend is removed from both time series ( ρ  = 0.69, P  < 0.01; Supplementary Fig. 4 ). Based on the strength of this correlation, we associate high January–March area-averaged Coral Sea SSTAs with increased thermal bleaching risk in the GBR.

a – e , SSTAs (using ERSSTv5 data) for January–March in the Australasian region relative to the 1961–90 average for the five recent GBR mass coral bleaching years: 2016, 2017, 2020, 2022 and 2024. The black box shows the Coral Sea region (4° S–26° S, 142° E–174° E). f , Coral Sea and GBR mean SSTAs for 1900–2024 in January–March relative to the 1961–90 average. The black vertical lines indicate the five recent GBR mass coral bleaching years.

Record temperatures were set in 2016 and 2017 in the Coral Sea, and in 2020 they peaked fractionally below the record high of 2017. The January–March of 2022 was another warm event, the fifth warmest on record at the time. Recent data (ERSSTv5) indicate that 2024 set a new record by a margin of more than 0.19 °C above the previous record for the region. The January–March mean SSTs averaged over the five mass bleaching years during the period 2016–2024 are 0.77 °C higher than the 1961–90 January–March averages in both the Coral Sea and the GBR. The multidecadal warming trend, extreme years and association between GBR and Coral Sea SSTs are similar for the HadISST 28 gridded SST dataset, with some notable differences in the 1900–40 period (Supplementary Fig. 3 ). Furthermore, analysis of modern temperature-sensitive Sr/Ca series from GBR corals for 1900–2017 provides coherent independent evidence of statistically significant multi-decadal warming trends in January–March SSTs in the central and southern GBR (Supplementary Information section  4.2 ).

A multi-century context (1618–present)

Reconstructing Coral Sea January–March SSTs from 1618 to 1995 extends the century-long instrumental record back in time by an additional three centuries (Fig. 2a and Methods ). The reconstruction (calibrated to ERSSTv5) shows that multi-decadal SST variability was a persistent feature in the past. At the centennial timescale, there is relative stability before 1900, with the exception that cooler temperatures prevailed in the 1600s. Warming during the industrial era has been evident since the early 1900s (Fig. 2a ). There is a warming trend for January–March of 0.09 °C per decade for 1900–2024 and 0.12 °C per decade for 1960–2024 (Fig. 1f ) using ERSSTv5 data. Calibrating our reconstruction to HadISST1.1 yields similar results, with some differences in the degree of pre-1900 variability at both multi-decadal and centennial timescales (Supplementary Information section  5.2.6 ).

a , Reconstructed and observed mean January–March SSTAs in the Coral Sea for 1618–2024 relative to 1961–90. Dark blue, highest skill (maximum coefficient of efficiency) reconstruction with the full proxy network; light blue, 5th–95th-percentile reconstruction uncertainty; black, observed (ERSSTv5) data. Red crosses indicate the five recent mass bleaching events. Dashed lines indicate the best estimate (highest skill, red) and 95th-percentile (pink) uncertainty bound for the maximum pre-1900 January–March SSTA. b , Central GBR SSTA for the inner shelf 23 in thick orange and outer shelf 25 (Flinders Reef) in thin orange lines; these series are aligned here (see Methods ) with modern observations of mean GBR SSTAs for January–March relative to 1961–90. Observed data are shown at annual (grey line) and five-year (black line with open circles, plotted at the centre of each five-year period and temporally aligned with the five-year coral series 23 ) resolution. Dashed lines indicate best-estimate pre-1900 January–March maxima for refs. 23 (red) and 25 (pink). Orange shading indicates 5th–95th-percentile uncertainty bounds. Red crosses indicate the five recent mass bleaching events. c , Evaluation metrics for the Coral Sea reconstruction (Supplementary Information section  3.1 ); RE, reduction of error; CE, coefficient of efficiency; Rsq-cal, R-squared in the calibration period; Rsq-ver, R-squared in the verification (evaluation) period. d , Coral data locations relative to source data region (orange box) and Coral Sea region (red box). Coral proxy metadata are given in Supplementary Tables 1 and 2 .

Our best-estimate (highest skill; Methods ) annual-resolution Coral Sea reconstruction (Fig. 2a ), using the full coral network calibrated to the ERSSTv5 instrumental data, indicates that the January–March mean SSTAs in 2016, 2017, 2020, 2022 and 2024 were, respectively, 1.50 °C, 1.54 °C, 1.53 °C, 1.46 °C and 1.73 °C above the 1618–1899 (hereafter ‘pre-1900’) reconstructed average. Using the same best-estimate reconstruction, Coral Sea January–March SSTs during these GBR mass bleaching years were five of the six warmest years the region has experienced in the past 400 years (Fig. 2a ).

By comparing the recent warm events to the reconstruction’s uncertainty range ( Methods ), we quantify, using likelihood terminology consistent with recent reports from the Intergovernmental Panel on Climate Change 19 , that the recent heat extremes in 2017, 2020 and 2024 are ‘extremely likely’ (>95th percentile; Fig. 2a ) to be higher than any January–March in the period 1618–1899. Furthermore, the heat extremes in 2016 and 2022 are (at least) ‘very likely’ (>90th percentile) to be above the pre-1900 maximum. We perform a series of tests that verify that our findings are not simply an artefact of the nature of the coral network itself (Supplementary Information section 5.2 ). In a network perturbation test, we generate 22 subsets of the reconstruction by adding proxy records incrementally in order from the highest to the lowest correlation with the target (Supplementary Information section  5.2.5 ). We confirm that 2017, 2020 and 2024 were ‘extremely likely’ (>95th percentile) to have been warmer than any year pre-1900 (using ERSSTv5 data) for all of these proxy subsets. Furthermore, in 20 of the 22 subsets, 2016 was also ‘extremely likely’ (>95th percentile), rather than ‘very likely’, to be warmer (2022 was ‘extremely likely’ in 14 of the 22 subsets). All our additional tests, including a reconstruction with only Sr/Ca coral data (thereby omitting the possibility of any non-temperature signal in δ 18 O coral on the reconstruction), achieve high reconstruction skill and confirm the extraordinary nature of recent extreme temperatures in the multi-century context (Supplementary Information section  5.2 ). Analyses using HadISST1.1 generally show lower correlations with the coral data and reconstructions with slightly warmer regional SSTs before 1900, along with more-muted centennial and multi-decadal variability in the pre-instrumental period. Nevertheless, the HadISST1.1-calibrated reconstructions show that the recent thermal extremes are well above the best estimate (highest skill) of the pre-1900 maximum of reconstructed January–March SSTAs (Supplementary Fig. 42 ). Furthermore, lower SSTAs (in the HadISST1.1 data) relative to the previous three centuries (as in our reconstructions calibrated to HadISST1.1), coupled with the recently observed mass coral bleaching events, could indicate that long-lived corals have a greater sensitivity to warming than is currently recognized.

Reconstructed regional GBR SSTAs based on a five-year-resolution, multi-century coral δ 18 O record from the central inshore GBR 23 (Fig. 2b ) show similarly strong warming since 1900 but more multi-decadal-to-centennial variability than the Coral Sea reconstruction. Recent five-year mean January–March GBR SSTAs narrowly exceed the best estimate of the maximum pre-1900 five-year mean since the early 1600s (Fig. 2b ). The averages for the five-year periods centred on 2018 and 2022 exceed the pre-1900 maximum by 0.11 °C and 0.06 °C, respectively. Results are similar using the five-year-resolution Flinders Reef (central outer shelf) 24 record (Supplementary Fig. 24 ), although its interpretation is limited by the lack of uncertainty estimates available for that record. Our Coral Sea reconstruction incorporates an updated (annual resolution) record from Flinders Reef 25 , which indicates similar centennial trends (thin orange line in Fig. 2b ) and shows that the recent high January–March SSTA events have approached the estimated local pre-1900 maximum SSTA. Although contiguous multi-century cores from within the GBR are limited in their spatial extent, twentieth-century warming is evident in these records.

The extraordinary nature of the recent Coral Sea January–March SSTs in the context of the past 400 years is further illustrated by comparing the ranked temperature anomalies (Fig. 3 ) for the combined reconstructed and instrumental period from 1618–2024, incorporating reconstruction uncertainty ( Methods ). The mass coral bleaching years of 2016, 2017, 2020, 2022 and 2024, and the heat event of 2004, stand out as the warmest events across the whole 407-year record. The warmest three years (2024, 2017 and 2020) exceed the upper uncertainty bound (95th percentile) of the warmest reconstructed January–March in the pre-1900 period (pink (upper) dashed line in Fig. 3 ); 2016, 2004 and 2022 exceed the 90th percentile bound (red (lower) dashed line in Fig. 3 ). The warming trend is clear in the association between the ascending rank of the temperature anomalies and the year (shown as the colour of the filled circles in Fig. 3 ). Despite high interannual variability, 78 of the warmest 100 January–March periods between 1618 and 2024 occurred after 1900, and the 23 warmest all occur after 1900. The warmest 20 January–March periods all occur after 1950, coinciding with accelerated global warming.

Ranked January–March SSTAs for 1618–2024 relative to 1961–90 (coloured circles) from the best-estimate (highest skill, full coral network) reconstruction (1618–1899) and instrumental (ERSSTv5) data (1900–2024). The year is indicated by the colour of the filled circles. The 5th–95th-percentile uncertainty bounds of the pre-1900 reconstructed SSTAs are shown by small grey dots. The year labels indicate the warmest six years on record, five of which were mass coral bleaching years on the GBR. The pink (upper) dashed line indicates the 95th-percentile uncertainty bound of the maximum pre-1900 reconstructed SSTA; the red (lower) dashed line indicates the 90th-percentile limit.

Assessing anthropogenic influence

Using climate model simulations from the most recent (sixth) phase of the Coupled Model Intercomparison Project 29 (CMIP6), we assess the human influence on January–March SSTAs in the Coral Sea. The model simulations are from two experiments in the Detection and Attribution Model Intercomparison Project (DAMIP) 30 . The first set of simulations represents historical climate conditions, including both the natural and human influences on the climate system over the 1850–2014 period (‘historical’; red in Fig. 4 ). The second experiment is a counterfactual climate that spans the same period and uses the same models but includes only natural influences on the climate, omitting all human influences (‘historical-natural’; blue in Fig. 4 ). The historical experiment includes anthropogenic emissions of greenhouse gases and aerosols, stratospheric ozone changes and anthropogenic land-use changes; the historical-natural experiment does not. Variations in natural climate forcings, such as from volcanic eruptions and solar variability, are incorporated in both experiments. We include models that have a transient climate response (the global mean surface-temperature anomaly at the time of a doubling of atmospheric CO 2 concentration) in the range 1.4–2.2 °C, which is deemed ‘likely’ by the science community 31 ( Methods and Supplementary Information ).

Climate-model simulations of Coral Sea January–March SSTAs relative to the 1850–1900 average for the period 1850–2014, for models within the ‘likely’ range for their transient climate response 31 . The blue line (median) and light blue shading (5th–95th-percentile limits) are from the ‘historical-natural’ climate model simulations (no anthropogenic climate forcing); the red line and light red shading are from the ‘historical’ simulations (anthropogenic influences on the climate included) using the same set of climate models. The climate-model-derived time of emergence of anthropogenic climate change, shown by the grey and black vertical lines (1976 and 1997), is when the ratio of the climate change signal to the standard deviation of noise/variability 32 across model ensemble members first rises above 1 and 2, respectively. All models are represented equally in the model ensemble.

It is only with the incorporation of anthropogenic influences on the climate that the model simulations capture the modern-era warming of the Coral Sea January–March SSTA (Fig. 4 ). The median of the historical simulations has statistically significant warming trends of 0.05 °C, 0.10 °C and 0.15 °C per decade for the periods from 1900, 1950 and 1970 to 2014, respectively; the equivalent historical-natural trends are smaller in magnitude than ±0.01 °C per decade. To further explore the centennial-scale trends, we use a bootstrap ensemble ( Methods ) of the two sets of 165-year simulations from 1850–2014. We found that 100% of the historical bootstrap ensemble has statistically significant positive trends ( Methods ) for 1900–2014, but this value is 0% for the historical-natural ensemble. The observed (ERSSTv5) mean SSTA for 2016–2024 of 0.60 °C relative to 1961–90 is warmer than any nine-year sequence in the 7,095 simulated years in the historical-natural experiments from models with transient climate responses in the ‘likely’ range 31 .

We also use the simulations to estimate the time of emergence of the anthropogenic influence on January–March Coral Sea SSTAs above the natural background variability. The anthropogenic warming signal 32 increases from near zero in 1900 to around 0.5 standard deviations of the variability (‘noise’) in 1960. The climate change signal-to-noise ratio then increases rapidly from 1960 to 2014, exceeding 1.0 in 1976, 2.0 in 1997 and around 2.8 by 2014, the end of these simulations (Fig. 4 , Methods and Supplementary Fig. 50 ). Anthropogenic impacts on the climate are virtually certain to be the primary driver of this long-term warming in the Coral Sea.

Previously, our knowledge of the SST history of the GBR and the Coral Sea region has been highly dependent on instrumental observations, with the exception of the five-year-resolution multi-century coral Sr/Ca and U/Ca SST reconstructions from the two point locations in the central GBR 23 , 24 , an update at one of these locations 25 , seasonal resolution ‘floating’ (in time) chronologies from the GBR in the Holocene 33 , 34 and point SST estimates further back in time 35 . Thus, the context of recent warming trends in the Coral Sea and GBR and their relation to natural variability on decadal to centennial timescales is largely unknown without reconstructions such as the one we developed here.

Our coral proxy network is located mostly beyond the GBR, in the Coral Sea, and some series are located outside the Coral Sea region (Fig. 2d ). The selection of the Coral Sea as a study region allowed for a larger sample of contributing coral proxy data than exists for the GBR. However, coral bleaching on the GBR can be influenced by factors other than large-scale SST, including local oceanic and atmospheric dynamics that can modulate the occurrence and severity of thermal bleaching and mortality events 13 . Nonetheless, warming of seasonal SSTs over the larger Coral Sea region is likely to prime the background state and increase the likelihood of smaller spatio-temporal-scale heat anomalies. Furthermore, where we use only the five-year resolution series directly from the GBR to reconstruct GBR SSTAs, we draw similar conclusions about the long-term trajectory of SSTAs as for our full coral network (Fig. 2b and Supplementary Fig. 24 ). Furthermore, short modern coral series from within the GBR, analysed in this study, document a multi-decadal warming signal that is coherent with instrumental data (Supplementary Figs. 29 and 30 ). Nonetheless, additional high-resolution, multi-century, temperature-sensitive coral geochemical series from within the GBR would help unravel the local and remote ocean–atmosphere contributions to past bleaching events and reduce uncertainties.

The focus on the larger Coral Sea study region also takes advantage of the global modelling efforts of CMIP6. The large number of ensemble members available for CMIP6 means that greater climate model diversity, and therefore greater certainty in our attribution analysis, is possible compared with most single model analyses. There is also a methodological benefit in having high replication of the same experiments run with multiple climate models. However, coarse-resolution global-scale models do not accurately simulate smaller-scale processes, such as inshore currents and mesoscale eddies in the Coral Sea or the Gulf of Carpentaria, which probably affect local surface temperatures and variations in nutrient upwelling in the GBR 36 , 37 . Upwelling on the GBR is linked to the strength of the East Australian Current 16 , the southward branch of the South Pacific subtropical gyre. The CMIP-scale models we use do capture these gyre dynamics. The models show that the East Australian Current is expected to increase in strength as the climate continues to warm through this century 38 , and this may lead to more nutrient inputs that can exacerbate coral sensitivity to rising heat stress 39 , 40 . As well as focusing our model analysis on the larger Coral Sea region, we use a three-month time step. In doing so, we minimize the impact of model spatio-temporal resolution on our inferences about the role of anthropogenic greenhouse-gas emissions on the SST conditions that give rise to GBR mass bleaching.

Remaining uncertainties

We present analyses and interpretations that are as robust as possible given currently available data and methods. However, several sources of remaining uncertainty mean that future reconstructions of past Coral Sea and GBR SSTs could differ from those presented here. Although bias corrections are applied to observational SST datasets such as ERSST and HadISST, these datasets probably retain biases, especially for the period during and before 1945 (ref. 41 ), and these may not be fully accounted for in the uncertainty estimates 42 . Because our reconstructions are calibrated directly to these datasets, future observational-bias corrections are likely to improve proxy-based reconstructions.

Reconstructions of SST that use coral δ 18 O records may be susceptible to the influence of changes in the coral δ 18 O–SST relationship on time periods longer than the instrumental training period, along with non-SST changes in the δ 18 O of seawater, which can covary with salinity. As such, new coral records of temperature-sensitive trace-element ratios such as Sr/Ca, Li/Mg or U/Ca may prove influential in future efforts to distinguish between changes in past temperature and hydroclimate. Owing to the limited availability of multi-century coral data from within the GBR itself, the reconstructed low-frequency variability of GBR SSTs in recent centuries is likely to change as more temperature proxy data become available. It is also likely that new sub-annual resolution records would aid in removing potential signal damping or bias from our use of some annual-resolution records to reconstruct seasonal SSTAs.

Ecological consequences

With global warming of 0.8–1.1 °C above pre-industrial levels 19 there has been a marked increase in mass coral bleaching globally 43 . Even limiting global warming to the Paris Agreement’s ambitious 1.5 °C level would be likely to lead to the loss of 70–90% of corals that are on reefs today 44 . If all current international mitigation commitments are implemented, global mean surface temperature is still estimated to increase in the coming decades, with estimates varying between 1.9 °C (ref. 45 ) and 3.2 °C (ref. 46 ) above pre-industrial levels by the end of this century. Global warming above 2 °C would have disastrous consequences for coral ecosystems 19 , 44 and the hundreds of millions of people who currently depend on them.

Coral reefs of the future, if they can persist, are likely to have a different community structure to those in the recent past, probably one with much less diversity in coral species 4 . This is because mass bleaching events have a differential impact on different coral species. For example, fast-growing branching and tabulate corals are affected more than slower-growing massive species because they have different thermal tolerance 4 . The simplification of reef structures will have adverse impacts on the many thousands of species that rely on the complex three-dimensional structure of reefs 4 . Therefore, even with an ambitious long-term international mitigation goal, the ecological function 4 of the GBR is likely to deteriorate further 5 before it stabilizes.

Coral adaptation and acclimatization may be the only realistic prospect for the conservation of some parts of the GBR this century. However, although adaptation opportunities may be plausible to some extent 47 , they are no panacea because evolutionary changes to fundamental variables such as temperature take decades, if not centuries, to occur, especially in long-lived species such as reef-building corals 48 . There is currently no clear evidence of the real-time evolution of thermally tolerant corals 48 . Most rapid changes depend on a history of exposure to key genetic types and extremes, and there are limitations to genetic adaptation that prevent species-level adaptation to environments outside of their ecological and evolutionary history 19 . Model projections also indicate that rates of coral adaptation are too slow to keep pace with global warming 49 . In a rapidly warming world, the temperature conditions that give rise to mass coral bleaching events are likely to soon become commonplace. So, although we may see some resilience of coral to future marine heat events through acclimatization, thermal refugia are likely to be overwhelmed 50 . Global warming of more than 1.5 °C above pre-industrial levels will probably be catastrophic for coral reefs 44 .

Our new multi-century reconstruction illustrates the exceptional nature of ocean surface warming in the Coral Sea today and the resulting existential risk for the reef-building corals that are the backbone of the GBR. The reconstruction shows that SSTs were relatively cool and stable for hundreds of years, and that recent January–March ocean surface heat in the Coral Sea is unprecedented in at least the past 400 years. The coral colonies and reefs that have lived through the past several centuries, and that yielded the valuable Sr/Ca and δ 18 O data on which our reconstruction is based, are themselves under serious threat. Our analysis of climate-model simulations confirms that human influence is the driver of recent January–March Coral Sea surface warming. Together, the evidence presented in our study indicates that the GBR is in danger. Given this, it is conceivable that UNESCO may in the future reconsider its determination that the iconic GBR is not in danger. In the absence of rapid, coordinated and ambitious global action to combat climate change, we will likely be witness to the demise of one of Earth’s great natural wonders.

Instrumental observations

The Coral Sea and GBR area-averaged monthly SSTAs relative to 1961–90 for January–March are obtained from version 5 of the Extended Reconstructed Sea Surface Temperature dataset (ERSSTv5) 27 . We compare our results using ERSSTv5 with those generated using the Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST1.1) 28 . We use only post-1900 instrumental SST observations here. Although gridded datasets have some coverage before 1900, ship-derived temperature data in the region for that period are too sparse to be reliable for calibrating our reconstruction (Supplementary Information section  1.2 ). The regional mean for the GBR is computed using the seven grid-cell locations used by the Australian Bureau of Meteorology (Supplementary Information section  1.1 ). We define the Coral Sea region as the ocean areas inside 4° S–26° S, 142° E–174° E.

Coral-derived temperature proxy data

We use a network of 22 published and publicly available sub-annual and annual resolution temperature-sensitive coral geochemical series (proxies; Fig. 2d , Supplementary Tables 1 and 2 , and Supplementary Fig. 5a–v ) from the western tropical Pacific in our source data region (4° N–27° S, 134° E–184° E) that cover at least the period from 1900 to 1995. Of these 22 series, 16 are δ 18 O, which are in per mil (‰) notation relative to Vienna PeeDee Belemnite (VPDB) 51 ; the remaining six are Sr/Ca series. The coral data are used as predictors in the reconstruction of January–March mean SSTAs in the Coral Sea region. We apply the inverse Rosenblatt transformation 52 , 53 to the coral data to ensure that our reconstruction predictors are normally distributed. Sub-annually resolved series are converted to the annual time step by averaging across the November–April window. This maximizes the detection of the summer peak values, allowing for some inaccuracy in sub-annual dating and the timing of coral skeleton deposition 54 , 55 . A small fraction (less than 0.8%) of missing data is infilled using the regularized expectation maximization (RegEM) algorithm 56 (Supplementary Information section  2.3 ), after which the proxy series are standardized such that each has a mean of zero and a standard deviation of one over their common 1900–1995 period.

Reconstruction method

To produce our Coral Sea reconstruction, we use nested principal component regression 57 (PCR), in which the principal components of the network of 22 coral proxies are used as regressors against the target-region January–March SSTA relative to the 1961–90 average. We perform the reconstructions separately for each nest of proxies, where a nest is a set of proxies that cover the same time period. The longest nest dates back to 1618, when at least two series are available. The nests allow for the use of all coral proxies over the full time period of their coverage. The 96-year portion of the instrumental period (1900–1995) that overlaps with the reconstruction period is used for calibration and evaluation (or equivalently, verification) against observations. We reconstruct regional SSTAs from the principal components of the coral network of δ 18 O and Sr/Ca data, rather than their local SST calibrations, to minimize the number of computational steps and to aid in representing the full reconstruction uncertainty.

Principal component analysis (PCA) is used to reduce the dimensionality of the proxy matrix, as follows. Let P ( t , r ) denote the palaeoclimate-data matrix during the time period t  = 1,..., n at an annual time step for proxy series r  = 1,..., p . PCA is undertaken on this matrix during the calibration period, P cal . We obtain the principal component coefficients matrix P coeff ( r , e ) for principal components e  = 1,..., n PC and principal component scores P score ( t , e ), which are representations of the input matrix P cal in the principal component space. P score is truncated to include n PC,use principal components to form \({P}_{{\rm{score}}}^{{\prime} }\) such that the variance of the proxy network explained by the n PC,use principal components is greater than \({\sigma }_{{\rm{expl}}}^{2}\) (which we set to 95%). Reconstruction tests in which \({\sigma }_{{\rm{expl}}}^{2}\) is varied from 70% to 95% show that our results are not strongly sensitive to this choice, and tests based on lag-one autoregressive noise for \({\sigma }_{{\rm{expl}}}^{2}\) from 50% to 99% further support this choice (Supplementary Information section  3.2 ). These principal components are used as predictors against which the Coral Sea January–March instrumental SSTAs are regressed. We regress the standardized SSTA target data during the calibration period, I cal , against the retained principal components of the predictor data, \({P}_{{\rm{score}}}^{{\prime} }\) :

Thus, we obtain n PC,use estimates of the regression coefficients γ e with gaussian error term ε t  ~  N (0, \({\sigma }_{N}^{2}\) ). The principal components are extended back into the pre-instrumental period by multiplying the entire proxy matrix P ( t , p ) with the truncated principal component coefficient matrix \({P}_{{\rm{coeff}}}^{{\prime} }\) ( t , e ) to obtain \({Q}_{{\rm{coeff}}}^{{\prime} }\) :

The reconstruction proceeds with the fitted regression coefficients γ e and extended coefficient matrix \({Q}_{{\rm{coeff}}}^{{\prime} }\) to obtain a reconstruction time series R m ( t ) for a given nest of proxy series

The standardized reconstruction R m ( t ) is then calibrated to the instrumental data such that the standard deviation and mean of the reconstruction and target during the calibration interval are equal. As well as obtaining reconstructions for each nest of available proxies, we compute stitched reconstructions S c ( t ) for each calibration period c , which include at each time step the reconstructed data for the proxy nest with maximum coefficient of efficiency 58 , 59 (Supplementary Information section  3.1 ). This procedure is performed for contiguous calibration intervals between 60 and 80 years duration between 1900 and 1995, with interval width and location increments of two years, reserving the remaining data in the overlapping period for independent evaluation, and for all proxy nests. The reconstruction error is modelled with a lag-one autoregressive process fitted to the residuals. We evaluate the capacity of our reconstruction method to achieve spurious skill from overfitting by performing a test in which we replace the coral data with synthetic noise (Supplementary Information section  3.2i ). We find that reconstructions based on synthetic noise achieve extremely low or zero skill and as more noise principal components are included in the regression, the evaluation metrics indicate declining skill. Our reconstruction and evaluation methods therefore guard against the potential for spurious skill.

Pseudo-proxy reconstructions

Our reconstruction method is further evaluated by using a pseudo-proxy modelling approach based on the Community Earth System Model (CESM) Last Millennium Experiment (LME) 60 , for which there are 13 full-forcing ensemble members covering the period 850–2005. We use the pseudo-proxy reconstructions to evaluate our reconstruction method and coral network in a fully coupled climate-model environment. We form pseudo-proxies by extracting from each LME ensemble member the SST and sea surface salinity (SSS) from the 1.5° × 1.5° grid cell located nearest to our coral data. We then apply proxy system models in the form of linear regression models, basing δ 18 O on both SST and SSS, and Sr/Ca on SST only (Supplementary Information section  3.3 ). We set the spatial and temporal availability of the pseudo-coral network to match that of the coral network. We then apply our PCR reconstruction and evaluation procedure to the pseudo-proxy network, taking advantage of the availability of the modelled Coral Sea SSTA data across the multi-century period of 1618–2005, which allows for the evaluation of the pseudo-proxy reconstruction over this entire time period. We first test our method using a ‘perfect proxy’ approach (with no proxy measurement error) before superimposing synthetic noise on the pseudo-proxy time series, evaluating our methodology at two separate levels of measurement error, quantified by signal-to-noise ratios of 1.0 and 4.0. The evaluation metrics for these tests indicate that our coral network and reconstruction method obtain skilful reconstructions of Coral Sea SSTAs in the climate-model environment (Supplementary Figs. 17b , 18 , 20b , 21 , 22b and 23 ).

Comparison with independent coral datasets

We use two multi-century five-year-resolution coral series from the central GBR 23 , 24 (Fig. 2b and Supplementary Fig. 24 ) and a network of sub-annual and annual resolution modern coral series (dated from 1900 onwards but not covering the full 1900–1995 period) from 44 sites in the GBR (Supplementary Information section  4.2 ) for independent evaluation of coral-derived evidence for warming in the region. We estimate five-year GBR SSTAs (Fig. 2b ) by aligning the post-1900 mean and variance of the proxy and instrumental (ERSSTv5) data.

Reconstruction sensitivity to non-SST influences

Of the 22 available coral series, 16 are records of δ 18 O, a widely used measure of the ratio of the stable isotopes 18 O and 16 O. In the tropical Pacific Ocean, δ 18 O is significantly correlated with SST 61 , 62 , 63 , 64 . Coral δ 18 O is also sensitive to the δ 18 O of seawater 65 , which can reflect advection of different water masses and/or changes in freshwater input, such as from riverine sources or precipitation, which in turn co-vary with SSS. Thus, it is generally considered that the main non-SST contributions to coral δ 18 O are processes that co-vary with SSS 62 , 66 . Our methodology minimizes the influence of non-temperature impacts on the reconstruction by exploiting the contrast in spatial heterogeneity between SST and SSS in January–March (Supplementary Information section  5.1 ). SSS is spatially inhomogeneous in the tropical Pacific 66 , 67 , leading to low coherence in SSS signals across our coral network. By contrast, the strong and coherent SST signal across our coral network locations and the Coral Sea region leads to principal components that are strongly representative of SST variations. This produces a skilful reconstruction of SST, as determined by evaluation against independent observations, and low correlations with SSS across the Coral Sea region (Supplementary Fig. 31 ).

Although the likelihood of non-SST influences on our SST reconstruction is low, we nonetheless test the sensitivity of our reconstruction and its associated interpretations to the possibility of these influences on the coral data. The tests compute the correlations between our best-estimate SSTA reconstruction (highest coefficient of efficiency) and observations of SSS, along with a series of additional reconstructions based on subsets of our coral network. The correlations between our highest coefficient of efficiency January–March Coral Sea SSTA reconstruction and January–March SSS are mapped for the Coral Sea and its neighbouring domain using three instrumental SSS datasets (Supplementary Fig. 31 ). Correlations are not statistically significant over most of the domain. Noting differing spatial correlation patterns between the instrumental SSS datasets 68 , which also cover different time periods (Supplementary Information section  5.1 ), we undertake six sensitivity tests using subsets of the coral network (Supplementary Information section  5.2 ). We use the following combinations of coral series: (1) the full network of 22 δ 18 O and Sr/Ca series (Figs. 2a and 3 ); (2) a subset of the six available Sr/Ca series (Supplementary Figs. 32 – 33 ), to test how the reconstruction is influenced by the inclusion of coral δ 18 O records; (3) a fixed nest subset of the five longest coral series, extending back to at least 1700 (Supplementary Figs. 34 – 35 ), to test for the potential influence of combining series of differing lengths (from our splicing of portions of the best reconstructions from each nest); (4) a subset of the ten coral series that are most strongly correlated with the target (Supplementary Figs. 36 and 37 ), to test how our reconstruction is influenced by the inclusion of coral series that are less strongly correlated with our target; (5) a subset of coral series that excludes the six records that are reported to potentially include biological mediation or non-climatic effects, or have low correlation with the target (Supplementary Figs. 38 and 39 ), to test their influence on the reconstruction; and (6) a network perturbation test comprising 22 separate subsets of proxies, in which proxy records are added incrementally in order of highest to lowest correlation with the target, starting with a single coral series and increasing the number of included proxies to all 22 series in our network (Supplementary Information section  5.2.5 ), to systematically quantify the influence of gradually including more coral datasets on our reconstruction and its interpretations.

The evaluation metrics (Fig. 2c and Supplementary Figs. 32b , 34b , 36b and 38b ) indicate a skilful reconstruction back to 1618 for the reconstructions based on the Full, Sr/Ca only, Long, Best-10 and OmitBioMed networks. These reconstructions explain 82.7%, 80.6%, 77.6%, 79.8% and 80.4% (R-squared values) of the variance in January–March SSTAs, respectively, in the independent evaluation periods (using ERSSTv5b). All coral subsets in the network perturbation test produce skilful reconstructions (Supplementary Fig. 40 ). The highest-skill reconstructions for all subsets in the network perturbation test align with our key interpretations (Supplementary Figs. 41 and 42 ). Together, our sensitivity tests show that the coral network, observational data and reconstruction methodology are a sound basis for reconstructing Coral Sea January–March SSTAs in past centuries and contextualizing recent high-SST events ( Supplementary Information ).

Climate-model attribution ensembles and experiments

The multi-model attribution analysis used here is based on simulations from CMIP6. We analyse simulations from the historical experiment (including natural and anthropogenic influences for 1850–2014) and the historical-natural experiment (natural-only forcings for 1850–2014). We select climate models for which monthly surface temperature is available in at least three historical and historical-natural simulations (Supplementary Table 5 ). All model simulations are interpolated to a common regular 1.5° × 1.5° latitude–longitude grid. January–March SSTAs relative to 1961–90 are calculated for each simulation. The full historical all-forcings ensemble is composed of 14 models with 268 simulations for 1850–2014. The natural-only ensemble is composed of the same 14 models with 95 individual simulations. A subset of climate models in the CMIP6 ensemble are considered by the science community to be ‘too hot’, simulating warming in response to increased atmospheric carbon dioxide concentrations that is larger than that supported by independent evidence 31 . We omit these models from our analysis by including only models with a transient climate response in the ‘likely’ range 31 of 1.4–2.2 °C. Our results are not strongly sensitive to this selection (Supplementary Information section  6.3 ). The ten remaining models yield a total of 25,410 years from 154 historical ensemble members and 7,095 years from 43 historical-natural ensemble members. We weight the models equally in our analysis using bootstrap sampling. We report linear trends based on simple linear regression models fitted with ordinary least squares. The statistical significance of linear trends is assessed using the Spearman’s rank correlation test 69 .

Time of emergence of the anthropogenic impact

We assess the anthropogenic influence on SSTAs in the Coral Sea region by starting with the assumption that any anthropogenic influence on SSTAs in the Coral Sea is indistinguishable from natural variability at the commencement of the model experiments. We measure the impact of anthropogenic influence on the climate in the region using a signal-to-noise approach 32 , 70 . We calculate the anthropogenic ‘signal’ as the mean of the difference between the smoothed (using a 41-year Lowess filter) modelled historical Coral Sea SSTA and the mean smoothed modelled historical-natural SSTA. Our ‘noise’ is the standard deviation of the difference between the modelled historical SSTA and its smoothed time series (Supplementary Information section  6 ).

Methods additionally rely on Supplementary Information and refs. 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 .

Data availability

The ERSSTv5 instrumental SST data are available from the US National Oceanic and Atmospheric Administration at https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html . The HadISST1.1 data are available from the UK Met Office at https://www.metoffice.gov.uk/hadobs/hadisst/ . The original coral palaeoclimate data are available at the links provided in Supplementary Table 2 . Land areas for maps are obtained from the Mapping Toolbox v.23.2 in Matlab v.2023b and the Global Self-consistent, Hierarchical, High-resolution Geography (GSHHS) Database at https://www.soest.hawaii.edu/pwessel/gshhg/ through the m_map toolbox by R. Pawlowicz, available at https://www.eoas.ubc.ca/%7Erich/map.html . Prepared data from the coral geochemical series, reconstructions and climate models that support the findings of this study are available at: https://doi.org/10.24433/CO.4883292.v1 .

Code availability

The code that supports the findings of this study is available and can be run at : https://doi.org/10.24433/CO.4883292.v1 .

Australian Institute of Marine Science. Long-Term Monitoring Program. https://www.aims.gov.au/research-topics/monitoring-and-discovery/monitoring-great-barrier-reef/long-term-monitoring-program (2024).

Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543 , 373–377 (2017).

Article   ADS   CAS   PubMed   Google Scholar  

Hoegh-Guldberg, O. Climate change, coral bleaching and the future of the world’s coral reefs. Mar. Freshw. Res. 50 , 839–866 (1999).

Google Scholar  

Hughes, T. P. et al. Global warming transforms coral reef assemblages. Nature 556 , 492–496 (2018).

Great Barrier Reef Marine Park Authority. Great Barrier Reef Outlook Report 2019 (Great Barrier Reef Marine Park Authority, 2019).

Hughes, T. P. et al. Coral reefs in the Anthropocene. Nature 546 , 82–90 (2017).

Davis, K. L., Colefax, A. P., Tucker, J. P., Kelaher, B. P. & Santos, I. R. Global coral reef ecosystems exhibit declining calcification and increasing primary productivity. Commun. Earth Environ. 2 , 105 (2021).

Article   ADS   Google Scholar  

Westcott, D. A. et al. Relative efficacy of three approaches to mitigate Crown-of-Thorns Starfish outbreaks on Australia’s Great Barrier Reef. Sci. Rep. 10 , 12594 (2020).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Mellin, C. et al. Spatial resilience of the Great Barrier Reef under cumulative disturbance impacts. Glob. Chang. Biol. 25 , 2431–2445 (2019).

Article   ADS   PubMed   Google Scholar  

Jackson, J. B. C. et al. Historical overfishing and the recent collapse of coastal ecosystems. Science 293 , 629–637 (2001).

Article   CAS   PubMed   Google Scholar  

Hoegh-Guldberg, O. & Smith, G. J. The effect of sudden changes in temperature, light and salinity on the population density and export of zooxanthellae from the reef corals Stylophora pistillata Esper and Seriatopora hystrix Dana. J. Exp. Mar. Biol. Ecol. 129 , 279–303 (1989).

Article   Google Scholar  

DeCarlo, T. M. et al. Acclimatization of massive reef-building corals to consecutive heatwaves. Proc. Biol. Sci. 286 , 20190235 (2019).

PubMed   PubMed Central   Google Scholar  

McGowan, H. & Theobald, A. ENSO weather and coral bleaching on the Great Barrier Reef, Australia. Geophys. Res. Lett. 44 , 10,601–10,607 (2017).

Zhao, W., Huang, Y., Siems, S. & Manton, M. The role of clouds in coral bleaching events over the Great Barrier Reef. Geophys. Res. Lett. 48 , e2021GL093936 (2021).

Oxley, W. G., Emslie, M., Muir, P. & Thompson, A. Marine Surveys Undertaken in the Lihou Reef National Nature Reserve (Australian Institute of Marine Science, 2004).

DeCarlo, T. M. & Harrison, H. B. An enigmatic decoupling between heat stress and coral bleaching on the Great Barrier Reef. PeerJ 7 , e7473 (2019).

Article   PubMed   PubMed Central   Google Scholar  

UNESCO World Heritage Committee. Extended 44th Session of the World Heritage Committee, Fuzhou (China) 16–31 July 2021 . Draft decision 44 COM 7B.90. https://whc.unesco.org/document/188005 (UNESCO, 2021).

UNESCO World Heritage Committee. Extended 45th Session of the World Heritage Committee, Riyadh (Saudi Arabia) 10–25 September 2023 . Decision 45 COM 7B.13. https://whc.unesco.org/document/199654 (UNESCO, 2023).

IPCC. Summary for Policymakers. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).

Kamenos, N. A. & Hennige, S. J. Reconstructing four centuries of temperature-induced coral bleaching on the Great Barrier Reef. Front. Mar. Sci. 5 , 283 (2018).

Hoegh-Guldberg, O. et al. Commentary: reconstructing four centuries of temperature-induced coral bleaching on the Great Barrier Reef. Front. Mar. Sci. 6 , 86 (2019).

DeCarlo, T. M. Commentary: reconstructing four centuries of temperature-induced coral bleaching on the Great Barrier Reef. Front. Mar. Sci. 7 , 30 (2020).

Hendy, E. J. et al. Abrupt decrease in tropical Pacific sea surface salinity at end of Little Ice Age. Science 295 , 1511–1514 (2002).

Calvo, E. et al. Interdecadal climate variability in the Coral Sea since 1708 A.D. Palaeogeogr. Palaeoclimatol. Palaeoecol. 248 , 190–201 (2007).

Zinke, J. et al. North Flinders Reef (Coral Sea, Australia) Porites sp. corals as a candidate global boundary stratotype section and point for the Anthropocene series. Anthropocene Rev. 10 , 201–224 (2023).

Spady, B. L. et al. Global Coral Bleaching Database (NCEI Accession 0228498) (NOAA National Centers for Environmental Information, 2022); https://www.ncei.noaa.gov/archive/accession/0228498 .

Huang, B. et al. Extended reconstructed sea surface temperature, Version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Clim. 30 , 8179–8205 (2017).

Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. Atmos. 108 , 4407 (2003).

Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9 , 1937–1958 (2016).

Gillett, N. P. et al. The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6. Geosci. Model Dev. 9 , 3685–3697 (2016).

Hausfather, Z., Marvel, K., Schmidt, G. A., Nielsen-Gammon, J. W. & Zelinka, M. Climate simulations: recognize the ‘hot model’ problem. Nature 605 , 26–29 (2022).

Hawkins, E. et al. Observed emergence of the climate change signal: from the familiar to the unknown. Geophys. Res. Lett. 47 , e2019GL086259 (2020).

Gagan, M. K. et al. Temperature and surface-ocean water balance of the mid-Holocene tropical western Pacific. Science 279 , 1014–1018 (1998).

Arzey, A. K. et al. Coral skeletal proxy records database for the Great Barrier Reef, Australia. Preprint at Earth Syst. Sci. Data https://doi.org/10.5194/essd-2024-159 (2024).

Brenner, L. D. et al. Coral record of Younger Dryas Chronozone warmth on the Great Barrier Reef. Paleoceanogr. Paleoclimatol. 35 , e2020PA003962 (2020).

Furnas, M. J. & Mitchell, A. W. Nutrient inputs into the central Great Barrier Reef (Australia) from subsurface intrusions of Coral Sea waters: a two-dimensional displacement model. Cont. Shelf Res. 16 , 1127–1148 (1996).

Wolanski, E., Andutta, F., Deleersnijder, E., Li, Y. & Thomas, C. J. The Gulf of Carpentaria heated Torres Strait and the Northern Great Barrier Reef during the 2016 mass coral bleaching event. Estuar. Coast. Shelf Sci. 194 , 172–181 (2017).

Oliver, E. C. J. & Holbrook, N. J. Extending our understanding of South Pacific gyre ‘spin-up’: modeling the East Australian Current in a future climate. J. Geophys. Res. Oceans 119 , 2788–2805 (2014).

DeCarlo, T. M. et al. Nutrient-supplying ocean currents modulate coral bleaching susceptibility. Sci. Adv. 6 , eabc5493 (2020).

Article   ADS   PubMed   PubMed Central   Google Scholar  

Wiedenmann, J. et al. Nutrient enrichment can increase the susceptibility of reef corals to bleaching. Nat. Clim. Chang. 3 , 160–164 (2013).

Article   ADS   CAS   Google Scholar  

Chan, D. & Huybers, P. Correcting observational biases in sea surface temperature observations removes anomalous warmth during World War II. J. Clim. 34 , 4585–4602 (2021).

Chan, D., Kent, E. C., Berry, D. I. & Huybers, P. Correcting datasets leads to more homogeneous early-twentieth-century sea surface warming. Nature 571 , 393–397 (2019).

Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359 , 80–83 (2018).

Hoegh-Guldberg, O. et al. Chapter 3: Impacts of 1.5°C global warming on natural and human systems. In Global Warming of 1.5°C (eds Masson-Delmotte, V. et al.) (IPCC, 2018).

Meinshausen, M. et al. Realization of Paris Agreement pledges may limit warming just below 2 °C. Nature 604 , 304–309 (2022).

Matthews, H. D. & Wynes, S. Current global efforts are insufficient to limit warming to 1.5 °C. Science 376 , 1404–1409 (2022).

Coles, S. L. et al. Evidence of acclimatization or adaptation in Hawaiian corals to higher ocean temperatures. PeerJ 6 , e5347 (2018).

Hughes, T. P., Baird, A. H., Morrison, T. H. & Torda, G. Principles for coral reef restoration in the anthropocene. One Earth 6 , 656–665 (2023).

Logan, C. A., Dunne, J. P., Ryan, J. S., Baskett, M. L. & Donner, S. D. Quantifying global potential for coral evolutionary response to climate change. Nat. Clim. Chang. 11 , 537–542 (2021).

Dixon, A. M., Forster, P. M., Heron, S. F., Stoner, A. M. K. & Beger, M. Future loss of local-scale thermal refugia in coral reef ecosystems. PLOS Clim. 1 , e0000004 (2022).

Coplen, T. B. Discontinuance of SMOW and PDB. Nature 375 , 285 (1995).

van Albada, S. J. & Robinson, P. A. Transformation of arbitrary distributions to the normal distribution with application to EEG test-retest reliability. J. Neurosci. Methods 161 , 205–211 (2007).

Article   PubMed   Google Scholar  

Emile-Geay, J. & Tingley, M. Inferring climate variability from nonlinear proxies: application to palaeo-ENSO studies. Clim. Past 12 , 31–50 (2016).

Barnes, D. J., Taylor, R. B. & Lough, J. M. On the inclusion of trace materials into massive coral skeletons. Part II: distortions in skeletal records of annual climate cycles due to growth processes. J. Exp. Mar. Biol. Ecol. 194 , 251–275 (1995).

Article   CAS   Google Scholar  

Gagan, M. K., Dunbar, G. B. & Suzuki, A. The effect of skeletal mass accumulation in Porites on coral Sr/Ca and δ 18 O paleothermometry. Paleoceanogr. Paleoclimatol. 27 , PA1203 (2012).

ADS   Google Scholar  

Schneider, T. Analysis of incomplete climate data: estimation of mean values and covariance matrices and imputation of missing values. J. Clim. 14 , 853–871 (2001).

PAGES 2k Consortium. Consistent multidecadal variability in global temperature reconstructions and simulations over the Common Era. Nat. Geosci. 12 , 643–649 (2019).

Cook, E. R., Briffa, K. R. & Jones, P. D. Spatial regression methods in dendroclimatology: a review and comparison of two techniques. Int. J. Climatol. 14 , 379–402 (1994).

Nash, J. E. & Sutcliffe, J. V. River flow forecasting through conceptual models part I − a discussion of principles. J. Hydrol. 10 , 282–290 (1970).

Otto-Bliesner, B. L. et al. Climate variability and change since 850 CE: an ensemble approach with the Community Earth System Model. Bull. Am. Meteorol. Soc. 97 , 735–754 (2016).

Evans, M. N., Kaplan, A. & Cane, M. A. Optimal sites for coral-based reconstruction of global sea surface temperature. Paleoceanogr. Paleoclimatol. 13 , 502–516 (1998).

Russon, T., Tudhope, A. W., Hegerl, G. C., Collins, M. & Tindall, J. Inter-annual tropical Pacific climate variability in an isotope-enabled CGCM: Implications for interpreting coral stable oxygen isotope records of ENSO. Clim. Past 9 , 1543–1557 (2013).

PAGES Hydro2k Consortium. Comparing proxy and model estimates of hydroclimate variability and change over the Common Era. Clim. Past 13 , 1851–1900 (2017).

Freund, M. B. et al. Higher frequency of Central Pacific El Niño events in recent decades relative to past centuries. Nat. Geosci. 12 , 450–455 (2019).

Gagan, M. K. et al. New views of tropical paleoclimates from corals. Quat. Sci. Rev. 19 , 45–64 (2000).

Thompson, D. M., Ault, T. R., Evans, M. N., Cole, J. E. & Emile-Geay, J. Comparison of observed and simulated tropical climate trends using a forward model of coral δ 18 O. Geophys. Res. Lett. 38 , L14706 (2011).

LeGrande, A. N. & Schmidt, G. A. Global gridded data set of the oxygen isotopic composition in seawater. Geophys. Res. Lett. 33 , L12604 (2006).

Reed, E. V., Thompson, D. M. & Anchukaitis, K. J. Coral-based sea surface salinity reconstructions and the role of observational uncertainties in inferred variability and trends. Paleoceanogr. Paleoclimatol. 37 , e2021PA004371 (2022).

Khaliq, M. N., Ouarda, T. B. M. J., Gachon, P., Sushama, L. & St-Hilaire, A. Identification of hydrological trends in the presence of serial and cross correlations: A review of selected methods and their application to annual flow regimes of Canadian rivers. J. Hydrol. 368 , 117–130 (2009).

Mahlstein, I., Hegerl, G. & Solomon, S. Emerging local warming signals in observational data. Geophys. Res. Lett. 39 , L21711 (2012).

Freeman, E. et al. ICOADS Release 3.0: a major update to the historical marine climate record. Int. J. Climatol. 37 , 2211–2232 (2017).

Huang, B. et al. Uncertainty estimates for sea surface temperature and land surface air temperature in NOAAGlobalTemp version 5. J. Clim. 33 , 1351–1379 (2020).

Druffel, E. R. M. & Griffin, S. Variability of surface ocean radiocarbon and stable isotopes in the southwestern Pacific. J. Geophys. Res. 104 , 23607–23613 (1999).

DeLong, K. L., Quinn, T. M., Taylor, F. W., Lin, K. & Shen, C.-C. Sea surface temperature variability in the southwest tropical Pacific since AD 1649. Nat. Clim. Change 2 , 799–804 (2012).

Quinn, T. et al. A multicentury stable isotope record from a New Caledonia coral: Interannual and decadal SST variability in the southwest Pacific since 1657. Paleoceanography 13 , 412–426 (1998).

Quinn, T. M., Crowley, T. J. & Taylor, F. W. New stable isotope results from a 173-year coral from Espiritu Santo, Vanuatu. Geophys. Res. Lett. 23 , 3413–3416 (1996).

Alibert, C. & Kinsley, L. A 170-year Sr/Ca and Ba/Ca coral record from the western Pacific warm pool: 1. What can we learn from an unusual coral record? J. Geophys. Res. Oceans 113 , C04008 (2008).

Tudhope, A. W. et al. Variability in the El Niño-Southern Oscillation through a glacial-interglacial cycle. Science 291 , 1511–1517 (2001).

Urban, F. E., Cole, J. E. & Overpeck, J. T. Influence of mean climate change on climate variability from a 155-year tropical Pacific coral record. Nature 407 , 989–993 (2000).

Guilderson, T. P. & Schrag, D. P. Reliability of coral isotope records from the western Pacific warm pool: A comparison using age-optimized records. Paleoceanography 14 , 457–464 (1999).

Quinn, T. M., Taylor, F. W. & Crowley, T. J. Coral-based climate variability in the Western Pacific Warm Pool since 1867. J. Geophys. Res. 111 , C11006 (2006).

Gorman, M. K. et al. A coral-based reconstruction of sea surface salinity at Sabine Bank, Vanuatu from 1842 to 2007 CE. Paleoceanography 27 , PA3226 (2012).

Bagnato, S., Linsley, B. K., Howe, S. S., Wellington, G. M. & Salinger, J. Coral oxygen isotope records of interdecadal climate variations in the South Pacific Convergence Zone region. Geochem. Geophys. Geosyst. 6 , Q06001 (2005).

Linsley, B. K. et al. Tracking the extent of the South Pacific Convergence Zone since the early 1600s. Geochem. Geophys. Geosyst. 7 , Q05003 (2006).

Cole, J. E., Fairbanks, R. G. & Shen, G. T. Recent variability in the Southern Oscillation: Isotopic results from a Tarawa Atoll coral. Science 260 , 1790–1793 (1993).

Dassié, E. P. et al. A Fiji multi-coral δ 18 O composite approach to obtaining a more accurate reconstruction of the last two-centuries of the ocean-climate variability in the South Pacific Convergence Zone region. Paleoceanography 29 , 1196–1213 (2014).

Carton, J. A., Chepurin, G. A. & Chen, L. SODA3: A new ocean climate reanalysis. J. Clim. 31 , 6967–6983 (2018).

Zuo, H., Balmaseda, M. A., Tietsche, S., Mogensen, K. & Mayer, M. The ECMWF operational ensemble reanalysis-analysis system for ocean and sea ice: A description of the system and assessment. Ocean Sci. 15 , 779–808 (2019).

Cheng, L. et al. Improved estimates of changes in upper ocean salinity and the hydrological cycle. J. Clim. 33 , 10357–10381 (2020).

Thompson, D. M. et al. Identifying hydro‐sensitive coral δ18O records for improved high‐resolution temperature and salinity reconstructions. Geophys. Res. Lett. 49 , e2021GL096153 (2022).

Wu, Y., Fallon, S. J., Cantin, N. E. & Lough, J. M. Assessing multiproxy approaches (Sr/Ca, U/Ca, Li/Mg, and B/Mg) to reconstruct sea surface temperature from coral skeletons throughout the Great Barrier Reef. Sci. Total Environ. 786 , 147393 (2021).

Sadler, J., Webb, G. E., Leonard, N. D., Nothdurft, L. D. & Clark, T. R. Reef core insights into mid-Holocene water temperatures of the southern Great Barrier Reef. Paleoceanography 31 , 1395–1408 (2016).

Roche, R. C. et al. Mid-Holocene sea surface conditions and riverine influence on the inshore Great Barrier Reef. Holocene 24 , 885–897 (2014).

Reed, E. V., Cole, J. E., Lough, J. M., Thompson, D. & Cantin, N. E. Linking climate variability and growth in coral skeletal records from the Great Barrier Reef. Coral Reefs 38 , 29–43 (2019).

Razak, T. B. et al. Use of skeletal Sr/Ca ratios to determine growth patterns in a branching coral Isopora palifera. Mar. Biol. 164 , 96 (2017).

Marshall, J. F. Decadal-scale, High Resolution Records of Sea Surface Temperature in the Eastern Indian and South Western Pacific Oceans from Proxy Records of the Strontium/calcium Ratio of Massive Porites Corals PhD thesis, Australian National Univ. (2000).

Marshall, J. F. & McCulloch, M. T. An assessment of the Sr/Ca ratio in shallow water hermatypic corals as a proxy for sea surface temperature. Geochim. Cosmochim. Acta 66 , 3263–3280 (2002).

Gagan, M. K. et al. Coral oxygen isotope evidence for recent groundwater fluxes to the Australian Great Barrier Reef. Geophys. Res. Lett. 29 , 43-1–43-4 (2002).

D’Olivo, J. P., Sinclair, D. J., Rankenburg, K. & McCulloch, M. T. A universal multi-trace element calibration for reconstructing sea surface temperatures from long-lived Porites corals: Removing ‘vital-effects’. Geochim. Cosmochim. Acta 239 , 109–135 (2018).

Fallon, S. J., McCulloch, M. T. & Alibert, C. Examining water temperature proxies in Porites corals from the Great Barrier Reef: a cross-shelf comparison. Coral Reefs 22 , 389–404 (2003).

Brenner, L. D., Linsley, B. K. & Potts, D. C. A modern Sr/Ca-δ 18 O-sea surface temperature calibration for Isopora corals on the Great Barrier Reef. Paleoceanography 32 , 182–194 (2017).

Alibert, C. et al. Source of trace element variability in Great Barrier Reef corals affected by the Burdekin flood plumes. Geochim. Cosmochim. Acta 67 , 231–246 (2003).

Murty, S. A. et al. Spatial and temporal robustness of Sr/Ca-SST calibrations in Red Sea corals: Evidence for influence of mean annual temperature on calibration slopes. Paleoceanogr. Paleoclimatol. 33 , 443–456 (2018).

Sayani, H. R., Cobb, K. M., DeLong, K., Hitt, N. T. & Druffel, E. R. M. Intercolony δ 18 O and Sr/Ca variability among Porites spp. corals at Palmyra Atoll: Toward more robust coral-based estimates of climate. Geochem. Geophys. Geosyst. 20 , 5270–5284 (2019).

Otto, F. E. L. Geert Jan van Oldenborgh 1961–2021. Nat. Clim. Chang. 11 , 1017 (2021).

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Acknowledgements

We acknowledge the originators of the coral data cited in Supplementary Tables 1 and 2 ; S. E. Perkins-Kirkpatrick and the deceased G. J. van Oldenborgh 105 for contributions to an earlier version of this manuscript; E. P. Dassié and J. Zinke for discussions and data; R. Neukom for advice on an earlier version of the reconstruction code; and B. Trewin and K. Braganza for advice about the Bureau of Meteorology GBR SST time series. B.J.H. and H.V.M. acknowledge support from an Australian Research Council (ARC) SRIEAS grant, Securing Antarctica’s Environmental Future (SR200100005), and ARC Discovery Project DP200100206. A.D.K. acknowledges support from an ARC DECRA (DE180100638) and the Australian government’s National Environmental Science Program. B.J.H. and A.D.K. acknowledge an affiliation with the ARC Centre of Excellence for Climate Extremes (CE170100023). H.V.M. acknowledges support from an ARC Future Fellowship (FT140100286). A.K.A. acknowledges support from an Australian government research training program scholarship and an AINSE postgraduate research award. Funding was provided to B.K.L. by the Vetlesen Foundation through a gift to the Lamont-Doherty Earth Observatory. Grants to B.K.L. enabled the generation of coral oxygen isotope and Sr/Ca data from Fiji that were used in our reconstruction (US National Science Foundation OCE-0318296 and ATM-9901649 and US National Oceanic and Atmospheric Administration NA96GP0406). We acknowledge the support of the NCI facility in Australia and the World Climate Research Programme’s working group on coupled modelling, which is responsible for CMIP. We thank the climate-modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provided coordinating support and led the development of software infrastructure in partnership with the Global Organisation for Earth System Science Portals.

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Benjamin J. Henley, Helen V. McGregor & Ariella K. Arzey

Securing Antarctica’s Environmental Future, University of Wollongong, Wollongong, New South Wales, Australia

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Janice M. Lough

ARC Centre of Excellence for Coral Reef Studies and School of Earth Sciences, University of Western Australia, Crawley, Western Australia, Australia

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Contributions

B.J.H., H.V.M. and A.D.K. conceived the study and developed the methodology. B.J.H. did most of the analysis. A.K.A. contributed analysis of modern coral data (Supplementary Information section  4.2 ). T.M.D. contributed analysis of instrumental data coverage (Supplementary Information section  1.2 ). B.K.L. contributed sub-annual coral data. B.J.H. and H.V.M. led the preparation of the manuscript, with contributions from A.D.K., O.H.-G., A.K.A., D.J.K., J.M.L., T.M.D. and B.K.L. Generative artificial intelligence was not used in any aspect of this study or manuscript.

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Henley, B.J., McGregor, H.V., King, A.D. et al. Highest ocean heat in four centuries places Great Barrier Reef in danger. Nature 632 , 320–326 (2024). https://doi.org/10.1038/s41586-024-07672-x

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Additive manufacturing of polymeric pressure die for rotary draw bending process

• ORIGINAL ARTICLE
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• Published: 09 August 2024

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• Muhammad Ali Kaleem   ORCID: orcid.org/0009-0005-1824-7380 1 ,
• Rainer Steinheimer 1 ,
• Peter Frohn-Sörensen 1 ,
• Steffen Gabsa 1 &
• Bernd Engel 1  

3D printing or additive manufacturing (AM) possesses enormous potential to benefit the manufacturing industry. Presently, rotary draw bending (RDB) is one of the most commonly used cold-forming industrial process for bending metal tubes. Pressure die is a fundamental forming tool in RDB processes, and it is conventionally made by various grades of comparatively expensive alloy steels. This research presents a novel design of a pressure die which can be 3D printed by using inexpensive polymeric filaments. In this research paper, the 3D-printed pressure die is named as “FFF-pressure die.” The material used to fabricate the FFF-pressure die is a thermoplastic polymer known as “ecoPLA.” The mechanical properties of ecoPLA are studied in relation to the process conditions of a RDB process. Firstly, an initial feasibility of using the FFF-pressure die in a RDB process is obtained by conducting a quick static stress analysis with actual process conditions. After initial feasibility, a complete RDB process is developed and simulated with actual process conditions and material properties. The FFF-pressure die is then practically fabricated by FFF 3D printer and experimentally tested on an industrial RDB machine. The results of practical experiments are compared with the simulation results. In order to make a comparison of the FFF-pressure die with the conventional metal pressure die, the simulation and practical process is also conducted with the conventional metal pressure die. A performance and cost comparison is made between the polymeric FFF-pressure die and the conventional metal pressure die. Von Mises stresses, contact forces, failure risk, and elastic deformations are analyzed. The advantages and limitations of using the FFF-pressure die in a RDB process are discussed in the end. This research intends to widen the avenue of using cost-effective and lightweight forming tools in metal forming industries.

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1 Introduction

Presently, 3D printing or additive manufacturing (AM) forms a significant segment of many manufacturing industries [ 1 ]. In AM, the layer-by-layer deposition of material offers immense possibilities to manufacture complex shapes with comparatively faster production times [ 2 ]. In the case of rotary draw bending (RDB), the process is predominantly executed by using forming tools. There are six fundamental forming tools in a RDB process, namely, bend die, clamp dies, pressure die, wiper die, mandrel, and collet. The positions of these tools are in the RDB process as shown in Fig.  1 [ 3 ]. Each forming tool holds a specific requirement of friction and surface hardness; for example, clamp dies require high friction for ensuring better grip and minimal sliding of the tube [ 4 ], pressure die requires less friction for easy sliding of tubes [ 5 ], and mandrel requires high hardness for ensuring better support and ovality [ 6 ]. The forming tools are mostly manufactured by conventional processes using tool steels or alloy steels. Currently, substantial research in the forming sector is directed towards the manufacturing of forming tools by AM. Tronvoll et al. demonstrated the use of 3D-printed hybrid mandrel for aluminum tubes [ 7 ]. He observed that the hybrid mandrel made from PLA and steel reduces wrinkling and cross-section flattening in bent tubes. Rotary draw bending possesses an intrinsic problem of axis stability. As soon as the forming tools in RDB are fixed with the machine, the central axis of the forming tools, tube, and mandrel are required to be aligned with each other. Borchmann et al. demonstrated that an increase in the axial displacement between the machine axis and the tool axis renders increased heights of wrinkles at the tube intrados [ 8 ]. If the axis of the tube and forming tools do not align exactly, the effective contact surfaces of the forming tools and the tube are significantly reduced [ 9 ]. Heftrich et al. highlighted the possibility of conducting the RDB process with limited contact surfaces of tools [ 10 ]. He demonstrated that reduced contact surfaces of a bend die provide desirable bending results in a RDB process.

Fundamental tool positions in RDB processes

It was recommended that a V-shaped tool will not only suffice the process requirements of a RDB process but will also provide enhanced flexibility of using a wide range of tube diameters. Pressure die is a fundamental forming tool in RDB processes because it provides counter support to bent tubes during bending operation [ 11 ]. Borchmann et al. demonstrated that pressure die clearance is a significant process parameter in RDB processes [ 12 ]. The material properties of forming tools also affect the process outcomes in a RDB process [ 13 ]. In addition to tool manufacturing, scientists are also contributing towards the quality enhancement of bent profiles and tubes. Li et al. demonstrated that the wrinkling in aluminum alloy tubes is reduced by placing a filler material in between tube layers [ 14 ]. Springback is an unavoidable effect in metal bending processes. Liu et al. demonstrated that the springback angle increases with an increase in the bending angle of 6063 extruded aluminum profiles [ 15 ]. Ha et al. devised a novel strategy to determine springback in bent tubes. He used the digital image-based laser tracking system to determine springback in RDB processes relevant to Industry 4.0 regimes [ 16 ]. The correct measurement of springback, wall thickness, and tube ovality is essentially important to construct an accurate FE-simulation model of the RDB process because practical measurements can validate the FE-simulation results.

AM possesses the potential to manufacture intricate shapes with engineered part properties [ 17 ]. That is why scientists are presently finding ways to develop tools by using AM techniques. From a material perspective, AM can be characterized into three broad categories: metal-based AM, ceramic-based AM, and polymer-based AM [ 18 ]. FDM (fused deposition modeling) or commonly known as FFF (fused filament fabrication) is a polymer-based AM technique [ 19 ]. The 3D printing of parts in FFF-based 3D printers is comparably faster as compared to metal-based 3D printers [ 20 ]. The strength of a FFF-fabricated part depends largely on the material properties of polymeric filament and printing conditions [ 21 ]. Complex parts fabricated through AM generally possess a support structure [ 22 ]. The support structures are intended to assist layer-by-layer deposition, thereby supporting the upper layers of the part in the desired geometry. The FFF technique provides options to fabricate parts with different patterns of infill [ 23 ]. The purpose of infill is generally to reduce weight and support the boundary walls by creating a pattern of internal walls within the part [ 24 ]. The infill density can vary from 0 to 100%. An infill density of 100% means a solid body [ 25 ]. In addition to infill, built orientation also affects the quality in terms of accuracy and surface finish of fabricated parts [ 26 ]. The parts can be fabricated in horizontal, vertical, or desired inclined angles. Wickramasinghe et al. showed that the most appropriate built orientation in FFF 3D printing depends mainly on geometric shape and support structures of the printed part [ 27 ]. Frohn-Sörensen et al. investigated the mechanical properties of commonly used polymeric materials suitable for FFF 3D printing [ 28 ]. He demonstrated that yield strength (under compression) of commercially available filaments of PLA ranges between 70 and 90 MPa for layer thicknesses between 0.1 and 0.3 mm. In the last couple of decades, many researchers have identified the economic advantages associated of polymeric materials. Kampker et al. highlighted the higher cost advantages of polymer additive manufacturing technologies as compared to metal-based manufacturing techniques [ 29 ]. Fuchs et al. highlighted the economic advantages of using lightweight polymeric materials in automobile manufacturing industries [ 30 ]. Kechagias and Chaidas discussed the impact of low-cost sustainable production of FFF-fabricated parts [ 31 ]. In a nutshell, low-cost and lightweight polymeric materials have recently gained the attention of any application-oriented researchers in the field of forming processes.

2 Objective

Lightweight and cost-effective tools are deemed critically important for modern manufacturing setups especially in factories where cobots are used to place and position the tools on manufacturing machines. This research aims to demonstrate the successful use of cost-effective and lightweight 3D-printed polymeric tools in metal bending processes. A fundamental forming tool (pressure die) used in rotary draw bending (RDB) processes is designed, developed, and tested in an industrial tube bending setup. A comparison is made between 3D-printed polymeric pressure die and its conventional metallic counterpart. The 3D-printed polymeric pressure die is named here as “FFF-pressure die.” Sects.  1 and 2 are introduction and objective. Section  3 highlights the design, development, and testing of the FFF-pressure die. In Sect.  4 , the results are presented. The performance and cost comparison is made between the FFF-pressure die and the metal pressure die. Section  5 discusses the advantages and limitations of using the FFF-pressure die in practical RDB processes. Section  6 presents the conclusion of this research paper. The schematic methodology of this research paper is shown in Fig.  2 .

Schematic diagram of the method of research

3.1 Parameterization of RDB process

A RDB process is conducted by specific process parameters. The wall factor (W) and bending factor (B) are two significant process parameters. These parameters are calculated by the following equations:

In addition to W and B , the tool geometry depends on the outer diameter of the tube. Presently, 22 mm tubes are widely used in household, construction, and aerospace industries [ 32 ]. For 22 mm tubes, the commonly applied values of W and B are W  = 22.0 and B  = 1.5. A correct value of the coefficient of friction of each forming tool is significantly important to accurately simulate the process. The friction coefficients of forming tools are slightly changed from their material value due to lubrication and polishing of tool surfaces. Kaleem et al. identified the accurate values of coefficients of friction of each forming tool used in RDB processes [ 33 ]. The parameterization of the RDB process used in this research paper is shown in Table  1 .

3.2 Design of polymeric FFF-pressure die

The polymer-made FFF-pressure die is designed according to the process parameterization of the RDB process. Conventionally, a pressure die consists of a semicircular surface which comes in contact with the tube. Literature review suggests that a V-shaped design with line contacts may provide enhanced flexibility to the process as the tool will be able to hold a wider range of tube diameters [ 10 ]. The circular circumference of conventional pressure dies is therefore replaced by a V-type shape. The V-shape is complemented with a bottom surface, i.e., two inclined surfaces and one straight surface. The inclined surfaces provide an enhanced flexibility to use tubes with diameters varying between a range of 22 ± 6 mm. Three bridge legs are formed to provide the springiness and damping effect to the tube. The bridge legs also offer enhanced flexibility of adjustment between the pressure die and the tube. Rectangular spaces are created at the sides and within to save the material. The hollow rectangular surfaces are interlinked with each other from the side and top surface so that circulation/flow of air is maintained within the pressure die during the bending operation. This restricts the rise of temperature in bridge legs of pressure die due to continuous flow of ambient air. The material in-between bridge legs and V-type shape has been kept thick enough to withstand the stresses applied by the tube during the bending operation. The bordering walls are also made thick enough to withstand plastic deformation. The base of the FFF-pressure die is fixed to the RDB machine by means of a central hole with a 10 mm central screw. The central hole caters for the difference in axial stiffness of the RDB machine in a rotational direction. The CAD design of the FFF-pressure die is created in a CAD modeling software AUTODESK INVENTOR. The CAD model of the FFF-pressure die is shown in Fig.  3 .

CAD model of FFF-pressure die

3.3 Material selection

The material selected to 3D print FFF-pressure die is a thermoplastic polymer (PLA) commercially known as “ecoPLA-Black.” The material is provided in the form of filament rolls by a private company 3DJAKE GmbH [ 34 ]. EcoPLA is a polymeric material suitable for 3D printing via the FFF (fused filament fabrication) technique. The material properties of ecoPLA are mentioned in Table  2 . In order to verify the anisotropic behavior of ecoPLA, an investigation is done according to the German organization of standardization DIN-604. Three cylindrical samples with dimensions of 20 × 30 mm (diameter × length) are FFF 3D printed in horizontal and vertical directions. The directions correspond to the x/y coordinates parallel to the printer bed (horizontal) and the z-coordinate in the build direction (vertical). For 3D printing, a Prusa-type MK4 machine is used. The print parameters used for fabrication are mentioned in Table  2 . After printing, the yield strength (in compression) of each sample is obtained by a universal tensile tester. The yield strength of horizontally and vertically printed samples is shown in Fig.  4 . Although the difference between horizontal and vertical samples is not significantly large yet, the material is categorized to present an anisotropic behavior. Here, the FFF-pressure die is planned to be 3D printed in a vertical direction; therefore, the yield strength of ecoPLA in a vertical plane (77.2 MPa) is considered. In order to keep the margin of safety, a rounded-off lower value of yield (i.e., 70 MPa) is considered in this research. The material of other forming tools is the standard alloy steel and hard-plated chrome steels, and the material of the tube is austenitic chromium-nickel stainless steel, AISI 304 (1.4301), or X5CrNi18-10. Tool materials with respective material properties are mentioned in Table  3 .

Experimentally obtained stress–strain curve and anisotropic behavior of ecoPLA

3.4 Initial feasibility analysis

A complete FE simulation of a RDB process with tool materials simulated as volume elements takes approximately 8–10 h of processing time. Therefore, before conducting a detailed process simulation, an initial feasibility check of the designed FFF-pressure die is conducted in a CAD modeling software AUTODESK INVENTOR. The initial feasibility is conducted in less than 20 min after applying actual process conditions, loads, and process constraints in static analysis mode. Based on the initial feasibility analysis, the design (CAD) of the FFF-pressured die can be modified by increasing the material at bridge legs or walls. The meshing of the CAD model is done by an inbuilt plugin feature of auto-mesh which generates small mesh sizes at the corners and comparably larger mesh sizes at straight surfaces. The function of “slide and fit” is enabled for in-contact surfaces between the tube and FFF-pressure die. The material properties of ecoPLA (yield strength, ultimate tensile strength, Poisson’s ratio, Young's modulus, and density) are fed to the software. The CAD model of the FFF-pressure die is a solid object, so the software-fed value of the density should correspond to the actual material density of ecoPLA (1.24 g/cm 3 ). A Poisson’s ratio of 0.35 for ecoPLA is used. The static analysis results of initial feasibility are shown in Fig.  5 . The maximum von Mises stress is 45.89 MPa. The obtained von Mises stress is compared with the yield strength of the material, and it is noticed that the von Mises stress experienced by the CAD model is significantly less than the yield strength of ecoPLA (70 MPa). The distortion energy theory, also known as the von Mises criterion, predicts that a material is expected to fail if the maximum von Mises stress surpasses the yield strength of the material [ 35 ]. In order to apply the distortion energy theory, the direction of forces applied to obtain the von Mises stress and the direction of material yield must lie in the same plane [ 36 ]. Here, the forces applied by a tube on a pressure die are directed in the same direction as the direction of material yield (i.e., vertical plane). The distortion energy theory suggests that the proposed design of the FFF-pressure die can safely withstand the load exerted by the tube during bending operation because the maximum von Mises stress is significantly less than the yield strength of ecoPLA (i.e., 45.89 MPa < 70 MPa). This analysis is only valid for the case in which the FFF-pressure die is 3D printed in the vertical direction. The vertical direction of printing means that the FFF-pressure die is built from bottom to top with deposited layers aligned with each other in a horizontal direction. The initial feasibility analysis provides a broader guideline that the proposed design of the FFF-pressure die can withstand the applied stresses during the process or the design should be altered by adding more material at bridge legs.

Initial feasibility check of designed FFF-pressure die

3.5 3D printing of FFF-pressure die

The FFF-pressure die is physically 3D-printed by a commercially available MK-4 FDM Printer by PRUSA Research Corporation. The material properties of ecoPLA and selected printing parameters of the FDM 3D printer are shown in Table  2 . The infill density is kept at 100% so as to correspond to actual material density. The print direction is vertical [ 37 ]. The support structures in hollow spaces are removed after the print. The practically fabricated FFF-pressure die is shown in Fig.  6 .

a FFF 3D printing in vertical plane highlighting sequential deposition of layers from bottom surfaces to top surfaces and b 3D-printed FFF-pressure

3.6 FE-simulation model of RDB process

The surfaces of tools in the RDB process are in-contact with the tube, and the position of the tools changes with a change in bending angle [ 10 ]. Therefore, the contact surface pressures and tool deformations cannot be measured during the bending process by physical measuring instruments. FE simulations are mainly used to predict surface stresses and deformations. The accuracy of a correct FE-simulation model therefore possesses a paramount importance in a RDB process. The CAD model of the FFF-pressure die is meshed with a mesh size of 1.00 mm and imported in the FE solver software PAMSTAMP. The process model is created and simulated in the tube-forming environment of PAMSTAMP. Volume elements are used to simulate the material response of tools [ 12 ]. The tube is created as a blank element comprising of shell elements. The material properties of the tube, metallic tools, and FFF-pressure die are fed to the software. The process conditions, coefficients of friction, and geometric data are added as pre-processing boundary conditions. The simulation is first carried out by a conventional metal pressure die, and the results are analyzed. Then, the metal pressure die is replaced by the FFF-pressure die, and the results are obtained again. The process model of the RDB process with metallic pressure die and FFF-pressure die is shown in Fig.  7 . The process parameters and tool properties are mentioned in Tables 1 and 3 , respectively.

Parametrized 3-dimensional FE-simulation model of RDB process with tool material properties and resultant bent tubes. Model with a FFF-pressure die and b metal pressure die

3.7 Practical experiments and accuracy of FE-simulation model

After obtaining FE-simulation results, the RDB process is practically conducted on an industrial machine by WAFIOS. The process is first conducted by using the metallic pressure die (conventional pressure die). Then, the same process is conducted by replacing the metallic pressure die with the FFF-pressure die. The geometrical configurations, dimensional alignments, and other tools are kept the same in both operations. The process parameters used for FE simulation and practical experiment are kept identical. Three tubes are bent in each operation. All bent tubes showed excellent consistency without any noticeable wrinkling. The experimental setup is shown in Fig.  8 .

Experimental setup of rotary draw bending process with installed FFF-pressure die

In order to ascertain the accuracy of the FE-simulation model, the quality characteristics of practically bent tubes are compared with simulated results. The wall thicknesses at intrados and extrados, ovality, wrinkling, and springback are compared [ 33 ]. The springback of the bent tubes is measured by a digital bent angle measuring device (AM-75) by Winton Corporation, and the ovality is measured by a digital measurement indicator from Mitutoyo Corporation. A significantly high level of agreement is established between the FE simulation and practical results. No wrinkling is noticed in both cases. A slight difference is observed in ovality and wall thickness at the intrados. This difference is insignificant because the same difference is observed in both cases (i.e., RDB process with metal pressure die (right) and FFF-pressure die (left). A springback of almost 3.5° is observed in both cases. The springback is an unavoidable characteristic which occurs due to the microstructural response of tube material. The comparison of actual and simulated results is shown in Fig.  9 .

Accuracy of FE-simulation model by comparison with practical experiments

4.1 Performance results

4.1.1 von mises stresses.

The von Mises stresses in the FFF-pressure die are comparatively less when compared to the metal-made pressure die. This is because of the low stiffness of polymeric material (PLA) in the FFF-pressure die. The polymeric pressure die is elastically deformed during the bending process, and as a result, comparatively low stresses are manifested. On the other hand, a metal-made pressure die is significantly stiff and offers higher reaction forces to deformation which results in manifestation of higher stresses. From Fig.  10 , it can be seen that the maximum VM stress becomes constant at approximately 140 MPa in the case of the metal pressure die and approximately 60 MPa for the FFF-pressure die. The effect of stresses is further discussed in sub-Sect.  4.1.3 (Failure Risk).

Maximum von Mises stresses in FFF-pressure die and metal pressure die

4.1.2 Elastic deformation

The FFF-pressure die is elastically deformed in both horizontal and vertical directions. A maximum horizontal compressive deformation of 0.036 mm and a maximum vertical compressive deformation of 0.060 mm are manifested at the surface of bridge legs of the FFF-pressure die. The deformation changes with a change in bending angle (α). As soon as the bending operation is completed, the surface of the FFF-pressure die regains its normal position. The changing elastic deformations with an increase in bending angle are shown in Fig.  11 . Plastic deformation is neither noticed in the practically built 3D-printed FFF-pressure die nor manifested in the FE-simulation model. The metal pressure die almost remained undeformed.

Elastic deformation in FFF-pressure die and metal pressure die

4.1.3 Failure risk

The failure risk of objects under loads is determined by the Forming Limit Diagram (FLD) [ 38 ]. In the case of tools, the failure is manifested in the form of rupture or cracks. A closeness to failure limit shows higher failure risk and vice versa. The failure risk of the metal pressure die and the FFF-pressure die is shown in Fig.  12 . Here, the marked spots show the maximum equivalent stress exhibited by each meshed volume element of the pressure die. The FFF-pressure die shows a significantly high failure risk because the stresses are fairly close to the failure limit. On the other hand, in the case of metal pressure die, the stresses are localized in one particular area which is significantly distant from the failure limit. Hence, the metal pressure die is less prone to failure as compared to the FFF-pressure die. Although both pressure dies did not fail in the understudy RDB process, it is realized that in the case of RDB processes requiring high tool stresses, the polymeric pressure die is expected to fail during the bending process.

Failure risk in metal pressure die (left) and FFF-pressure die (right)

After the practical experiment, thin lines are seen at the contact surfaces of the FFF-pressure die. These lines are a sign of expected wear in the polymer (PLA). In polymers, the wear is typically measured by electron spectroscopy techniques [ 39 ]. The quantified measurement of wear rate is a complex technique requiring multiple physical measurement operations. However in RDB processes, the tube is continuously in contact with the tube; therefore, in-process wear measurement by physical techniques is prone to generate errors. In the case of practical bending operation with the FFF-pressure die, thin inconsistent lines can be visualized by the naked eye. These lines are visualized at the in-contact tool surfaces of the FE-simulation model as shown in Fig.  13 . Hence, it is deducted that wear has manifested in the FFF-pressure die; however, its quantification is not deemed essential in this research paper. Ashby et al. have shown that 3D-printed samples of PLA exhibit a wear of almost 0.2 mm after 1.0 × 10 5 cycles of rotary operations [ 40 ]. The wear results depend on multiple factors such as applied load, process effects, 3D print properties, and environmental conditions. In this research paper, keeping in view the manifestation of wear lines on surfaces of the FFF-pressure die, it is recommended that the polymeric tools are only suitable for small batch size productions.

Manifestation of wear lines on surfaces of FFF-pressure die

4.1.4 Flexibility

The V-shaped geometry of the FFF-pressure die can hold a wide range of tube diameters. The presented RDB process is conducted on a 22 mm tube diameter. In order to investigate the performance of the FFF-pressure die with different tube diameters, the FE-simulation of the process is conducted with a larger tube diameter of 28 mm and a smaller tube diameter of 16 mm. The process results of the 16 mm tube are similar to the process results of the 22 mm tube. Although a strong wrinkling trend emerged at the intrados, yet no wrinkling is visualized in 16 mm and 22 mm tubes. On the other hand, wrinkling and cracks are witnessed in 28 mm tube. The cracks are formed at the extrados as shown in Fig.  14 . This shows that the contact pressure variations and resultant sinusoidal oscillations in the FFF-pressure die (in the case of 28 mm tube) are large enough to produce wrinkling and cracking in the tube (see Fig.  15 ). At the end of the bending process, an almost equal value of springback (≈ 3.5°) is manifested in all three tube diameters.

Use of different diameter tubes with FFF-pressure die

Contact pressure variation on the surface of the FFF-pressure die and the metal pressure die

As opposed to conventional pressure die in which the complete surface of the pressure die remains in contact with the tube, the V-shaped FFF-pressure die maintains only a line contact. The comparison of contact normal pressures on the surface of the metal pressure die and the FFF-pressure die is shown in Fig.  15 . It can be seen that the line contact in the FFF-pressure die produces a sinusoidally changing pattern of maximum surface pressures with an increase in bending angle. In the case of metal pressure die, the maximum surface pressure remains almost constant throughout the bending operation. The large variation in surface pressures during a bending operation is not a desirable feature in bending processes as it may initiate oscillations in the tool. For the presented process model, the line contact does not affect the quality of bent tubes; however, for larger diameter tubes (e.g., tube diameter ≥ 28 mm), the polymeric tools providing line contact are not considered feasible because they tend to generate excessively large surface pressure variations.

4.2 Cost-effectiveness

The weight, volume, and geometric dimensions of the FFF-pressure die and the metal pressure die (conventional) are mentioned in Table  4 . The Ashby material selection charts are widely used to conduct cost comparison of designed parts made from different materials [ 40 ]. The Ashby cost performance indexes of the FFF-pressure die and the metal pressure die are also presented in Table  4 . A higher cost performance index shows an enhanced lightweight response of the material and vice versa [ 41 ]. The cost per part is obtained by considering the geometric volume and weight of the tools. Only the material costs are considered.

5 Discussions

The performance comparison of the metal pressure die and the FFF-pressure die is conducted in terms of experienced stresses, deformations, failure risk, and flexibility offered to the process. In the case of stresses, the FFF-pressure die manifests lower von Mises stresses as compared to the metallic pressure die. This is because polymeric materials are elastically deformable as compared to highly stiff metals. The elastic deformation in the FFF-pressure die is noted to be considerably high whereas the metal pressure die is almost undeformed. FLD diagrams show that in both cases, the process is conducted safely, and pressure dies did not fail during the bending operation. This failure risk provided by FE simulation is validated by practical experiments as no defect (crack or rupture) is noticed in the FFF-pressure die after practical bending operations. However, FE simulations show that the failure risk of the FFF-pressure die is significantly high as compared to the metal pressure die. This means that for large bending operations requiring high stresses on pressure die, the polymer-made pressure dies are not considered feasible for use. The V-shaped design offers more flexibility; therefore, the FFF-pressure die is tested with comparatively larger and smaller diameters. The smaller tube (diameter = 16 mm) conducted the operation safely whereas the bigger tube (diameter = 28 mm) produced wrinkled tubes. In addition to wrinkling, cracking is also observed in the larger tubes. Hence, it is deduced that the FFF-pressure die can only conduct the bending operation for tubes having diameters ≤ 22 mm. For larger bending operations, the design of a polymeric pressure die must be engineered according to process parameterization and material properties.

In a typical RDB process, the contact forces of the pressure die are greater than the combined contact forces of the mandrel and wiper die [ 42 ]. This means that the pressure die has effectively withstood the tangential forces applied by the tube and reciprocated these tangential forces to the mandrel and wiper die. In this study, the contact force graph validates that the FFF-pressure die has effectively counteracted the contact forces of the mandrel and wiper die as shown in Fig.  16 . Only in the first 10 degrees, the contact force of the wiper die is greater than the contact force of FFF-pressure die because the tools adjust with a tube in the beginning of the process. This validation may serve as a quick-check solution for manufacturers working in the industry. The visualization of contact forces on pressure die surfaces will tell us that the polymeric pressure die is feasible for the RDB process or otherwise. Here, the following advantages are obtained by the use of a 3D-printed polymeric pressure die in a RDB process:

The cost of polymeric materials is significantly less than the cost of tool steel.

The pressure die is 3D printed by the FFF printer within 3 h. For smaller batch sizes, the manufacturing time of a polymeric pressure die is substantially less than the manufacturing time of conventional pressure dies made from alloy steel.

The weight of polymeric tools is significantly less than the weight of metallic tools. Hence, cobots can effectively position the tools on machines.

No post-processing or surface treatment is required.

A complex design possessing damping (springiness) effect is possible.

Substantial tool material can be saved by selecting an appropriate design and topology optimization.

In RDB processes, the machine axis may not coincide with the axis of forming tools (bend die, pressure die, and clamp dies). Owing to robust stiffness of the machines and substantial stiffness of forming tools, this difference in machine and tool axis, known as axial stiffness, can result in significant defects during bending. The FFF-pressure die is deemed to reduce the effect of axial stiffness by providing small elastic deformations offered by the polymeric material.

Contact forces of FFF-pressure die (blue), mandrel (red), and wiper die (black) obtained from FE simulation of the RDB process

Here, the feasibility of using the FFF-pressure die is only investigated for one RDB process with specific process conditions ( B  = 1.5, W  = 22). For all other RDB processes, an engineered feasibility analysis should be conducted before using the polymeric pressure die. The feasibility analysis will depend on the following aspects:

Before the development of the detailed process model and conducting FE simulation with volume elements which may take almost 8–10 h, an initial feasibility of the tool use should be obtained with actual process conditions and static loads. The initial feasibility may not be 100% accurate, but it provides a rough guideline to model and modify the CAD geometry. Material failure theory (distortion energy theory) can be applied with actual process conditions obtained from literature review of RDB processes. In this research paper, the initial feasibility of the FFF-pressure die is carried out in less than 20 min.

The material failure criterion (distortion energy theory) should not be considered as a stand-alone solution for predicting tool failure. An engineered FE-simulation model of the RDB must be constructed according to process parameterization. The accuracy of the FE-simulation model must be verified by practical experiments. Finally, the 3D-printed pressure die made from polymeric material must be tested practically under actual conditions before industrial production.

Print direction in FFF 3D printer should be selected according to in-plane material properties of the polymer.

Infill density should be 100% so that the material represents a solid body with the same density as that of actual polymeric material. For infill densities less than 100%, the Ashby–Gibson model is necessitated during stress calculations.

The design of the pressure die should allow easy removal of support structures.

6 Conclusion

Presently, RDB processes are conducted by forming tools made from metals and alloy steels. Pressure die is a fundamental forming tool in RDB processes which is used to counteract the tangential forces during bending operations. This research paper demonstrates the development of a polymeric pressure die through an additive manufacturing process and the subsequent testing of a polymeric pressure die in a RDB process. A unique design of the 3D-printed polymeric pressure die, herein called as the FFF-pressure die, is proposed. Before using the FFF-pressure die, an initial feasibility analysis is conducted by using actual process conditions and static loads. The initial feasibility is conducted in the software AUTODESK INVENTOR in which it was demonstrated that the CAD model of the FFF-pressure die is feasible for use in the RDB process. The initial feasibility is carried out in less than 20 min. The FFF-pressure die is practically 3D printed by a FFF printer using PLA thermoplastic polymer filaments. A comprehensive model of the RDB process is created in the software PAMSTAMP with forming tools made from volume elements. The CAD model of the FFF-pressure die is imported in PAMSTAMP, and the FE simulation of the complete RDB process is conducted. In order to compare the performance of the FFF-pressure die with the conventional metallic pressure die, the FE simulation is also conducted with metal pressure die. The RDB process is then conducted practically on an industrial RDB machine. The practical process rendered defect-free tubes without any tool failure. The accuracy of FE simulations is verified by the results obtained from the practically conducted process. The comparison of the FFF-pressure die with the metal pressure die provided the following conclusions:

The stresses, contact forces, and failure analysis indicate that the FFF-pressure die made from a polymeric material (PLA) is able to conduct the selected RDB process. In this research paper, the engineered design of the FFF-pressure die is able to bend metal tubes made from stainless steel up to a maximum outer diameter of 22 mm. However, for large RDB processes with higher values of W and B, the polymeric tools are not recommended to be used. In each case, an engineered design is required to be developed by integrating process parameters in the design process.

The cost of the FFF-pressure die is significantly less as compared to the metal-made pressure die. In this research, the material cost of one (conventional) metal pressure die is equal to the cost of 12 polymer-made FFF-pressure dies. The cost comparison is indicated by the Ashby cost performance index. The cost performance index of the FFF-pressure die is significantly high as compared to the metal pressure die. (FFF-pressure die = 1.95 and metal pressure die = 0.206).

Due to low stiffness, polymeric tools tend to deform with an application of loads. An engineered design makes it possible that the deformation remains within elastic limits. In this paper, the FFF-pressure die made from PLA is elastically deformed in both horizontal and vertical directions. A total deformation of 0.12 mm is observed. On the other hand, metal-made pressure die remains almost undeformed.

The weight of the FFF-pressure die is substantially less as compared to the metal pressure die (FFF-pressure die = 0.35 kg and metal pressure die = 3.32 kg). In modern manufacturing regimes, lightweight tools are significantly important because cobots can position the tools on the machine without human intervention.

In the next phase of this research, the RDB process will be tested with polymeric bend die and clamp dies, and a “ Process Window ” will be identified in which the limits of process conditions (bending factor, wall thickness, and tube diameter) will be derived for additively manufactured polymeric forming tools. The possibility of AI-based design and automated additive manufacturing of customized pressure dies within the framework of Industry 4.0 will also be investigated at later stages.

Data availability

The corresponding author declares that the experimental data and the simulation results that support the findings of this study are available within the paper. The complete simulation results are available with the corresponding author and can be obtained on request via email.

Gibson I, Rosen D, Stucker B, Khorasani M, Rosen D, Stucker B, Khorasani M (2021) Additive manufacturing technologies, vol 17. Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-030-56127-7

Book   Google Scholar  

Prakash, K. S., Nancharaih, T., & Rao, V. S. (2018). Additive manufacturing techniques in manufacturing-an overview. Materials Today: Proceedings, 5(2), 3873–3882; https://doi.org/10.1016/j.matpr.2017.11.642

Strano M (2005) Automatic tooling design for rotary draw bending of tubes. Int J Adv Manuf Technol 26:733–740. https://doi.org/10.1007/s00170-003-2055-6

Article   Google Scholar  

Yang H, Li H, Zhan M (2010) Friction role in bending behaviors of thin-walled tube in rotary-draw-bending under small bending radii. J Mater Process Technol, 210(15), 2273–2284; https://doi.org/10.1016/j.jmatprotec.2010.08.021

Masoumi H, Mirbagheri Y, Jafari NR, Salem M, Kalantari M (2012) Effect of mandrel, its clearance and pressure die on tube bending process via rotary draw bending method.

Salem M, Farzin M, Kadkhodaei M, Nakhaei M (2015) A chain link mandrel for rotary draw bending: experimental and finite element study of operation. Int J Adv Manuf Technol 79:1071–1080. https://doi.org/10.1007/s00170-015-6910-z

Tronvoll S A, Treffen H, Ma J, Welo T (2023) Low-cost tooling concept for customized tube bending by the use of additive manufacturing. © Materials Research Forum; https://doi.org/10.21741/9781644902479-106

Borchmann L, Heftrich C, Engel B (2020) Influence of the stiffness of machine axes on the formation of wrinkles during rotary draw bending. SN Applied Sciences 2:1–13. https://doi.org/10.1007/s42452-020-03419-1

Tronvoll SA, Ma J, Welo T (2023) Deformation behavior in tube bending: a comparative study of compression bending and rotary draw bending. Int J Adv Manuf Technol, 124(3–4), 801–816; https://doi.org/10.1007/s00170-022-10433-7

Heftrich, C., Steinheimer, R., & Engel, B. (2018). Rotary-draw-bending using tools with reduced geometries. Procedia Manufacturing, 15, page 805; https://doi.org/10.1016/j.promfg.2018.07.410

Simonetto E, Ghiotti A, Bruschi S (2021) In-process measurement of springback in tube rotary draw bending. Int J Adv Manuf Technol 112:2485–2496. https://doi.org/10.1007/s00170-020-06453-w

Borchmann L, Kuhnhen C, Frohn P, Engel B (2019) Sensitivity analysis of the rotary draw bending process as a database of digital equipping support. Procedia Manufacturing 29:592–599. https://doi.org/10.1016/j.promfg.2019.02.100

Berger C, Scheerer H, Ellermeier J (2010) Modern materials for forming and cutting tools–overview. Materialwissenschaft und Werkstofftechnik, 41(1), 5–16; https://doi.org/10.1002/mawe.200900529

Sun H, Li H, Gong F, Liu Y, Li G, Fu M (2022) Filler parameters affected wrinkling behavior of aluminum alloy double-layered gap tube in rotary draw bending process. Int J Adv Manuf Technol, 1–16

Liu Z, Li L, Wang G, Chen J, Yi J (2020) Springback behaviors of extruded 6063 aluminum profile in subsequent multi-stage manufacturing processes. Int J Adv Manuf Technol 109:1–13

Ha T, Welo T, Ringen G, Wang J (2021) A strategy for on-machine springback measurement in rotary draw bending using digital image-based laser tracking. Int J Adv Manuf Technol, 1–14

Liu G, Zhang X, Chen X, He, Y, Cheng L, Huo M, ... & Lu, J. (2021). Additive manufacturing of structural materials. Mater Sci Eng: R: Reports, 145, 100596; https://doi.org/10.1016/j.mser.2020.100596

Bourell D, Kruth JP, Leu M, Levy G, Rosen D, Beese AM, Clare A (2017) Materials for additive manufacturing. CIRP annals, 66(2), 659–681; https://doi.org/10.1016/j.cirp.2017.05.009

Cano-Vicent A, Tambuwala MM, Hassan SS, Barh D, Aljabali AA, Birkett M, ... Serrano-Aroca Á (2021) Fused deposition modelling: current status, methodology, applications and future prospects. Additive Manufacturing, 47, 102378; https://doi.org/10.1016/j.addma.2021.102378

Giri J, Chiwande A, Gupta Y, Mahatme C, Giri P (2021) Effect of process parameters on mechanical properties of 3D printed samples using FDM process. Mater Today: Proceed 47:5856–5861. https://doi.org/10.1016/j.matpr.2021.04.283

Doshi M, Mahale A, Singh SK, Deshmukh S (2022) Printing parameters and materials affecting mechanical properties of FDM-3D printed parts: perspective and prospects. Mater Today: Proceed 50:2269–2275. https://doi.org/10.1016/j.matpr.2021.10.003

Jiang J, Xu X, Stringer J (2018) Support structures for additive manufacturing: a review. J Manuf Mater Process, 2(4), 64; https://doi.org/10.3390/jmmp2040064

Baich L, Manogharan G, Marie H (2015) Study of infill print design on production cost-time of 3D printed ABS parts. Int J Rapid Manuf, 5(3–4), 308–319; https://doi.org/10.1504/ijrapidm.2015.074809

Birosz MT, Ledenyak D, Ando M (2022) Effect of FDM infill patterns on mechanical properties. Polymer Testing, 113, 107654; https://doi.org/10.1016/j.polymertesting.2022.107654

https://www.wevolver.com/article/infill-3d-printing-all-you-need-to-know . Last accessed: 05 Mar 2024

Taufik M, & Jain PK (2013) Role of build orientation in layered manufacturing: a review. Int J Adv Manuf Technol and Manag, 27(1–3), 47–73; https://doi.org/10.1504/ijmtm.2013.058637

Wickramasinghe S, Do T, & Tran P (2020) FDM-based 3D printing of polymer and associated composite: a review on mechanical properties, defects and treatments. Polymers, 12(7), 1529; https://doi.org/10.3390/polym12071529

Frohn-Sörensen P, Geueke M, Engel B, Löffler B, Bickendorf P, Asimi A, ... & Schuh G (2022). Design for 3D printed tools: mechanical material properties for direct polymer additive tooling. Polymers, 14(9), 1694; https://doi.org/10.3390/polym14091694

Kampker A, Triebs J, Kawollek S, Ayvaz P, & Beyer T (2019) Direct polymer additive tooling–effect of additive manufactured polymer tools on part material properties for injection moulding. Rapid Prototyping J, 25(10), 1575–1584; https://doi.org/10.1108/rpj-07-2018-0161

Fuchs ER, Field FR, Roth R, & Kirchain RE (2008) Strategic materials selection in the automobile body: economic opportunities for polymer composite design. Composites Sci Technol, 68(9), 1989–2002; https://doi.org/10.1016/j.compscitech.2008.01.015

Kechagias J, & Chaidas D (2023) Fused filament fabrication parameter adjustments for sustainable 3D printing. Mater Manuf Process, 38(8), 933–940; https://doi.org/10.1080/10426914.2023.2176872

https://www.easycomposites.eu/22mm-woven-finish-carbon-fibre-tube . Last Access : 4 July 2024

Kaleem MA, Steinheimer R, Frohn-Sörensen P, Kotzian T, & Engel B (2024) Topology optimization of forming tools: pressure die in rotary draw bending process. Int J Interact Design Manuf (IJIDeM), 1–14

https://www.3djake.com/3djake/ecopla-black . Last accessed : 06 Mar 2024

J Polak 1991 Cyclic plasticity and low cycle fatigue life of metals Elsevier Amsterdam 123 9780444988393

https://www.simscale.com/docs/simwiki/fea-finite-element-analysis/what-is-von-mises-stress . Last accessed : 06 Mar 2024

Zohdi N, & Yang R (2021) Material anisotropy in additively manufactured polymers and polymer composites: a review. Polymers, 13(19), 3368; https://doi.org/10.3390/polym13193368

Hasan RZ, Kinsey BL, & Tsukrov I (2011) Effect of element types on failure prediction using a stress-based forming limit curve

Schappo H, Gindri IM, Cubillos PO, Maru MM, Salmoria GV, Roesler CR (2018) Scanning electron microscopy and energy-dispersive X-ray spectroscopy as a valuable tool to investigate the ultra-high-molecular-weight polyethylene wear mechanisms and debris in Hip implants. J Arthroplasty 33(1):258–262

Ashby MF (1997) Material property charts. In  Materials Selection and Design  (pp. 266–280). ASM international

Ashby MF (2012) Materials and the environment: eco-informed material choice. Elsevier

Google Scholar  

Borchmann L, Frohn-Sörensen P, Engel B (2020) In situ detection and control of wrinkle formation during rotary draw bending. Procedia Manufacturing 50:589–596. https://doi.org/10.1016/j.promfg.2020.08.106

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The authors are thankful to DAAD (Deutscher Akademischer Austauschdienst)–Germany and the Institute of Forming Technology, UTS-Siegen for providing the funding and resources to conduct this study.

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Kaleem, M.A., Steinheimer, R., Frohn-Sörensen, P. et al. Additive manufacturing of polymeric pressure die for rotary draw bending process. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-14221-3

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JSmol Viewer

A compendium of research, tools, structural analysis, and design for bamboo structures.

1. Introduction

2. methodology.

Click here to enlarge figure

3. Results and Discussion

3.1. bamboo species.

3.2. Bamboo Structures

3.3. codes and standards for structural analysis and design of bamboo structures.

3.4. Software Packages for Structural Analysis of Bamboo Structures

3.5. Adopted Methodologies

3.5.1. material parameters, 3.5.2. load parameters, 3.6. research gaps and challenges, 3.6.1. material properties, 3.6.2. structural analysis and design, 4. conclusions, author contributions, data availability statement, acknowledgments, conflicts of interest.

• Raftery, A.E.; Alkema, L.; Gerland, P. Bayesian Population Projections for the United Nations. Stat. Sci. 2014 , 29 , 419. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• United Nations Population Fund. State of World Population 2023: 8 Billion Lives, Infinite Possibilities: The Case for Rights and Choices ; State of World Population; United Nations: New York, NY, USA, 2023; ISBN 978-92-1-002713-7. [ Google Scholar ]
• Watari, T.; Cao, Z.; Serrenho, A.C.; Cullen, J. Growing Role of Concrete in Sand and Climate Crises. iScience 2023 , 26 , 106782. [ Google Scholar ] [ CrossRef ]
• Wu, W.; Liu, Q.; Zhu, Z.; Shen, Y. Managing Bamboo for Carbon Sequestration, Bamboo Stem and Bamboo Shoots. Small-Scale For. 2015 , 14 , 233–243. [ Google Scholar ] [ CrossRef ]
• Cho, E.; Um, Y.; Yoo, S.K.; Lee, H.; Kim, H.B.; Koh, S.; Shin, H.C.; Lee, Y. An Expressed Sequence Tag Analysis for the Fast-Growing Shoots of Bambusa Edulis Murno. J. Plant Biol. 2011 , 54 , 402–408. [ Google Scholar ] [ CrossRef ]
• Bredenoord, J. Bamboo as a Sustainable Building Material for Innovative, Low-Cost Housing Construction. Sustainability 2024 , 16 , 2347. [ Google Scholar ] [ CrossRef ]
• Ahmad, Z.; Upadhyay, A.; Ding, Y.; Emamverdian, A.; Shahzad, A. Bamboo: Origin, Habitat, Distributions and Global Prospective. In Biotechnological Advances in Bamboo ; Ahmad, Z., Ding, Y., Shahzad, A., Eds.; Springer: Singapore, 2021; pp. 1–31. ISBN 9789811613098. [ Google Scholar ]
• Madhushan, S.; Buddika, H.A.D.; Bandara, S.; Navaratnam, S.; Abeysuriya, N. Uses of Bamboo for Sustainable Construction-A Structural and Durability Perspective—A Review. Sustainability 2023 , 15 , 11137. [ Google Scholar ] [ CrossRef ]
• Hailemariam, L.M.; Amede, E.A.; Hailemariam, E.K.; Nuramo, D.A. Philosophies of Bamboo Structural Design and Key Parameters for Developing the Philosophies. Cogent Eng. 2022 , 9 , 2122155. [ Google Scholar ] [ CrossRef ]
• Iqbal, Q. Scopus: Indexing and Abstracting Database. 2018. Available online: https://www.elsevier.com/products/scopus (accessed on 12 June 2024).
• Aniñon, M.J.C.; Garciano, L.E.O. Advances in Connection Techniques for Raw Bamboo Structures—A Review. Buildings 2024 , 14 , 41126. [ Google Scholar ] [ CrossRef ]
• MATLAB , R2024a. The MathWorks Inc.: Natick, MA, USA, 2024.
• Roque, C.; Lourenço Cardoso, J.; Connell, T.; Schermers, G.; Weber, R. Topic Analysis of Road Safety Inspections Using Latent Dirichlet Allocation: A Case Study of Roadside Safety in Irish Main Roads. Accid. Anal. Prev. 2019 , 131 , 336–349. [ Google Scholar ] [ CrossRef ]
• Osmani, A.; Mohasefi, J.B.; Gharehchopogh, F.S. Enriched Latent Dirichlet Allocation for Sentiment Analysis. Expert Syst. 2020 , 37 , e12527. [ Google Scholar ] [ CrossRef ]
• Dela Cruz, O.; Ongpeng, J. Building Information Modeling on Construction Safety: A Literature Review. In Advances in Architecture, Engineering and Technology: Smart Techniques in Urban Planning & Technology ; Springer: Berlin/Heidelberg, Germany, 2022; pp. 89–102. ISBN 978-3-031-11231-7. [ Google Scholar ]
• Liu, W.; Hui, C.; Wang, F.; Wang, M.; Liu, G.; Liu, W.; Hui, C.; Wang, F.; Wang, M.; Liu, G. Review of the Resources and Utilization of Bamboo in China. In Bamboo—Current and Future Prospects ; IntechOpen: London, UK, 2018; ISBN 978-1-78923-231-8. [ Google Scholar ]
• VOSViewer: Visualizing Scientific Landscapes 2010. Available online: https://www.vosviewer.com/ (accessed on 6 June 2024).
• Akinlabi, E.T.; Anane-Fenin, K.; Akwada, D.R. Bamboo the Multipurpose Plant ; Springer International Publishing: Cham, Switzerland, 2017; ISBN 978-3-319-56807-2. [ Google Scholar ]
• Bahtiar, E.T.; Imanullah, A.P.; Hermawan, D.; Nugroho, N. Abdurachman Structural Grading of Three Sympodial Bamboo Culms (Hitam, Andong, and Tali) Subjected to Axial Compressive Load. Eng. Struct. 2019 , 181 , 233–245. [ Google Scholar ] [ CrossRef ]
• Candelaria, M.D.E.; Hernandez, J.Y. Determination of the Properties of Bambusa Blumeana Using Full-Culm Compression Tests and Layered Tensile Tests for Finite Element Model Simulation Using Orthotropic Material Modeling. ASEAN Eng. J. 2019 , 9 , 54–71. [ Google Scholar ] [ CrossRef ]
• Ávila de Oliveira, L.; Luiz Passaia Tonatto, M.; Luiza Cota Coura, G.; Teixeira Santos Freire, R.; Hallak Panzera, T.; Scarpa, F. Experimental and Numerical Assessment of Sustainable Bamboo Core Sandwich Panels under Low-Velocity Impact. Constr. Build. Mater. 2021 , 292 , 123437. [ Google Scholar ] [ CrossRef ]
• Chahrour, M.K.; Hosen, M.A.; Goh, Y.; Tong, T.Y.; Yap, S.P.; Khadimallah, M.A. Failure Mechanisms of Structural Bamboo Using Microstructural Analyses. Adv. Mater. Sci. Eng. 2021 , 2021 , 1571905. [ Google Scholar ] [ CrossRef ]
• Buachart, C.; Hansapinyo, C.; Sukontasukkul, P.; Zhang, H.; Sae-Long, W.; Chetchotisak, P.; O’Brien, T.E. Characteristic and Allowable Compressive Strengths of Dendrocalamus Sericeus Bamboo Culms with/without Node Using Artificial Neural Networks. Case Stud. Constr. Mater. 2024 , 20 , 2794. [ Google Scholar ] [ CrossRef ]
• Tangphadungrat, P.; Hansapinyo, C.; Buachart, C.; Suwan, T.; Limkatanyu, S. Analysis of Non-Destructive Indicating Properties for Predicting Compressive Strengths of Dendrocalamus Sericeus Munro Bamboo Culms. Materials 2023 , 16 , 41352. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bahtiar, E.T.; Malkowska, D.; Trujillo, D.; Nugroho, N. Experimental Study on Buckling Resistance of Guadua Angustifolia Bamboo Column. Eng. Struct. 2021 , 228 , 111548. [ Google Scholar ] [ CrossRef ]
• Quintero, M.A.M.; Tam, C.P.T.; Li, H. Structural Analysis of a Guadua Bamboo Bridge in Colombia. Sustain. Struct. 2022 , 2 , 20. [ Google Scholar ] [ CrossRef ]
• Villegas, L.; Moran, R.; García, J. Combined Culm-Slat Guadua Bamboo Trusses. Eng. Struct. 2019 , 184 , 495–504. [ Google Scholar ] [ CrossRef ]
• Seixas, M.; Eustáquio Moreira, L.; Bina, J.; Ripper, J. Design and Analysis of a Self-Supporting Bamboo Roof Structure with Flexible Connections. J. Int. Assoc. Shell Spat. Struct. 2019 , 60 , 221. [ Google Scholar ] [ CrossRef ]
• Seixas, M.; Moreira, L.E.; Stoffel, P.; Bina, J. Form Finding and Analysis of an Active Bending-Pantographic Bamboo Space Structure. J. Int. Assoc. Shell Spat. Struct. 2021 , 62 , 206–222. [ Google Scholar ] [ CrossRef ]
• Ramful, R. Failure Analysis of Bamboo Bolt Connection in Uniaxial Tension by FEM by Considering Fiber Direction. For. Prod. J. 2021 , 71 , 58–64. [ Google Scholar ] [ CrossRef ]
• Ramful, R.; Sakuma, A. Investigation of the Effect of Inhomogeneous Material on the Fracture Mechanisms of Bamboo by Finite Element Method. Materials 2020 , 13 , 5039. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Han, S.; Xu, H.; Chen, F.; Wang, G. Construction Relationship between a Functionally Graded Structure of Bamboo and Its Strength and Toughness: Underlying Mechanisms. Constr. Build. Mater. 2023 , 379 , 131241. [ Google Scholar ] [ CrossRef ]
• Jin, B.-B.; Hao, J.-P.; Luo, Y.-N.; Tian, L.-M. Mechanical Behavior of Round Bamboo under Transverse Local Compression. Eng. Struct. 2023 , 294 , 116790. [ Google Scholar ] [ CrossRef ]
• Lefevre, B.; West, R.; O’Reilly, P.; Taylor, D. A New Method for Joining Bamboo Culms. Eng. Struct. 2019 , 190 , 1–8. [ Google Scholar ] [ CrossRef ]
• Long, L.; Wang, Z.; Chen, K. Analysis of the Hollow Structure with Functionally Gradient Materials of Moso Bamboo. J. Wood Sci. 2015 , 61 , 569–577. [ Google Scholar ] [ CrossRef ]
• Meng, X.; Zhang, Z.; Wu, Y.; Xu, F.; Feng, P. A Comprehensive Evaluation of the Effects of Bamboo Nodes on the Mechanical Properties of Bamboo Culms. Eng. Struct. 2023 , 297 , 116975. [ Google Scholar ] [ CrossRef ]
• Nie, S.; Yu, P.; Huang, Y.; Luo, Y.; Wang, J.; Liu, M.; Elchalakani, M. Experimental Study on Compressive Performance of the Multiple-Culm Bamboo Columns Connected by Bolts. Eng. Struct. 2024 , 303 , 117525. [ Google Scholar ] [ CrossRef ]
• Wang, F.; Yang, J. Experimental and Numerical Investigations on Load-Carrying Capacity of Dowel-Type Bolted Bamboo Joints. Eng. Struct. 2020 , 209 , 109952. [ Google Scholar ] [ CrossRef ]
• Wang, J.; Shi, D.; Zhou, C.; Zhang, Q.; Li, Z.; Marmo, F.; Demartino, C. An Active-Bending Sheltered Pathway Based on Bamboo Strips for Indoor Temporary Applications: Design and Construction. Eng. Struct. 2024 , 307 , 117863. [ Google Scholar ] [ CrossRef ]
• Wang, G.; Zhuo, X.; Zhang, S.; Wu, J. Study on the Mechanical Properties and Design Method of Frame-Unit Bamboo Culm Members Based on Semi-Rigid Joints. Buildings 2024 , 14 , 991. [ Google Scholar ] [ CrossRef ]
• Chiacchiera, P.; Bocco, A.; Ceretto, W.; Ghirardotti, D. An Investigation of Bamboo-Strip Constructions Built According to Yona Friedman’s Manuals. Proc. Inst. Civ. Eng. Constr. Mater. 2022 , 175 , 82–91. [ Google Scholar ] [ CrossRef ]
• Pradhan, N.; Paraskeva, T.; Dimitrakopoulos, E. Simulation and Experimental Verification of an Original Full-Scale Bamboo Truss. Eng. Struct. 2022 , 256 , 113965. [ Google Scholar ] [ CrossRef ]
• Nurdiah, E.; Wang, T.-H.; Chang, W.-S. Form Finding and Optimisation of Bamboo Gridshell Structures. In Education and Research in Computer Aided Architectural Design in Europe ; Dokonal, W., Hirschberg, U., Wurzer, G., Wurzer, G., Eds.; 2023; Volume 1, pp. 579–588. Available online: https://ecaade.org/conference/past/ (accessed on 6 June 2024).
• Harries, K.A.; Bumstead, J.; Richard, M.; Trujillo, D. Geometric and Material Effects on Bamboo Buckling Behaviour. Proc. Inst. Civ. Eng. Struct. Build. 2017 , 170 , 236–249. [ Google Scholar ] [ CrossRef ]
• Moran, R.; Webb, K.; Harries, K.; García, J.J. Edge Bearing Tests to Assess the Influence of Radial Gradation on the Transverse Behavior of Bamboo. Constr. Build. Mater. 2017 , 131 , 574–584. [ Google Scholar ] [ CrossRef ]
• Sá Ribeiro, R.; Sá Ribeiro, M.; Miranda, I. Bending Strength and Nondestructive Evaluation of Structural Bamboo. Constr. Build. Mater. 2017 , 146 , 38–42. [ Google Scholar ] [ CrossRef ]
• Chand, N.; Shukla, M.; Sharma, M.K. Analysis of Mechanical Behaviour of Bamboo (Dendrocalamus Strictus) by Using FEM. J. Nat. Fibers 2008 , 5 , 127–137. [ Google Scholar ] [ CrossRef ]
• Zhou, Q.; Li, J.; Liu, P.; Fu, F.; Zhu, H.; Chen, H. Study of the Tensile Properties of the Original Bamboo Sleeve Grouting Joints. J. Build. Eng. 2023 , 78 , 107708. [ Google Scholar ] [ CrossRef ]
• Puri, V.; Chakrabortty, P.; Anand, S.; Majumdar, S. Bamboo Reinforced Prefabricated Wall Panels for Low Cost Housing. J. Build. Eng. 2017 , 9 , 52–59. [ Google Scholar ] [ CrossRef ]
• Taufani, A.R.; Nugroho, A.S.B. Proposed Bamboo School Buildings for Elementary Schools in Indonesia. Procedia Eng. 2014 , 95 , 5–14. [ Google Scholar ] [ CrossRef ]
• ISO 22157:2019 ; Bamboo Structures—Determination of Physical and Mechanical Properties of Bamboo Culms—Test Methods 2019. International Organization for Standardization: Geneva, Switzerland, 2019.
• Lorenzo, R.; Mimendi, L. Digitisation of Bamboo Culms for Structural Applications. J. Build. Eng. 2020 , 29 , 101193. [ Google Scholar ] [ CrossRef ]
• Janssen, J.J. Bamboo in Building Structures. Ph.D. Thesis, Technische Hogeschool Eindhoven, Eindhoven, The Netherlands, 1981. [ Google Scholar ]
• Lorenzo, R.; Godina, M.; Mimendi, L.; Li, H. Determination of the Physical and Mechanical Properties of Moso, Guadua and Oldhamii Bamboo Assisted by Robotic Fabrication. J. Wood Sci. 2020 , 66 , 20. [ Google Scholar ] [ CrossRef ]
• Mimendi, L.; Lorenzo, R.; Li, H. An Innovative Digital Workflow to Design, Build and Manage Bamboo Structures. Sustain. Struct. 2022 , 2 , 11. [ Google Scholar ] [ CrossRef ]
• NBR-16828-2 ; Métodos de Prueba Para Determinar Las Propiedades Físico-Mecánicas de Los Bambúes. Brazilian Association of Technical Standards: Rio de Janeiro and São Paulo, Brazil, 2020.
• NBR-16828-1 ; Diseño y Dimensionamiento de Estructuras de Bambú. Brazilian Association of Technical Standards: Rio de Janeiro and São Paulo, Brazil, 2020.
• NSR-10 ; Colombian Building Code. Asociación Colombiana de Ingeniería Sísmica: Bogotá, Colombia, 2010.
• ASTM ASTM D143 ; Test Methods for Small Clear Specimens of Timber. ASTM International: West Conshohocken, PN, USA, 2013.
• C09 Committee ASTM C469 ; Test Method for Static Modulus of Elasticity and Poissons Ratio of Concrete in Compression. ASTM International: West Conshohocken, PN, USA, 2022.
• BS EN 26891 ; Timber Structures-Joints Made with Mechanical Fasteners–General Principles for the Determination of Strength and Deformation Characteristics. British Standards Institution (BSI): London, UK, 1991.
• AC 162 ; Acceptance Criteria for Structural Bamboo. ICC Evaluating Service, LCC: Brea, CA, USA, 2000. Available online: https://icc-es.org/acceptance-criteria/ac162/ (accessed on 6 June 2024).
• ASTM D2915 ; Practice for Sampling and Data-Analysis for Structural Wood and Wood-Based Products. ASTM International: West Conshohocken, PN, USA, 2022.
• ISO 19624:2018 ; Bamboo Structures—Grading of Bamboo Culms—Basic Principles and Procedures. International Organization for Standardization: Geneva, Switzerland, 2018.
• ISO 22156:2021 ; Bamboo Structures—Bamboo Culms—Structural Design. International Organization for Standardization: Geneva, Switzerland, 2021.
• JG/T 199-2007 ; Standardization Administration of China Testing Methods for Physical and Mechanical Properties of Bamboo Used in Building. Standardization Administration of China (SAC): Beijing, China, 2007.
• GB/T 2690 ; Bamboo Timber. 2000. Available online: https://max.book118.com/html/2019/0810/8022043116002041.shtm (accessed on 6 June 2024).
• ABNT NBR 8681 ; Ações e Segurança Nas Estruturas. Associação Brasileira de Normas Técnicas (ABNT): Rio de Janeiro, Brazil, 2003.
• NSR-10 ; Título G—Estructuras de Madera y Estructuras de Guadua. Asociación Colombiana de Ingeniería Sísmica: Bogotá, Colombia, 2010.
• Michiels, T.; Lu, L.; Archer, R.; Adriaenssens, S.; Tresserra, G. Design of Three Hypar Roofs Made of Guadua Bamboo. J. Int. Assoc. Shell Spat. Struct. 2017 , 58 , 844. [ Google Scholar ] [ CrossRef ]
• JGJ 254 ; Technical Code for Safety of Bamboo Scaffold in Construction. Ministry of Housing and Urban-Rural Development (MOHURD): Beijing, China, 2011.
• Hailemariam, E.; Hailemariam, L.; Amede, E.; Nuramo, D. Identification of Barriers, Benefits and Opportunities of Using Bamboo Materials for Structural Purposes. Eng. Constr. Archit. Manag. 2022 , 30 , 996. [ Google Scholar ] [ CrossRef ]
• Khatry, R.; Mishra, D.P. Finite Element Analysis of Bamboo Column along with Steel Socket Joint under Loading Condition. Int. J. Appl. Eng. Res. 2012 , 7 , 1247–1251. [ Google Scholar ]
• Smith, M. ABAQUS/Standard User’s Manual, Version 6.9 ; Dassault Systèmes Simulia Corp: Providence, RI, USA, 2009. [ Google Scholar ]
• DeSalvo, G.J.; Swanson, J.A. ANSYS Engineering Analysis System User’s Manual ; Swanson Analysis Systems, Inc.: Elisabeth, PA, USA, 1979. [ Google Scholar ]
• SAP2000 ; Integrated Software for Structural Analysis and Design. Computers and Structures, Inc. (CSI): Berkeley, CA, USA, 2013.
• Tahmasebinia, F.; Ma, Y.; Joshua, K.; Sepasgozar, S.M.E.; Yu, Y.; Li, J.; Sepasgozar, S.; Marroquin, F.A. Sustainable Architecture Creating Arches Using a Bamboo Grid Shell Structure: Numerical Analysis and Design. Sustainability 2021 , 13 , 2598. [ Google Scholar ] [ CrossRef ]
• Strand7 Release 3.1.4 (R3.1.4). Available online: https://www.strand7.com/r3/Strand7%20R3%20Setup%20Guide.pdf (accessed on 6 June 2024).
• Estrada Meza, M.G.; González Meza, E.; Chi Pool, D.A.; McNamara Trujillo, J.S. Design Exploration of Bamboo Shells Structures by Using Parametric Tools. Appl. Sci. 2022 , 12 , 7522. [ Google Scholar ] [ CrossRef ]
• de Albuquerque, N.B.; Gaspar, C.M.R.; Seixas, M.; Santana, M.V.B.; Cardoso, D.C.T. Design, Fabrication and Analysis of a Bio-Based Tensegrity Structure Using Non-Destructive Testing. Eng. Struct. 2022 , 265 , 114457. [ Google Scholar ] [ CrossRef ]
• Oasys Software. Available online: https://www.oasys-software.com/ (accessed on 6 June 2024).
• Torres, L.A.; Ghavami, K.; García, J.J. A Transversely Isotropic Law for the Determination of the Circumferential Young’s Modulus of Bamboo with Diametric Compression Tests. Lat. Am. Appl. Res. 2007 , 37 , 255–260. [ Google Scholar ]
• García, J.J.; Rangel, C.; Ghavami, K. Experiments with Rings to Determine the Anisotropic Elastic Constants of Bamboo. Constr. Build. Mater. 2012 , 31 , 52–57. [ Google Scholar ] [ CrossRef ]
• Hu, C.; Cheng, R.; Cheng, Q.; Liu, J. Study on Behavior of Steel Hoop Connections for Raw Bamboo Members. Materials 2021 , 14 , 7253. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Khatry, R.; Mishra, D.P. Finite Element Analysis of Bamboo and Joints Using Steel Members under Various Loading Conditions for Design Study. Ind. Inst. Technol. Kanpur 2013 . [ Google Scholar ]
• Masdar, A.; Suhendro, B.; Siswosukarto, S.; Sulistyo, D. Determinant of Critical Distance of Bolt on Bamboo Connection. J. Teknol. 2014 , 69 , 3319. [ Google Scholar ] [ CrossRef ]
• Taylor, D.; Kinane, B.; Sweeney, C.; Sweetnam, D.; O’Reilly, P.; Duan, K. The Biomechanics of Bamboo: Investigating the Role of the Nodes. Wood Sci. Technol. 2015 , 49 , 345–357. [ Google Scholar ] [ CrossRef ]

Share and Cite

Muhammad, N.A.G.; Orejudos, J.N.; Aniñon, M.J.C. A Compendium of Research, Tools, Structural Analysis, and Design for Bamboo Structures. Buildings 2024 , 14 , 2419. https://doi.org/10.3390/buildings14082419

Muhammad NAG, Orejudos JN, Aniñon MJC. A Compendium of Research, Tools, Structural Analysis, and Design for Bamboo Structures. Buildings . 2024; 14(8):2419. https://doi.org/10.3390/buildings14082419

Muhammad, Nurwin Adam G., Jerson N. Orejudos, and Mary Joanne C. Aniñon. 2024. "A Compendium of Research, Tools, Structural Analysis, and Design for Bamboo Structures" Buildings 14, no. 8: 2419. https://doi.org/10.3390/buildings14082419

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