How Can I Verify My FEA Results? (What to know)

Finite Element Analysis (FEA) is an incredibly powerful tool, capable of simulating complex physical phenomena with remarkable accuracy. But, like all tools, its efficacy is only as good as the validity of the results it generates. 

It is important to verify FEA results to ensure the simulation accurately represents the real-world scenario. 

To verify FEA results, compare your results with experimental data or analytical solutions. Check convergence by refining mesh and assessing changes in results. Perform sensitivity analysis to evaluate the influence of input parameters. Validate against known benchmarks and consult industry standards.

In this article, I will explain what FEA verification means and why it is crucial in engineering. I will also discuss ways to check if your FEA results are reliable and what can be done if verification is impossible.

An engineer prepares a 3D model for FEA

What Do We Mean By FEA Verification?

FEA Verification refers to the process of confirming that the mathematical model of a Finite Element Analysis (FEA) accurately represents the system’s physical behaviour. This involves comparing the FEA results with known solutions or experimental results to ensure they align within an acceptable error range. 

Verification is not just about checking the correctness of the FEA model but also the assurance that the numerical solution process is working correctly. Suppose you never verify your simulation model by comparing it to real-world data. In that case, you can’t be sure that your simulation is truly accurate and can be depended on to make further design changes.

It’s necessary to build confidence in the FEA model before it can be applied to practical design or analysis tasks.

Why Do We Need To Verify FEA Results?

Verification of FEA results is crucial for several reasons. Firstly, it ensures that the simulation accurately mirrors the reality it aims to replicate, reducing the likelihood of unforeseen problems in the design or evaluation process. 

Secondly, verification can highlight potential issues in the FEA model, such as incorrect parameter settings or software glitches, which can lead to inaccurate results. 

Lastly, consistent verification builds trust in the FEA model, giving stakeholders and decision-makers confidence in the analyses and predictions made using the model. 

Without verification, the risk of basing decisions on potentially faulty data increases substantially, which could have significant implications in fields like structural engineering or aerodynamics, where safety and precision are paramount.

How Can I Verify My FEA Results?

There are several approaches you can use to verify your FEA results:

  1. Compare With Experimental Data: If possible, compare your FEA results with experimental or test data. This is arguably the most reliable verification method, as it directly matches the simulated scenario with real-world results.
  2. Use Analytical Solutions: For simpler models or situations where analytical solutions are available, use these to check your FEA results. However, remember that analytical solutions may not exist for more complex scenarios.
  3. Perform A Mesh Convergence Study: Refine the mesh and see if the solution converges. A mesh-independent solution indicates that your FEA model correctly represents the physical scenario.
  4. Conduct A Sensitivity Analysis: Check how much your results change with slight modifications to your input parameters. A stable solution should not show significant changes.
  5. Check Against Known Benchmarks: If available, compare your results against known benchmarks in your field of study or industry. Consistency with these can offer reassurance that your model is valid.

It’s worth noting that, at times, it may not be possible to verify your FEA results using the methods above due to constraints such as time, resources, or the complexity of the model. 

In such cases, it is prudent to use your engineering judgment, backed with experience and understanding of the physical phenomena being modelled.

How To Check If Your FEA Is Right?

Here are some tips on how you can verify if your FEA is correct:

  1. Start Simple: Always begin your simulation with the simplest possible model. Solve a simpler version of the problem first and gradually add complexity. This step-by-step approach can help you identify and rectify potential errors at an early stage.
  2. Use Known Solutions: Whenever possible, start with a problem for which you know the solution. This will allow you to check whether the FEA model produces the correct results.
  3. Check Boundary Conditions: One common source of error in FEA is improperly defined boundary conditions. Make sure your boundary conditions accurately represent the physical scenario.
  4. Examine The Results Carefully: Spend time reviewing the results. Look for any inconsistencies or anomalies in the output, such as unrealistic deformations or stress concentrations.
  5. Trust But Verify: Even if the results seem to make sense and align with your expectations, do not just accept them at face value. Always cross-verify with other methods or consult with others.

Remember, verifying your FEA results can be both an art and a science, requiring a blend of engineering knowledge, intuition, and rigorous validation techniques.

Do I Always Have To Verify My FEA Results?

It is highly recommended to always verify your FEA results, regardless of how routine or seemingly straightforward the simulation might be. 

While it may appear to be an added step, consider verification as an integral part of the modelling process. This practice instils confidence in the results and ensures that the decisions made based on the model are sound and reliable. 

However, there might be instances where complete verification is not feasible due to time or resource constraints. In such scenarios, caution should be exercised, and partial verification, supplemented with engineering judgment, may be considered the course of action. 

Remember, unverified or poorly verified results can lead to misinterpretations, errors, and potentially costly or even catastrophic design failures.

What Should I Do If It Is Not Possible To Verify My FEA?

In the real world, when working in an industry with tight deadlines, it is not always possible to verify FEA. This can be stressful for the FEA analysis, and this is when experience comes into play. I have been in this position many times. 

In scenarios where complete verification of FEA results is not possible, a few strategies can help ensure the credibility of your results. 

Firstly, always apply your engineering judgment. Your experience and understanding of the physics of the problem at hand are invaluable in assessing the plausibility of your results. 

Secondly, consider conducting a sensitivity analysis to understand how varying your input parameters by a reasonable amount influences the results. This can provide a sanity check and identify potential instabilities in your model. 

Lastly, if available, consult with colleagues or take advantage of community forums and industry groups. Peer review can provide additional insights and catch potential errors or inaccuracies. 

Despite the challenges in verification, never fully disregard this crucial step. Instead, adapt and employ creative methods to build confidence in your results to the best extent possible.

Final Thoughts

FEA verification is a vital process in ensuring the accuracy and reliability of simulation results. Despite the varying levels of complexity, a number of strategies can be employed to verify FEA results, including comparison with experimental data, use of analytical solutions, mesh convergence studies, sensitivity analysis and consultation with known benchmarks. 

Even when complete verification seems challenging due to constraints, judicious application of engineering judgement, use of sensitivity analysis and seeking peer review can help maintain the integrity of the results. 

It’s essential to remember that the goal of verification is not to achieve perfection but to instil confidence in your results and reduce the margin of error, thereby enabling sound, informed decision-making.

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