Dyna result doesn't match Test result

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In summary: It's also possible that there are errors in your data collection or conversion process.In summary, the conversation discusses the discrepancies between a simple tensile test for steel MAT_024 and the results from a Dyna simulation. The speaker suggests using a formula to convert the collected data into true stress and strain, and then converting the true strain into plastic strain. However, the results from the test and simulation were different, potentially due to incorrect material properties or boundary conditions. The speaker asks for help in solving this issue.
  • #1
lambertlai
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I try many time to model a simple tensile test for steel MAT_024 but the graph doesn't match from Dyna result and Test result.
Process:
1. Collect data Tensile strain and stress convert to True stress and strain use formula True stress: eng. stress*(1+eng. strain). True strain= ln(1+eng. strain) and then the true strain convert to plastic strain = true strain - (true stress / Young modulus) and plot the graph
389954639.jpg


2. Use MAT_024 from dyna
389954647.jpg

389954647.jpg

3. Then I extract nodout and sec force.
389954850.jpg

LN1 is left node 1 (triangle on left)
RN1 is right node (triangle on right)

4. Eng stress= Force/Ao and eng. strain= delta Length / original length and plot the graph. (original area is 40, original length is 45mm)
389954524.jpg

389954523.jpg

389954525.jpg


Then the both result was different, why? What the misstake? Anyone can help me solve this problem?
 
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  • #2
The most likely cause of the discrepancy between the test result and Dyna result is that you have not accurately captured the material's mechanical properties. In order to match the test result, you will need to accurately capture the Young's modulus, yield strength, ultimate strength, strain hardening, and other properties of the material. Additionally, you may need to adjust the boundary conditions for the simulation to ensure that they accurately reflect the test setup.
 

1. Why does the dyna result not match the test result?

There are several possible reasons for this discrepancy. It could be due to experimental error, such as incorrect measurements or equipment malfunctions. It could also be a result of the dyna test not accurately representing the real-world conditions of the test. Additionally, there may be variations in the test conditions or materials used that can affect the results.

2. How can I ensure that the dyna result matches the test result?

To ensure consistency between dyna and test results, it is important to carefully design and conduct the experiment, controlling for any potential sources of error. Using standardized protocols and equipment can also help improve the accuracy of the results. It may also be helpful to repeat the experiment multiple times and compare the average results to minimize any discrepancies.

3. Can differences in sample size affect the dyna and test results?

Yes, sample size can play a significant role in the accuracy of results. A larger sample size can help reduce the impact of outliers and provide a more representative average result. It is important to have a sufficient sample size to ensure the reliability and validity of the experiment.

4. How can statistical analysis help explain the differences between dyna and test results?

Statistical analysis can provide valuable insights into the differences between dyna and test results. By using techniques such as hypothesis testing and confidence intervals, we can determine if the differences are significant or simply due to chance. This can help identify any underlying factors that may be contributing to the discrepancies.

5. What steps can be taken to improve the accuracy of dyna and test results?

In addition to carefully designing and conducting the experiment, there are several steps that can be taken to improve the accuracy of dyna and test results. These include ensuring a consistent testing environment, minimizing human error, and using reliable and calibrated equipment. It may also be helpful to consult with other scientists or experts in the field to review and validate the experimental design and results.

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