How to Validate the Results of Static Structural Analysis Using ANSYS

Validating the results of static structural analysis using ANSYS is crucial for ensuring the accuracy and reliability of simulation outcomes. Below is a detailed step-by-step guide to help you validate your ANSYS results effectively.

1. Check Input Parameters

Material Properties

Young's Modulus: Ensure that the Young's modulus is accurately defined for your material. Poisson's Ratio: Confirm that the Poisson's ratio is correctly specified. Yield Strength: Verify that the yield strength is appropriately set.

Geometry

Ensure that the geometry of the model accurately represents the intended design specifications. Any discrepancies in the geometry can lead to incorrect stress and strain distributions.

2. Mesh Quality

Mesh Density

Use a sufficiently fine mesh to capture stress gradients, especially in regions with high stress concentrations. A finer mesh means a higher level of detail and accuracy in the simulation results.

Element Quality

Skewness: Assess the skewness of the mesh elements. Skewness metrics help in determining the quality of the mesh. Aspect Ratio: Check the aspect ratio of the elements to ensure they are not overly distorted, as this can affect the simulation results. Metric-Based Quality Measures: Utilize ANSYS tools that assess and improve mesh quality.

3. Boundary Conditions and Loads

Correct Application

Ensure that boundary conditions and loads are applied correctly, reflecting the physical constraints and forces acting on the structure.

Consistency

Double-check that the loads are consistent with the intended loading conditions. For example, ensure that static loading is correctly differentiated from dynamic loading.

4. Comparison with Analytical Solutions

Simplified Cases

For simple geometries and loading conditions, compare the ANSYS results with analytical solutions. This can be done for cases such as beam bending and torsion to identify any discrepancies.

Benchmark Problems

Utilize well-documented benchmark problems from literature to compare your results. This helps in validating the accuracy of your simulation.

5. Convergence Studies

Refinement Studies

Perform convergence studies by refining the mesh and observing how the results change. The results should stabilize as the mesh is refined.

Load Cases

Validate the results under different load cases to ensure consistent behavior. This helps in identifying any load-dependent issues in the model.

6. Review Results

Post-Processing

Carefully review the post-processed results, looking for unexpected stress concentrations or deformation patterns. Ensure that the stress distribution makes physical sense and aligns with expectations based on the material and loading conditions.

7. Experimental Validation

Physical Testing

If possible, conduct physical experiments on a prototype or similar structure and compare the experimental results with the simulation results.

Correlation

Analyze the correlation between the experimental data and simulation results to establish confidence in the model. This step provides strong evidence of the model's validity.

8. Sensitivity Analysis

Parameter Variation

Conduct a sensitivity analysis to see how changes in key parameters such as material properties and load magnitudes affect the results.

Robustness

This helps in understanding the robustness of the model and identifying critical parameters, which can be improved for better accuracy.

9. Documentation and Reporting

Thorough Documentation: Document all assumptions, methodologies, and findings throughout the validation process. Proper documentation ensures transparency and facilitates peer review.

Clear Reporting: Prepare a clear report summarizing the validation steps, results, and conclusions. This report should provide a comprehensive overview of the validation process, allowing others to follow and understand your methodology.

Conclusion

By following these steps, you can effectively validate your static structural analysis results in ANSYS, ensuring that they are reliable for engineering decision-making. Remember that validation is an iterative process, and continuous improvement in modeling practices will enhance the accuracy of your simulations.