How do you validate and verify your cyclic loading and stress concentration results?

Validating and verifying cyclic loading and stress concentration results involve – Defining your loading scenario accurately, including magnitude, frequency, and duration of cycles. Using finite element analysis (FEA) to simulate stress distribution and identify potential concentration points. Comparing simulation results with theoretical calculations and empirical data for consistency. Conducting physical tests on prototypes or samples to correlate with simulation outcomes. Implementing a rigorous peer-review process to scrutinise the methodology and findings. Iterating the validation process with adjusted parameters to refine the accuracy of the results.

Again, entry wording, is it structural analysis fails or structural material? I think the second. One has to learn the metallurgy then fatigue design philosophy.

In my study, we validated stress and mechanical fatigue in PRD1 particles by combining Atomic Force Microscopy (AFM) imaging and nanoindentation measurements. Here's how: Stress: Imaging: They visualized individual particles on mica surfaces using AFM, confirming their presence and integrity. Nanoindentation: They applied controlled forces to particles using the AFM tip, observing their response to compression. Force curves: By analyzing the force vs. distance curves, they identified the yield point (onset of significant deformation) and calculated the yield force and strain for each particle type. Fracture: Force curves revealed fracture events occurring after the yield point, suggesting how particles break under mechanical stress.

Define quantitative metrics to assess the agreement between predicted and observed fatigue responses. Develop criteria for evaluating the accuracy, precision, and reliability of the cyclic loading and stress concentration models. Establish acceptance thresholds based on industry standards and best practices to determine the validity of the fatigue analysis results. Conduct sensitivity studies to evaluate the impact of varying input parameters on the predicted fatigue behavior. Analyze the sensitivity of fatigue life estimates to factors such as material properties, loading conditions, and geometric configurations.

Incorporating risk assessment methodologies, such as Failure Mode and Effects Analysis (FMEA), helps in prioritizing critical fatigue failure modes and identifying mitigation strategies. In a project involving the fatigue analysis of automotive suspension components, we conducted FMEA to assess the potential consequences of fatigue failures on vehicle safety and performance. By quantifying the severity, occurrence, and detectability of failure modes, we could prioritize design modifications to mitigate high-risk scenarios effectively. Utilizing advanced life prediction models, such as the Coffin-Manson equation or Paris Law, enhances the accuracy of fatigue life estimations and aids in long-term structural integrity management.

Ensuring the mesh is sufficiently refined near areas of expected high stress concentrations is fundamental. In my experience, conducting mesh convergence studies, where the mesh density is systematically increased until the changes in stress values fall within a pre-defined tolerance, has been crucial. For instance, in analysing the fatigue life of welded joints under cyclic loading, mesh convergence studies ensured that the predicted stress concentrations were not artefacts of the numerical model but accurate representations of the physical behaviour. Aligning the analysis results with established industry standards and guidelines serves as an additional layer of verification.