PSI - Issue 57

Andrew Halfpenny et al. / Procedia Structural Integrity 57 (2024) 718–730 Andrew Halfpenny / Structural Integrity Procedia 00 (2023) 000–000

728

11

Fig. 6. Weibull Comparison of Simulated Data with Reliability Test Data

• The mean simulated fatigue life (50% unreliability or 0.5 reliability) is seen to correlate well with the mean qualification test (both curves intersect at the mean). • At the 95% reliability level (5% unreliability or 0.95 reliability), the simulation is seen to overestimate the expected test damage. This results in a shorter predicted life. However, this prediction is still within the 90% confidence bounds of the qualification test data, so the null hypothesis (the simulation is truly representative of the test) is not rejected. The fact that damage is slightly overestimated by the simulation is often welcomed by the design engineer. • At the 5% reliability level (95% unreliability or 0.05 reliability), the simulation is seen to underestimate the expected test damage. This results in a longer than observed predicted life. In this case the simulation lies outside of the 90% confidence bounds so we must conclude that the simulation is not representative of the test at the 90% confidence level. This situation is not alarming to the design engineer because these lives are significantly beyond the warranty life (100,000 cycles in this case). A further simulation was undertaken to compare the uncertainty resulting from Material performance (an aleatoric uncertainty) and that resulting from FE modelling errors (an epistemic uncertainty). The results are shown in Fig. 7. At the 90% confidence level all contours intersect which implies that the null hypothesis (the simulation is truly representative of the test) is not rejected. It also shows that the largest variability is due to material fatigue performance. This further implies that any additional improvements in FE simulation will not reduce the overall uncertainty as this is largely attributable to the fatigue performance of the material.

5. Conclusion

In the aerospace, automotive, and power generation industries, it is becoming increasingly necessary to qualify components based on their reliability and risk of failure. This paper considers how the existing design, simulation, verification, and validation process used by the industries may be enhanced to o ff er significant improvements in predicted confidence. These enhancements are cost-e ff ective and fairly easy to implement. They consist of:

1. Additional test instrumentation applied in the qualification test to verify the simulation results. 2. Qualification tests that must be continued to failure to verify the fatigue simulation.