The use of simulations to displace physical tests has become essential in accelerating product development and reducing costs. However, simulation results may be substantially different from what is observed. This could lead to premature product failure, costly warranty payments and a redesign campaign. Statistical calibration is an analytical method for narrowing the gap between simulation and test results.
Using the same workflow as suggested in the ASME V&V 10 and V&V 40 documentation, Uncertainty Quantification methods, such as statistical calibration and uncertainty propagation, will be applied to a practical, end-to-end case study in which the performance of a balloon expandable coronary stent model is analyzed with respect to geometric and material property variation. The model’s credibility will also be assessed using a set of mock physical test results.
This 30-minute webinar will cover:
