Methods of CAE-based Robust Design Optimization (RDO)
The goal of CAE-based optimization in virtual prototyping is often to achieve an optimal product performance with a minimal usage of resources (e.g. material, energy). This pushes designs to the boundaries of tolerable stresses, deformations or other critical responses. As a result, the product behavior may become sensitive to scatter with regard to material, geometric or environmental conditions. Subsequently, a robustness evaluation has to be implemented in the optimization process leading to a Robust Design Optimization (RDO) strategy that consists of:
- Sensitivity analyses to identify the most affecting parameters regarding the optimization task
- Multi-disciplinary and multi-objective optimizations to determine the optimal design
- Robustness evaluations to verify robustness values and failure probabilities
As a final step, a reliability analysis allows a necessary verification of small probabilities of failure after the conduction of a robustness evaluation or Robust Design Optimization (RDO).
Regarding the procedure of parameter identification, also named model update, a sensitivity analysis helps to identify parameters of CAE models suitable for the best possible calibration with test results.
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