Application of gradient based algorithms for robust shape optimization of a tensile test specimen

Abstract

In case of technical applications such as automotive or aeronautic part optimization, uncertainties in design variables and other parameters have to be taken into account. Especially, scattering of material properties and mechanical loads have large influences on the component behavior. Due to the difficulty in calculating of sensitivities, usually stochastic algorithms are used for robust and reliability optimization. That entails a large number of function calls and long computation time. Therefore, the stochastic responses with expectation value and variances will be approximated by and responses surface in this contribution. Based on the practical example of a tensile test specimen an deterministic optimization and optimization under uncertainties will be done. The results of the different optimizations will compared and the influence of the uncertainties will be shown and discussed.