Adding hypothesis testing to evolutionary RBDO with Monte Carlo simulations
Résumé
Engineers have a long history with accounting for uncertainties in the design process [2]. They have first defined critical loadings and safety factors. More recently, uncertainty quantification is receiving a large attention from the engineering community because a finer characterization of the uncertainties is seen as an important performance reserve. In the presence of uncertainties, the performance of an individual system varies. Reliability based design optimization (RBDO) and robust optimization average out uncertainties by ultimately seeking solutions having the best statistical performance measure [1].