Reliability-based design optimization using local sensitivity with application to magnetic nano switch

Abstract

This paper presents a method and a tool for solving the reliability-based design optimization (RBDO). The RBDO aims to minimize a cost function by changing the value of design parameters while ensuring a level of reliability. Uncertainties propagation is a key concept in reliable studies and it can be associated with a sensitivity analysis in order to sort parameter influences. Global and local sensitivities are compared in this study in order to keep a reasonable cost versus accuracy ratio. A software tool has been also developed to automate reliable studies. It is applied to the reliable optimization of a magnetic nano switch with SQP algorithm using Jacobian calculated by composition of automatic and symbolic differentiation. In comparison to the formulation of the classical optimization problem, the inequality constraint ap- pears modified: {P (Hj(X) 0) PHj} which is a reliability constraintinvolving the stochastic vector X modelling the uncertainties inherent in the model, and PHj is the maximal probability allowed.