Abstract
In order to extend the application of reliability-based design optimization to engineering electromagnetic problems, the main contribution of this paper is to propose an efficient reliability analysis method: adaptive Kriging-assisted weight index Monte Carlo Simulation (MCS). The Kriging model is constructed to substitute for expensive finite-element analysis of engineering problem during optimization and reliability analysis. To improve the interpolation accuracy of Kriging, a learning function is adopted in adaptive sampling process. A weight index form of MCS method is proposed to enhance the efficiency of conventional MCS method. Finally, taking the result of conventional MCS as a reference, proposed reliability analysis method is compared with reliability index approach and sensitivity-assisted MCS methods.
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