期待値と分散が不確かな正規分布に対する信頼性制約について

抄録

This paper deals with uncertainty of moments of multivariate normal distribution that design variables in reliability-based design optimization follow. Specifically, we assume that the expected value vector and the variance-covariance matrix belong to given closed convex sets, and require that structural reliability in the worst case is no smaller than a target value. It is shown that this performance requirement can be reduced to some deterministic constraints. A simple numerical example demonstrates a potential that the presented formulation can be handled within the conventional framework of deterministic optimization.