Ns-kriging based microstructural optimization applied to minimizing stochastic variation of homogenized elasticity of fiber reinforced composites

This paper describes an approximate microstructural optimization using the ns-kriging (noise-resistant smoothed kriging) method for minimizing the maximum stochastic variation of homogenized elastic properties of a composite material caused by microscopic uncertainties of component materials. Since evaluation of a stochastic characteristic of a homogenized material property such as expectation or variance will involve a high computational cost and its results include inaccuracy in using the Monte Carlo simulation, an approximation-based optimization technique is useful for solving the optimization problem considering the multiscale stochastic problem. Especially, the ns-kriging will work well in case of using inaccurate data for an unknown objective function. In order to investigate applicability and effectiveness of the proposed ns-kriging based approach to the optimization problem, it is applied to the cross-sectional shape optimization of fiber in a unidirectional FRP. From the numerical results, validity and effectiveness of the proposed approach are confirmed.