Calibration of numerical models based on advanced optimization and penalization techniques

Abstract

A new approach to estimation of unknown material parameters and boundary conditions of physical models was developed. The approach is based on processing measured data by advanced optimization techniques connected with penalization. The data are supposed to be in the form of random variables with normal probability distributions. Several examples were calculated proving the strength of the proposed algorithm.