Identification of Gurson's material constants by using Kalman filter

Abstract

This paper presents a method for identifying the Gurson's material constants by inverse analysis. Firstly, in older to improve the accuracy, the measurement condition. such as geometries of specimens. locations of measurements and types of measurements. is optimized. This approach is based on the Kalman filter technique. The optimization is achieved by minimizing the maximum eigen value of a posteriori estimate error covariance matrix. Mathematically. this procedure is reduced to solve a combinational/discrete optimization problem. Secondly, the Gurson's material constants is estimated by using Kalman filter. A numerical identification is presented to demonstrate the validity and usefulness of proposed method.