Material identification in structural optimization using response surfaces

Abstract

This paper evaluates the use of a response surface optimization algorithm for structural material or parameter identification. The algorithm used is the successive response surface method (SRSM) as implemented in LS-OPT. Two methods are used in the formulation of the optimization problem. The first is to minimize the maximum deviation of the distance function between the simulated and experimental results at selected points, while the second approach minimizes the more standard least squares residual form of the distance function, effectively providing a compromised match over all the parameters selected. SRSM uses a trust region that is adapted using a heuristic contraction and panning approach. The method has only one user-required parameter, the size of the initial trust region. To illustrate the robustness of SRSM as a material identification tool, three test cases are presented. The first concerns the identification of the power-law material parameters of a simple tensile test specimen. The second test case determines the leakage coefficient-pressure load curve of an airbag given experimental kinematic data of a chest form impacting the airbag. In the third test case the material identification of a rate-dependent low-density foam material is conducted. It is shown that SRSM essentially converges within 10 iterations for all the test cases, and that the two distance function minimization approaches produce similar results.