A comparison of metamodeling techniques for crashworthiness optimization

Abstract

This crashworthiness optimization study compares the use of three metamodeling techniques while using a sequential random search method as a control procedure. The three methods currently applied are (i) the Successive Linear Response Surface Method, (ii) the Updated Neural Network method and (iii) the Kriging method. Three crashworthiness examples, including a full vehicle multidisciplinary analysis, are investigated. It is shown that, although NN and Kriging seem to require a larger number of initial points, the three metamodeling methods have comparable efficiency when attempting to achieve a converged result. The Neural Network and Kriging methods have the advantage that they can be updated to construct a reasonable global approximation with higher accuracy at the optimum. Copyright © 2004 by Livermore Software Technology Corporation.