Comparative Study of Two Optimization Methods for Structural Damage Severity Estimation

Abstract

This paper presents comparative assessment of the performance characteristics of two optimization algorithms, namely a deterministic nonlinear least squares (NLS) optimization and a stochastic adaptive simulated (ASA) annealing global optimization, implemented in the context of a two-stage structural damage severity estimation approach. First, both the standard NLS and global ASA optimization algorithms were employed to estimate single as well as multiple structural damage severity via minimization of a cost function expressed in terms of the scalar distance between the “damage-sensitive” response parameter determined from a potentially damaged structure and that computed from a finite element model of the undamaged structure. Consequently, the results obtained from extensive simulation studies conducted on data acquired from numerical experiments performed on a simply supported beam-like structure using both of the optimization algorithms in the presence of more realistic damage condition states were compared. The practical relevance of these results are critically summarized in this paper.