PARAMETER-IDENTIFICATION FOR VISCOPLASTIC MODELS BASED ON ANALYTICAL DERIVATIVES OF A LEAST-SQUARES FUNCTIONAL AND STABILITY INVESTIGATIONS

In this work a unified strategy for identification of material paramet ers of viscoplastic constitutive equations from uniaxial test data is presented. Gradient-based descent methods (e.g. Gauss-Newton method, Q uasi-Newton method) are used for minimization of a least-squares funct ional, thus requiring the associative gradient. The corresponding sens itivity analysis is explained in detail, where as a main result a recu rsion formula is obtained. Furthermore, the stability of the numerical results for the material parameters is investigated by use of the eig envalues for the Hessian of the least-squares functional. Numerical ex amples are presented in the context of monotonic and cyclic loading. I n particular, comparative results with a genetic algorithm reflect the efficiency of our strategy with respect to execution time, and we stu dy the effect of perturbations of the experimental data on the stabili ty of the parameters. In one example we demonstrate how possible insta bilities can be circumvented by a regularization of the basic least-sq uares functional. Copyright (C) 1996 Elsevier Science Ltd