Automated parameter determination of advanced constitutive models

Parameter determination of advanced cyclic plasticity models which are developed for simulation of cyclic stress-strain and ratcheting responses is complex. This is mainly because of the large number of model parameters which are interdependent and three or more experimental responses are used in parameter determination. Hence the manual trial and error approach becomes quite tedious and time consuming for determining a reasonable set of parameters. Moreover, manual parameter determination for an advanced plasticity model requires in-depth knowledge of the model and experience with its parameter determination. These are few of the primary reasons for advanced cyclic plasticity models not being widely used for analysis and design of fatigue critical structures. These problems could be overcome through developing an automated parameter optimization system using heuristic search technique (e.g. genetic algorithm). This paper discusses the development of such an automatic parameter determination scheme for improved Chaboche model developed by Bari and Hassan [4]. A new stepped GA optimization approach which is found to be more efficient over the conventional GA approach in terms of fitness quality and optimization time is presented.