Optimization Of Chaboche Kinematic Hardening Parameters For 20mnmoni55 Reactor Pressure Vessel Steel By Sequenced Genetic Algorithms Maintaining The Hierarchy Of Dependence

The material 20MnMoNi55 reactor pressure vessel (RPV) steel has safety-critical applications and may experience cyclic loading during atypical operating conditions. Simulation of the material behaviour subjected to cyclic loading requires suitable kinematic hardening rules and accurate material parameters. The determination of Chaboche kinematic hardening parameters from experimental data is not well defined and the same is true for the cyclic yield stress. These parameters are interdependent and need optimization, maintaining the same hierarchy of dependence. Therefore, in the present work, evolutionary search algorithms are implemented in nested applications to find the material parameters phenomenologically. The main coding is done in MATLAB(R), while the objective function is evaluated in the ABAQUS finite element simulation environment. Necessary extraction of the field outputs is achieved by PYTHON scripting. The optimum material parameters offer good simulation of the actual material behaviour in cyclic plastic loading.