Kinematic Hardening Parameters Identification with Finite Element Simulation of Low Cycle Fatigue using Genetic Algorithm Approach

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Jagabandhu Shit

Abstract

This paper deals with finite element (FE) simulation to characterize the low cycle fatigue (LCF) behavior using genetic algorithm (GA) approach. Non linear version of Chaboche’s kinematic hardening material model is used to address the stable hysteresis cycles of the material. Cyclic hardening phenomenon is addressed by introducing exponential isotropic hardening rule in the material model. The elastic plastic FE code ABAQUS is used for finite element simulation of LCF behavior. The plastic modulus formulation is coupled with the isotropic/kinematic hardening rule together with the yield surface consistency condition Incremental plasticity theories is used to study the cyclic plastic stress-strain responses. The GA approach is used to optimize the isotropic/ kinematic hardening parameters of SS 316 steel. The validity of GA method is verified by comparing its simulation results with those of manual parameter determination approach available in the literature. The simulation results confirm the potentiality and efficacy of the Genetic algorithm.

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How to Cite
, J. S. (2018). Kinematic Hardening Parameters Identification with Finite Element Simulation of Low Cycle Fatigue using Genetic Algorithm Approach. International Journal on Recent and Innovation Trends in Computing and Communication, 6(6), 218–226. https://doi.org/10.17762/ijritcc.v6i6.1661
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