Genetic algorithm based inverse analysis for functionally graded material parameters

To determine the model parameters of functionally graded material(FGM), an inverse analysis procedure based on genetic algorithm and response surface interpolation was introduced, in which the experimental records obtained from instrumented micro-indentation and their finite element analysis results were utilized. With an uncoupled manner, the finite element simulation of indentation was first conducted followed by the construction of a set of load-displacement response surfaces by a cubic Lagrange interpolation function, and then transferred to genetic algorithm for material parameter identification. This study shows that this approach inherits high accuracy from the general method based on genetic algorithm; however its solution efficiency is much higher since the large amounts of finite element calculations are substituted by interpolation on response surfaces. Numerical investigation also discloses that a double-indenter test mode can obtain a more reasonable result in comparison with the single-indenter mode for parameter identification of FGM.