Parameter identification of elastoplastic materials by simulation of static and dynamic indentation tests

This work presents a numerical optimisation procedure for the identification of elastoplastic material parameters by inverse analysis, through both static and dynamic indentation tests. A Finite Element Method modelling of the indentation test is put in place, by analysing first macroscopic effects (indentation curve, residual imprint geometry) at variable constitutive parameters (elastic modulus, yield stress, hardening coefficient). The FEM solver is then linked to an optimisation routine, by assembling an integrated loop towards the solution of the inverse problem. Later, the FEM solver is replaced by a Radial Basis Function (RBF) Network interpolation of pre-calculated data, combined to a Principal Component Analysis (PCA), allowing to reduce the computational burden of each non-linear analysis. Next, a detailed study on the identification procedure is performed, by applying it to pseudoexperimental data generated numerically priory to the inverse analysis, possibly affected by random uncertainty at given variance. The reliability of the inverse procedure is then demonstrated, for both static and dynamic indentation tests, which appears to be a necessary condition for further validations based on true experimental data.