Determination of plastic properties of metals by instrumented indentation using a stochastic optimization algorithm

A novel optimization approach, capable of extracting the mechanical properties of an elasto-plastic material from indentation data, is proposed. Theoretical verification is performed on two simulated configurations. The first is based on the analysis of the load–displacement data and the topography of the residual imprint of a single conical indenter. The second is based on the load–displacement data obtained from two conical indenters with different semi-angles. In both cases, a semi-analytical approach [e.g., Dao et al., Acta Mater.49, 3899 (2001) and Bucaille et al., Acta Mater.51, 1663 (2003)] is used to estimate Young’s modulus, yield stress, and strain hardening coefficient from the load–displacement data. An inverse finite element model, based on a commercial solver and a newly developed optimization algorithm based on a robust stochastic methodology, uses these approximate values as starting values to identify parameters with high accuracy. Both configurations use multiple data sets to extract the elastic-plastic material properties; this allows the mechanical properties of materials to be determined in a robust way.