Optimisation based material parameter identification using full field displacement and temperature measurements

Abstract

A material parameter identification is presented for a fully thermo-mechanically coupled material model based on full field displacement and temperature measurements. The basic theory of the inverse problem is recapitulated, focusing on the choice of the objective function, proposing a new formulation, and explaining in detail the necessary numerical treatment of experimental data during the pre-processing of an identification. This includes the handling of the intrinsically different data sets of displacement (Lagrangian type) and temperature (Eulerian type). Experimental data is obtained by means of a Digital-Image-Correlation (DIC) as well as by a thermography system and three algorithmic boxes are provided for the necessary pre-processing. The experimental setup is discussed, measured data presented and analysed. From this setup, a successive approach to the identification process is motivated. Based on the experimental observations, a thermo-mechanically coupled material model is chosen, the required constitutive relations summarised and the material parameters interpreted. For the fixed choice of model and experiments, the inverse problem is solved. A very good fit was obtained for both the displacement and the temperature field. Results are interpreted and remaining errors discussed.