LAUSR

Abstract The meta-modelling approach based on an adaptive sparse grid interpolator is proposed for tackling the identification problem of parametric hysteresis models for steels with different microstructures. Parametric models of Jiles-Atherton and Mel'gui, respectively, have been considered in this work. The main advantage of the present approach is the separation of the calculation procedure in a computationally demanding off-line phase, which has to be carried out only once, and a very fast on-line evaluation. This decomposition is particularly interesting when a large amount of successive evaluations has to be carried out. Especially in the case that we are interested in a particular family of ferromagnetic materials (e.g. steels subjected to different treatments), where the sought parameters are lying in a specific interval, a single meta-model may be sufficient to be used for the study of a wide range of specimens. The steel samples considered in this study have been obtained from industrially produced low carbon steel, 84% cold rolled, and isothermally annealed in laboratory.