Abstract
The aim of this work was to improve the previously developed model of austenite-ferrite phase transformation by its identification for selected steels and by performing sensitivity analysis. Created model allows prediction of phase transformation kinetics for non-isothermal conditions. Model is characterized by very short computing time and relatively good predictive capabilities. There are five input coefficients in the model, which should be identified for each steel on the basis of dilatometric tests. In the previous works model was used to predict phase transformation kinetics in various DP steels for different thermal cycles. In the first part of this work sensitivity analysis of the model was performed using three methods: quality method, factorial design method and Morris analysis method. Obtained sensitivity coefficients described how changes of the model input parameters influence the response of the model and which of these parameters are the most significant. The second part of the work was devoted to model identification for the selected steels. Identification problem was turned into optimization task which was solved using Hooke-Jeeves method. Obtained model’s parameters allowed describing austenite-ferrite phase transformation in the conditions of varying temperatures. Validation of the model was performed by comparison with the results obtained from the advances numerical model based on the solution of the diffusion equation in the austenite. Results obtain from both models for typical thermal cycled used to obtain multiphase microstructure were compared.