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Metallurgical Model Fitted to Experimental Data Using a Genetic Algorithm

The hot stamping process is an established process in the automotive industry to satisfy challenges concerning security aspects and lightweight construction. Now, innovative processes have arisen which consist in heating locally the tools and thus adjust local final mechanical properties of the parts. To simulate accurately this so called tailored tempering process, a coupling between thermal and metallurgical phenomena must be considered as the metallurgical transformations lead to a source term in the heat equation and the thermal evolution drives the transformation. To improve the model, a genetic algorithm optimizes the metallurgical model parameters to fit both the CCT and TTT diagrams, taking in account the cooling rate dependence. This method for creating a metallurgical data file, that is directly usable by the industrial software and that fits the TTT diagram and the final constituent proportions of the different constituents, is presented. This method, tested on hypothetical experimental data, is then validated and results are presented. Moreover, the principle of this work can be adapted to various softwares that industries use.