P7UC2022 - Thermal exchange and friction coefficients optimization of the numerical modeling of hot rolling

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Authors:

Corentin Pondaven, R&D Engineer, ABS Centre Métallurgique

Journal / Event:

pSeven User Conference 2022

Abstract:

The hot rolling of long steel products is a forming process used to provide the final cross section of rolled bars suited to further manufacturing processes. During this process, the microstructure is refined and the defects generated during the casting of steel such as shrinkage pore are reduced. The finite element modeling of this process is useful to reduce the trial phase necessary to elaborate an industrial rolling sequence suited to the requirements of customers in terms of product soundness and mechanical properties. To reach this objective, the boundary conditions of the model need to be carefully identified to ensure its ability to correctly model the thermomechanical fields involved in the rolled bloom. In the current study, pSeven is used to optimize the thermal exchange and the friction coefficients of the rolling model of the Rotoforgia rolling mill of ABS. The simulation model is built using the FORGE software and the optimization procedure is based on the minimization of the difference between simulated and measured rolling forces. The workflow implemented in pSeven is using a surrogate-based optimization approach to explore the defined design space and then optimize the response of the simulation. During the workflow, the setting up of the thermal exchanges and friction coefficients in FORGE and the running of the simulations are fully automated by pSeven. The post-processing phase is automatized as well. During this step, the mean rolling force of each stand of the rolling sequence and other process parameters such as the surface temperature are extracted. Using this approach, a large combination of entry parameters is tested without configuring each simulation case individually. The required storage space is also limited to only one computed case at once for the whole study. The use of computation resources is thus optimized, and the large computation time needed can be executed as background tasks. Using this approach, the performances of the simulation model are improved after 75 runs of the computation.

Keywords: P7UC2022, Industrial Equipment, Metallurgy, Optimization