Semi-automatic optimization of steel heat treatments for achieving desired microstructure
Pohjonen, Aarne; Javaheri, Vahid; Paananen, Joni; Pyykkönen, Juha (2021-03-03)
Pohjonen, Aarne; Javaheri, Vahid; Paananen, Joni; Pyykkönen, Juha (2020) Semi-automatic optimization of steel heat treatments for achieving desired microstructure. In: E. Juuso, B. Lie, E. Dahlquist & J. Ruuska (Eds.), Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020, Virtual Conference, Finland, 22-24 September 2020. Linköping electronic conference proceedings, 176, 139-145. https://doi.org/10.3384/ecp20176139
© 2020 The authors. Creative Commons Attribution 4.0 (CC-BY) licence.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe202103197896
Tiivistelmä
Abstract
The thermo-mechanical processing history together with the steel composition defines the final microstructure, which in turn produces the macroscopic mechanical properties of the final product. In many industrial processes it is therefore of paramount importance to find the optimal thermal path that produces the desired microstructure. In the current study an optimization method has been developed to calculate the optimal thermal path for producing desired amounts of microstructural constituents (ferrite, bainite, martensite) of a medium carbon, low-alloy steel, and a low carbon microalloyed steel. The optimization is performed for two separate industrial processes: induction hardening of a pipeline steel and a water cooling of hot rolled steel strip. The optimization workflow consists of first setting the desired amounts of microstructural constituents, and subsequent optimization of the thermal path, which produces these desired amounts. For the water cooling of a steel strip we additionally employed previously developed tool to calculate the cooling water fluxes that are needed to realize the optimized cooling path in water cooling line after hot rolling. To demonstrate the applicability of the method, we present results that were obtained for different case studies related to the industrial processes.
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