Abstract

Integrated computational materials engineering (ICME) is emerging as an increasingly powerful approach to integrate computational materials science tools into a holistic system and address the multiscale modeling challenges in the processing of advanced steels. This work aims at incorporating macroscopic model (finite element-based thermal model) and microscopic model (CALPHAD-based microstructure model), building an industry-oriented computational tool (MICAST) for casting of steels. Two case studies were performed for solidification simulations of tool steel and stainless steel by using the CALPHAD approach (Thermo-Calc package and CALPHAD database). The predicted microsegregation results agree with the measured ones. In addition, two case studies were performed for continuous casting and ingot casting with selected steel grades, mold geometries and process conditions. The temperature distributions and histories in continuous casting and ingot casting process of steels were calculated using in-house finite-element code which is integrated in MICAST. The predicted temperature history from the casting process simulation was exported as input data for the DICTRA simulation of solidification. The resulting microsegregation by the DICTRA simulation can reflect the microstructure evolution in the real casting process. Current computational practice demonstrates that CALPHAD-based material models can be directly linked with casting process models to predict location-specific microstructures for smart material processing.

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