Steel ingot casting crack prediction criterion method based on numerical simulation

By constructing three-dimensional geometric models and numerical simulations, combining metal solidification and thermal cracking theories, a thermal crack prediction model is established, and the prediction problem of thermal cracks during the casting of large special steels is solved, and accurate thermal crack prediction and process optimization are achieved.

CN120277947APending Publication Date: 2025-07-08SHANGHAI JIAOTONG UNIV +1
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Patent Information

Application Number
CN202510347612.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-21
Publication Date
2025-07-08

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Abstract

The invention discloses a steel ingot casting crack prediction criterion method based on numerical simulation, and relates to the field of casting numerical simulation, and the method comprises the following steps: building a three-dimensional geometric model of a casting and a mold to be tested, and building a simulation model according to actual production conditions; performing numerical simulation on the solidification process of the to-be-tested casting to obtain data in the casting process of the to-be-tested casting; key parameters of a hot crack initiation position in the simulation model are determined, and a hot crack prediction model is established; according to a simulation analysis result, parameters are adjusted, and the hot crack prediction model is optimized; and performing hot crack prediction according to the optimized hot crack prediction model. According to the metal solidification theory and the heat crack theory, important characteristics of induced cracking are analyzed through finite element simulation results, heat crack prediction results are visualized through cloud picture results, criterion output results are better detected in real time, heat cracks under the current experimental scheme can be predicted, related process optimization can be guided, and the method is suitable for large-scale popularization and application. And the expansibility is high.
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