Abstract
Designing efficient steel solidification methods could contribute to a sustainable future manufacturing. Current computational models, including physics-based and machine learning-based design, have not led to a robust solidification design. Predicting phase-change interface is the crucial step for steel solidification design. In the present work, we propose a simplified model for thermal radiation to be included in the phase-change equations. The proposed model forms a set of nonlinear partial differential equations and it accounts for both thermal radiation and phase change in the design. As numerical solver we implement a fully implicit time integration scheme and a Newton-type algorithm is used to deal with the nonlinear terms. Computational results are presented for two test examples of steel solidification. The findings here could be used to understand effect of thermal radiation in steel solidification. Combining the present approach with physics-based computer modeling can provide a potent tool for steel solidification design.
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Financial support provided by the Royal Society under the contract IES-R2-202078 is gratefully acknowledged.
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Moutahir, FE., Belhamadia, Y., El-Amrani, M., Seaid, M. (2022). Enhancing Computational Steel Solidification by a Nonlinear Transient Thermal Model. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13350. Springer, Cham. https://doi.org/10.1007/978-3-031-08751-6_22
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