Jinhui Yan
Water quenching is a widely employed heat treatment technique to produce high-quality metallic components with desired properties. It is crucial to model the temperature distribution and assess its impact on residual stress and distortion to ensure the quality of quenched parts. However, quenching is a complex, multi-scale, and multi-physics problem involving many interplay phenomena, such as rapid evaporation, condensation, and thermal-mechanical interactions. The physical complexity makes developing an accurate and efficient quenching model to achieve this objective a significant challenge. This paper presents a coupled data-physics thermo-mechanical simulator (DPTMS) for quenching processes. DPTMS is built on a data-physics coupling framework, which leverages physics-informed machine learning and finite element method techniques to address the intricacies of quenching modeling effectively.
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title={2026 Xu DPTMS Quenching Process},
author={Jinhui Yan},
year={2026},
language={en}
}TY - JOUR TI - 2026 Xu DPTMS Quenching Process AU - Jinhui Yan PY - 2026 LA - en ER -
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