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Qiang Liu

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Preprint Aug 2026

Physics-Informed Neural Networks for Biot's Model via Fixed-Stress Splitting and Energy Natural Gradient Descent

Physics-Informed Neural Networks (PINNs) have recently gained considerable attention as a mesh-free framework for solving partial differential equations. Nevertheless, their performance deteriorates when applied to strongly coupled multiphysics systems, such as Biot's consolidation model, due to severely ill-conditione...

Kexin Sun, Qiang Liu, Ming-Cheng Feng et al. · 0 citations
Open access Aug 2026

Physics-Informed Machine Learning for Smarter Design and Manufacturing Part I

Ten contributions are brought together to demonstrate how the systematic integration of physical knowledge can enhance model robustness, reduce data requirements, and improve generalization across manufacturing applications.

Jie-Wu Leng, Hui Yang, Min Xia et al. · 0 citations

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