Author

Lin Zhu

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Review Open access Sep 2026

Physics-Informed Machine Learning in Subsurface Multiphysics Flow Modeling: Integrating Physical Constraints for Accelerated Simulation

Subsurface thermo-hydro-mechanical (THM) coupled processes are fundamental to geomechanics, yet conventional mesh-based methods face high computational costs and limited efficiency in strongly nonlinear simulations and inverse problems. This review examines two representative physics-informed machine learning paradigms...

Lin-Chao Wang, Fei Xiong, F. Dang et al. · Buildings · 0 citations

Review Open access Aug 2026

Machine Learning-Driven Multi-Scale Modeling and Digital Twin Evolution for Geothermal Reservoirs and Underground Thermal Storage

Geothermal energy and underground thermal storage (UTES) are vital to the low-carbon energy transition, yet their optimization is bottlenecked by multi-scale heterogeneity, coupled thermal–hydraulic–mechanical–chemical (THMC) processes, and the high computational cost of full-physics simulations. This review systematic...

Xue Li, Lin Zhu, Wan Zhang et al. · Applied Sciences · 0 citations