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physics.comp-ph2026
Monte Carlo Physics-informed Neural Networks for Inverse Multiscale Heat Conduction Problems via the Phonon Boltzmann Transport Equation
Qingyi Lin, Chuang Zhang, Xuhui Meng +1
Inferring thermal fields and thermophysical properties from limited measurements is a fundamental challenge in micro- and nanoscale heat conduction, where the classical Fourier law…
physics.comp-ph2024
Monte Carlo Physics-informed neural networks for multiscale heat conduction via phonon Boltzmann transport equation
Qingyi Lin, Chuang Zhang, Xuhui Meng +1
The phonon Boltzmann transport equation (BTE) is widely used for describing multiscale heat conduction (from nm to m or mm) in solid materials. Developing numerical approaches…
physics.comp-ph2024
Modeling Heat Conduction with Dual-Dissipative Variables: A Mechanism-Data Fusion Method
Leheng Chen, Chuang Zhang, Jin Zhao
Many macroscopic non-Fourier heat conduction models have been developed in the past decades based on Chapman-Enskog, Hermite or other small perturbation expansion methods. These ma…