On the application of physics informed neural networks (PINN) to solve boundary layer thermal-fluid problems
Author:
Publisher
Elsevier BV
Subject
Condensed Matter Physics,General Chemical Engineering,Atomic and Molecular Physics, and Optics
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1. Multistep asymptotic pre-training strategy based on PINNs for solving steep boundary singular perturbation problems;Computer Methods in Applied Mechanics and Engineering;2024-11
2. Thermal conductivity estimation using Physics-Informed Neural Networks with limited data;Engineering Applications of Artificial Intelligence;2024-11
3. HCP-PIGN: Efficient heat conduction prediction by physics-informed graph convolutional neural network;International Journal of Heat and Fluid Flow;2024-10
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5. Physics-informed neural network for turbulent flow reconstruction in composite porous-fluid systems;Machine Learning: Science and Technology;2024-07-31
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