LSTM-PINN uses memory mechanisms to preserve consistency across heat, fluid, and electric fields in electrothermal transport, outperforming standard PINNs on complex convective regimes.
Physics-informed neural network for real-time thermal modeling of large-scale borehole thermal energy storage systems.Energy, 315:134344
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LSTM-PINN for Steady-State Electrothermal Transport: Preserving Multi-Field Consis tency in Strongly Coupled Heat and Fluid Flow
LSTM-PINN uses memory mechanisms to preserve consistency across heat, fluid, and electric fields in electrothermal transport, outperforming standard PINNs on complex convective regimes.