FEA-PINN combines a physics-informed neural network with corrective finite element simulations to predict melt pool dynamics in laser powder bed fusion at accuracy comparable to full FEA but lower computational cost.
Hybrid thermal modeling of additive manufacturing processes using physics-informed neural networks for temperature prediction and parameter identification
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Physics-Informed Machine Learning Regulated by Finite Element Analysis for Simulation Acceleration of Melt Pool Dynamics in Laser Powder Bed Fusion
FEA-PINN combines a physics-informed neural network with corrective finite element simulations to predict melt pool dynamics in laser powder bed fusion at accuracy comparable to full FEA but lower computational cost.