A data-free physics-informed neural network matches finite-element thermal histories of wire-arc directed energy deposition to about 7% relative L2 error, reporting up to 98.6% compute-time reduction versus a fine-mesh FEM baseline.
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Physics-informed machine learning surrogate for scalable simulation of thermal histories during wire-arc directed energy deposition
A data-free physics-informed neural network matches finite-element thermal histories of wire-arc directed energy deposition to about 7% relative L2 error, reporting up to 98.6% compute-time reduction versus a fine-mesh FEM baseline.