Henry Kasumba
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126
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Numerical Analysis×1Comp. Eng.×1ML×1
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2026
Physics-Informed Residuals for Adaptive Mesh Refinement in Finite-Difference PDE Solvers
The paper proposes using a Physics-Informed Neural Network (PINN) residual as an efficient, physics-guided indicator to guide adaptive mesh refinement (AMR) for classical finite-difference PDE solvers, significantly reducing required degrees of freedom.
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