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arXiv · 2609.32358

Application of Machine Learning to the Computation of Parameters in the SUPG Method for Unstructured and Anisotropic Meshes

Petr Knobloch·Manoj Prakash
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Abstract

Solution of convection-dominated problems using stabilized methods often requires to specify stabilization parameters whose optimal choice is not known but which considerably influence the quality of the approximate solution. In a recent work of the authors, an approach for computing these parameters by machine learning was proposed and applied to the streamline upwind/Petrov-Galerkin (SUPG) method for convection-diffusion equations. In the present paper, this approach is studied numerically for unstructured meshes and extended to meshes obtained by anisotropic mesh adaptation.

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Petr Knobloch, Manoj Prakash. 2026-09-26. Application of Machine Learning to the Computation of Parameters in the SUPG Method for Unstructured and Anisotropic Meshes. https://arxiv.org/abs/2609.32358

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