DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations)

Autor:	Nastorg, Matthieu, Schoenauer, Marc, Charpiat, Guillaume, Faney, Thibault, Gratien, Jean-Marc, Bucci, Michele-Alessandro
Rok vydání:	2022
Předmět:	Computer Science - Machine Learning Computer Science - Artificial Intelligence Mathematics - Numerical Analysis
Zdroj:	Machine Learning and the Physical Sciences workshop, NeurIPS 2022, Dec 2022, New-Orleans, United States
Druh dokumentu:	Working Paper
Popis:	This paper proposes a novel Machine Learning-based approach to solve a Poisson problem with mixed boundary conditions. Leveraging Graph Neural Networks, we develop a model able to process unstructured grids with the advantage of enforcing boundary conditions by design. By directly minimizing the residual of the Poisson equation, the model attempts to learn the physics of the problem without the need for exact solutions, in contrast to most previous data-driven processes where the distance with the available solutions is minimized.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2211.11763 Zobrazit plný text záznamu View this record from Arxiv