Machine learning approximations in finite volume methods

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• Sam Lewin, Research Software Engineering, University of Cambridge
• Wednesday 20 February 2019, 13:00-14:00
• JJ Thomson Seminar Room, Maxwell Centre, Cavendish Laboratory.

If you have a question about this talk, please contact Jeffrey Salmond.

The Riemann solver is the foundation of many finite volume methods used in computational fluid dynamics (CFD). In this talk we discuss how a some of the approximations in common Riemann solvers can be improved: by constructing a neural network to estimate some of the physical quantities required to construct the approximate solution of the Riemann problem, we can achieve better performance both in accuracy and in time-to-solution.

This talk is part of the RSE Seminars series.

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