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arXiv · 1511.02073

Problem adapted Hierarchical Model Reduction for the Fokker-Planck equation

Julia Brunken·Tobias Leibner·Mario Ohlberger·Kathrin Smetana
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Abstract

In this paper we introduce a new hierarchical model reduction framework for the Fokker-Planck equation. We reduce the dimension of the equation by a truncated basis expansion in the velocity variable, obtaining a hyperbolic system of equations in space and time. Unlike former methods like the Legendre moment models, the new framework generates a suitable problem-dependent basis of the reduced velocity space that mimics the shape of the solution in the velocity variable. To that end, we adapt the framework of [M. Ohlberger and K. Smetana. A dimensional reduction approach based on the application of reduced basis methods in the framework of hierarchical model reduction. SIAM J. Sci. Comput., 36(2):A714-A736, 2014] and derive initially a parametrized elliptic partial differential equation (PDE) in the velocity variable. Then, we apply ideas of the Reduced Basis method to develop a greedy-algorithm that selects the basis from solutions of the parametrized PDE. Numerical experiments demonstrate the potential of this new method.

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Julia Brunken, Tobias Leibner, Mario Ohlberger, Kathrin Smetana. 2016-02-01. Problem adapted Hierarchical Model Reduction for the Fokker-Planck equation. https://arxiv.org/abs/1511.02073

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