Problem adapted Hierarchical Model Reduction for the Fokker-Planck equation
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.
Cite
@article{arxiv.1511.02073,
title = {Problem adapted Hierarchical Model Reduction for the Fokker-Planck equation},
author = {Julia Brunken and Tobias Leibner and Mario Ohlberger and Kathrin Smetana},
journal= {arXiv preprint arXiv:1511.02073},
year = {2016}
}
Comments
In proceedings of ALGORITMY 2016