arXiv Analytics

Sign in

arXiv:1905.09023 [math.NA]AbstractReferencesReviewsResources

A bi-fidelity method for the multiscale Boltzmann equation with random parameters

Liu Liu, Xueyu Zhu

Published 2019-05-22Version 1

In this paper, we study the multiscale Boltzmann equation with multi-dimensional random parameters by a bi-fidelity stochastic collocation (SC) method developed in [A. Narayan, C. Gittelson and D. Xiu, SIAM J. Sci. Comput., 36 (2014); X. Zhu, A. Narayan and D. Xiu, SIAM J. Uncertain. Quantif., 2 (2014)]. By choosing the compressible Euler system as the low-fidelity model, we adapt the bi-fidelity SC method to combine computational efficiency of the low-fidelity model with high accuracy of the high-fidelity (Boltzmann) model. With only a small number of high-fidelity asymptotic-preserving solver runs for the Boltzmann equation, the bi-fidelity approximation can capture well the macroscopic quantities of the solution to the Boltzmann equation in the random space. A priori estimate on the accuracy between the high- and bi-fidelity solutions together with a convergence analysis is established. Finally, we present extensive numerical experiments to verify the efficiency and accuracy of our proposed method.

Related articles: Most relevant | Search more
arXiv:1910.09080 [math.NA] (Published 2019-10-20)
Error estimate of a bi-fidelity method for kinetic equations with random parameters and multiple scales
arXiv:2505.03360 [math.NA] (Published 2025-05-06)
Hierarchical dynamic domain decomposition for the multiscale Boltzmann equation
arXiv:1808.09379 [math.NA] (Published 2018-08-28)
A transport-based multifidelity preconditioner for Markov chain Monte Carlo