Kernel-based stochastic collocation for the random two-phase Navier-Stokes equations
Numerical Analysis
2019-04-12 v3
Abstract
In this work, we apply stochastic collocation methods with radial kernel basis functions for an uncertainty quantification of the random incompressible two-phase Navier-Stokes equations. Our approach is non-intrusive and we use the existing fluid dynamics solver NaSt3DGPF to solve the incompressible two-phase Navier-Stokes equation for each given realization. We are able to empirically show that the resulting kernel-based stochastic collocation is highly competitive in this setting and even outperforms some other standard methods.
Cite
@article{arxiv.1810.11270,
title = {Kernel-based stochastic collocation for the random two-phase Navier-Stokes equations},
author = {Michael Griebel and Christian Rieger and Peter Zaspel},
journal= {arXiv preprint arXiv:1810.11270},
year = {2019}
}