Griebel, MichaelMichaelGriebelRieger, ChristianChristianRiegerZaspel, PeterPeterZaspel2022-03-062022-03-062019https://publica.fraunhofer.de/handle/publica/26088810.1615/Int.J.UncertaintyQuantification.2019029228In 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 nonintrusive 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.en003004310005006518Kernel-based stochastic collocation for the random two-phase navier-stokes equationsjournal article