A New Class of High-Order Methods for Fluid Dynamics Simulations using Gaussian Process Modeling
Computational Physics
2017-05-16 v2
Abstract
We introduce an entirely new class of high-order methods for computational fluid dynamics (CFD) based on the Gaussian Process (GP) family of stochastic functions. Our approach is to use kernel-based GP prediction methods to interpolate/reconstruct high-order approximations for solving hyperbolic PDEs. We present the GP approach as a new formulation of high-order (magneto)hydrodynamic state variable interpolation that furnishes an alternative to conventional polynomial-based approaches.
Cite
@article{arxiv.1611.08084,
title = {A New Class of High-Order Methods for Fluid Dynamics Simulations using Gaussian Process Modeling},
author = {Adam Reyes and Dongwook Lee and Carlo Graziani and Petros Tzeferacos},
journal= {arXiv preprint arXiv:1611.08084},
year = {2017}
}