On Multiscale Methods in Petrov-Galerkin formulation

TL;DR

This paper explores multiscale Petrov-Galerkin methods for PDEs, demonstrating their accuracy, stability, and computational efficiency, and applying them to two-phase flow simulation with mass conservation.

Contribution

It introduces a general multiscale Petrov-Galerkin framework, proves stability and accuracy preservation, and applies it to efficient flow simulation with local mass conservation.

Findings

Petrov-Galerkin methods retain convergence order.

Framework reduces computational complexity.

Application to two-phase flow with mass conservation.

Abstract

In this work we investigate the advantages of multiscale methods in Petrov-Galerkin (PG) formulation in a general framework. The framework is based on a localized orthogonal decomposition of a high dimensional solution space into a low dimensional multiscale space with good approximation properties and a high dimensional remainder space{, which only contains negligible fine scale information}. The multiscale space can then be used to obtain accurate Galerkin approximations. As a model problem we consider the Poisson equation. We prove that a Petrov-Galerkin formulation does not suffer from a significant loss of accuracy, and still preserve the convergence order of the original multiscale method. We also prove inf-sup stability of a PG Continuous and a Discontinuous Galerkin Finite Element multiscale method. Furthermore, we demonstrate that the Petrov-Galerkin method can decrease the computational complexity significantly, allowing for more efficient solution algorithms. As another application of the framework, we show how the Petrov-Galerkin framework can be used to construct a locally mass conservative solver for two-phase flow simulation that employs the Buckley-Leverett equation. To achieve this, we couple a PG Discontinuous Galerkin Finite Element method with an upwind scheme for a hyperbolic conservation law.