Geometric Multigrid Methods for Flow Problems in Highly Heterogeneous Porous Media

In this dissertation, we develop geometric multigrid methods for the finite element approximation of flow problems (e:g:, Stokes, Darcy and Brinkman models) in highly heterogeneous porous media. Our method is based on H^(div)-conforming discontinuous Galerkin methods and the Arnold-Falk-Winther (AFW) type smoothers. The main advantage of using H^(div)-conforming elements is that the discrete velocity field will be globally divergence-free for incompressible fluid flows. Besides, the smoothers used are of overlapping domain decomposition Schwarz type and employ a local Helmholtz decomposition. Our flow solvers are the combination of multigrid preconditioners and classical iterative solvers. The proposed preconditioners act on the combined velocity and pressure space and thus does not need a Schur complement approximation. There are two main ingredients of our preconditioner: first, the AFW type smoothers can capture a meaningful basis on local divergence free subspace associated with each overlapping patch; second, the grid operator does not increase the divergence from the coarse divergence free subspace to the fine one as the divergence free spaces are nested. We present the convergence analysis for the Stokes' equations and Brinkman's equations ( with constant permeability field ), as well as extensive numerical experiments. Some of the numerical experiments are given to support the theoretical results. Even though we do not have analysis work for the highly heterogeneous and highly porous media cases, numerical evidence exhibits strong robustness, efficiency and unification of our algorithm

Final report on the Copper Mountain conference on multigrid methods

The Copper Mountain Conference on Multigrid Methods was held on April 6-11, 1997. It took the same format used in the previous Copper Mountain Conferences on Multigrid Method conferences. Over 87 mathematicians from all over the world attended the meeting. 56 half-hour talks on current research topics were presented. Talks with similar content were organized into sessions. Session topics included: fluids; domain decomposition; iterative methods; basics; adaptive methods; non-linear filtering; CFD; applications; transport; algebraic solvers; supercomputing; and student paper winners

Efficient d-multigrid preconditioners for sparse-grid solution of high-dimensional partial differential equations

Fast and efficient solution techniques are developed for high-dimensional parabolic partial differential equations (PDEs). In this paper we present a robust solver based on the Krylov subspace method Bi-CGSTAB combined with a powerful, and efficient, multigrid preconditioner. Instead of developing the perfect multigrid method, as a stand-alone solver for a single problem discretized on a certain grid, we aim for a method that converges well for a wide class of discrete problems arising from discretization on various anisotropic grids. This is exactly what we encounter during a sparse grid computation of a high-dimensional problem. Different multigrid components are discussed and presented with operator construction formulae. An option-pricing application is focused and presented with results computed with this method

An Efficient and Robust Method for Simulating Two-Phase Gel Dynamics

We develop a computational method for simulating models of gel dynamics where the gel is described by two phases: a networked polymer and a fluid solvent. The models consist of transport equations for the two phases, two coupled momentum equations, and a volume-averaged incompressibility constraint, which we discretize with finite differences/volumes. The momentum and incompressibility equations present the greatest numerical challenges since (i) they involve partial derivatives with variable coefficients that can vary quite significantly throughout the domain (when the phases separate), and (ii) their approximate solution requires the “inversion” of a large linear system of equations. For solving this system, we propose a box-type multigrid method to be used as a preconditioner for the generalized minimum residual (GMRES) method. Through numerical experiments of a model problem, which exhibits phase separation, we show that the computational cost of the method scales nearly linearly with the number of unknowns and performs consistently well over a wide range of parameters. For solving the transport equation, we use a conservative finite-volume method for which we derive stability bounds

Numerical solution of steady-state groundwater flow and solute transport problems: Discontinuous Galerkin based methods compared to the Streamline Diffusion approach

In this study, we consider the simulation of subsurface flow and solute transport processes in the stationary limit. In the convection-dominant case, the numerical solution of the transport problem may exhibit non-physical diffusion and under- and overshoots. For an interior penalty discontinuous Galerkin (DG) discretization, we present a $h$-adaptive refinement strategy and, alternatively, a new efficient approach for reducing numerical under- and overshoots using a diffusive $L^2$-projection. Furthermore, we illustrate an efficient way of solving the linear system arising from the DG discretization. In $2$-D and $3$-D examples, we compare the DG-based methods to the streamline diffusion approach with respect to computing time and their ability to resolve steep fronts

Iterative solution to the biharmonic equation in mixed form discretized by the Hybrid High-Order method

We consider the solution to the biharmonic equation in mixed form discretized by the Hybrid High-Order (HHO) methods. The two resulting second-order elliptic problems can be decoupled via the introduction of a new unknown, corresponding to the boundary value of the solution of the first Laplacian problem. This technique yields a global linear problem that can be solved iteratively via a Krylov-type method. More precisely, at each iteration of the scheme, two second-order elliptic problems have to be solved, and a normal derivative on the boundary has to be computed. In this work, we specialize this scheme for the HHO discretization. To this aim, an explicit technique to compute the discrete normal derivative of an HHO solution of a Laplacian problem is proposed. Moreover, we show that the resulting discrete scheme is well-posed. Finally, a new preconditioner is designed to speed up the convergence of the Krylov method. Numerical experiments assessing the performance of the proposed iterative algorithm on both two- and three-dimensional test cases are presented

SciCADE 95: International conference on scientific computation and differential equations

This report consists of abstracts from the conference. Topics include algorithms, computer codes, and numerical solutions for differential equations. Linear and nonlinear as well as boundary-value and initial-value problems are covered. Various applications of these problems are also included