An adaptive multigrid approach for the simulation of contaminant transport in the 3D subsurface

This paper presents an adaptive multigrid approach, combining adaptive local grid refinement and multigrid methods, in conjunction with the Lagrangian-Eulerian finite element method to simulate contaminant transport in the 3D subsurface. Adaptive local grid refinement can improve solution accuracy without sacrificing computational efficiency because computer efforts are focused on the rough regions (i.e., requiring high spatial resolution) of the problem domain. To implement adaptive grids, a backward/forward particle tracking technique is applied in the Lagrangian step, and the interpolation errors of the Lagrangian concentrations are compared with prescribed error tolerances to determine rough regions. A modular setting of the grid generation is then used to generate locally zooming grids and to prepare information for applying multigrid methods. The Lagrangian concentrations of the newly generated nodes at the finest grid level are also evaluated by performing a backward tracking. Multigrid strategies which can effectively eliminate the smooth component error through coarse grid correction are finally applied in the Eulerian step to solve the matrix equations for further saving of computer time. Example problems are used to demonstrate the success of this integrated approach.