A numerical study of bacteria transport through porous media using the green element method.

Abstract

The continued widespread contamination of the subsurface environment by microbial pathogens and chemical wastes has resulted in an increased interest in the factors that influence microbial transport through porous media. In this work a numerical study is undertaken to determine the influence of various processes that contribute to microbial transport in porous media. The evaluations were conducted by the simulation of a typical macroscopic transport model, using a novel numerical technique referred to as the Green Element Method (GEM). This computational method applies the singular boundary integral theory of the Boundary Element Method (BEM) to a discretised domain in a typical Finite Element Method (FEM) procedure. Three models are presented to evaluate the effects of the various parameters and factors: a constant porosity model was formulated to verify the GEM formulation against an analytical solution, a variable porosity linear model was developed and used for the simulation of the transport process involving first order type clogging, and a variable porosity nonlinear model used to evaluate effects of nonlinear type clogging. All three models were validated by simulations in specific applications in which analytical or deduced solutions were available. The parameters and factors evaluated included the effects of substrate concentrations, decay rates, source concentrations (boundary conditions), flow velocity, clogging rates, dispersivity, point and distributed sources, and nonlinear clogging. The results show that the trends predicted were consistent with the trends expected from theory. The conditions that enhanced bacteria transport included high velocities, low decay rate constants, high substrate concentrations, and low clogging rates. The range of dispersivities investigated showed little variation in the bacteria concentration in the longitudinal direction. Reduction in porosity resulted in retardation of the migrating plume. Conditions that led to significant loss in porosity are high bacteria loadings and high growth rates. The GEM formulation showed no restrictions or limitations in solving transient linear and transient nonlinear applications. In the nonlinear application, the Newton Raphson algorithm was successfully used for the iterative solution procedures. In addition, the GEM formulation easily facilitated the application of distributed and point sources in the problem domain.