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Ureolytically driven calcite precipitation is a promising approach for inducing subsurface mineral precipitation, but engineered application requires the ability to control and predict precipitate distribution. To study the coupling between reactant transport and precipitate distribution, columns with defined zones of immobilized urease were used to examine the distribution of calcium carbonate precipitation along the flow path, at two different initial flow rates. As expected, with slower flow precipitate was concentrated toward the upstream end of the enzyme zone and with higher flow the solid was more uniformly distributed over the enzyme zone. Under constant hydraulic head conditions the flow rate decreased as precipitates decreased porosity and permeability. The hydrolysis/precipitation zone was expected to become compressed in the upstream direction. However, apparent reductions in the urea hydrolysis rate and changes in the distribution of enzyme activity, possibly due to CaCO3 precipitate hindering urea transport to the enzyme, or enzyme mobilization, mitigated reaction zone compression. Co-injected strontium was expected to be sequestered by coprecipitation with CaCO3, but the results suggested that coprecipitation was not an effective sequestration mechanism in this system. In addition, spectral induced polarization (SIP) was used to monitor the spatial and temporal evolution of the reaction zone.

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This paper is the second part of a two part sequence on multiphysics algorithms and software. The first [1] focused on the algorithms; this part treats the multiphysics software framework and applications based on it. Tight coupling is typically designed into the analysis application at inception, as such an application is strongly tied to a composite nonlinear solver that arrives at the final solution by treating all equations simultaneously. The application must also take care to minimize both time and space error between the physics, particularly if more than one mesh representation is needed in the solution process. This paper presents an application framework that was specifically designed to support tightly coupled multiphysics analysis. The Multiphysics Object Oriented Simulation Environment (MOOSE) is based on the Jacobian-free Newton-Krylov (JFNK) method combined with physics-based preconditioning to provide the underlying mathematical structure for applications. The report concludes with the presentation of a host of nuclear, energy and environmental applications that demonstrate the efficacy of the approach and the utility of a well-designed multiphysics framework.