Pore-Scale Modeling of Mineral Growth and Nucleation in Reactive Flow

A fundamental understanding of mineral precipitation kinetics relies largely on microscopic observations of the dynamics of mineral surfaces exposed to supersaturated solutions. Deconvolution of tightly bound transport, surface reaction, and crystal nucleation phenomena still remains one of the main challenges. Particularly, the influence of these processes on texture and morphology of mineral precipitate remains unclear. This study presents a coupling of pore-scale reactive transport modeling with the Arbitrary Lagrangian-Eulerian approach for tracking evolution of explicit solid interface during mineral precipitation. It incorporates a heterogeneous nucleation mechanism according to Classical Nucleation Theory which can be turned “on” or “off.” This approach allows us to demonstrate the role of nucleation on precipitate texture with a focus at micrometer scale. In this work precipitate formation is modeled on a 10 micrometer radius particle in reactive flow. The evolution of explicit interface accounts for the surface curvature which is crucial at this scale in the regime of emerging instabilities. The results illustrate how the surface reaction and reactive fluid flow affect the shape of precipitate on a solid particle. It is shown that nucleation promotes the formation of irregularly shaped precipitate and diminishes the effect of the flow on the asymmetry of precipitation around the particle. The observed differences in precipitate structure are expected to be an important benchmark for reaction-driven precipitation in natural environments.

Pore-Scale Investigation of Coupled Two-Phase and Reactive Transport in the Cathode Electrode of Proton Exchange Membrane Fuel Cells

A three-dimensional multicomponent multiphase lattice Boltzmann model (LBM) is established to model the coupled two-phase and reactive transport phenomena in the cathode electrode of proton exchange membrane fuel cells. The gas diffusion layer (GDL) and microporous layer (MPL) are stochastically reconstructed with the inside dynamic distribution of oxygen and liquid water resolved, and the catalyst layer is simplified as a superthin layer to address the electrochemical reaction, which provides a clear description of the flooding effect on mass transport and performance. Different kinds of electrodes are reconstructed to determine the optimum porosity and structure design of the GDL and MPL by comparing the transport resistance and performance under the flooding condition. The simulation results show that gradient porosity GDL helps to increase the reactive area and average concentration under flooding. The presence of the MPL ensures the oxygen transport space and reaction area because liquid water cannot transport through micropores. Moreover, the MPL helps in the uniform distribution of oxygen for an efficient in-plane transport capacity. Crack and perforation structures can accelerate the water transport in the assembly. The systematic perforation design yields the best performance under flooding by separating the transport of liquid water and oxygen.

On Parameter Identification for Reaction-Dominated Pore-Scale Reactive Transport Using Modified Bee Colony Algorithm

Parameter identification is an important research topic with a variety of applications in industrial and environmental problems. Usually, a functional has to be minimized in conjunction with parameter identification; thus, there is a certain similarity between the parameter identification and optimization. A number of rigorous and efficient algorithms for optimization problems were developed in recent decades for the case of a convex functional. In the case of a non-convex functional, the metaheuristic algorithms dominate. This paper discusses an optimization method called modified bee colony algorithm (MBC), which is a modification of the standard bees algorithm (SBA). The SBA is inspired by a particular intelligent behavior of honeybee swarms. The algorithm is adapted for the parameter identification of reaction-dominated pore-scale transport when a non-convex functional has to be minimized. The algorithm is first checked by solving a few benchmark problems, namely finding the minima for Shekel, Rosenbrock, Himmelblau and Rastrigin functions. A statistical analysis was carried out to compare the performance of MBC with the SBA and the artificial bee colony (ABC) algorithm. Next, MBC is applied to identify the three parameters in the Langmuir isotherm, which is used to describe the considered reaction. Here, 2D periodic porous media were considered. The simulation results show that the MBC algorithm can be successfully used for identifying admissible sets for the reaction parameters in reaction-dominated transport characterized by low Pecklet and high Damkholer numbers. Finite element approximation in space and implicit time discretization are exploited to solve the direct problem.