Abstract
Reactive transport within porous reactors is crucial to many diverse applications, and the efficacy of these reactors hinges on their microstructure. Mathematical modeling and optimization play a pivotal role in the exploration of efficient designs, enabling the generation of structures that may not be achievable through random realizations of packings. In this study, we propose a framework for high-resolution topological optimization of porous flow-through reactors based on pore-scale simulations using a non-dominated sorting genetic algorithm II. A pore network model for an advection–diffusion-reaction system is developed to simulate reactor performance. This model is integrated with a mathematical optimization algorithm, incorporating a background grid and Delaunay tessellation. The optimization framework generates enhanced porous structures, simultaneously maximizing conversion rates while minimizing pumping costs. Striking a balance between permeability and reactive surface area, the final designs yield a set of Pareto optimal solutions, encompassing diverse non-dominated designs with varying reaction rates and hydraulic requirements. The results demonstrate that optimal pore configurations lead to a 280% increase in conversion rates and a 6% reduction in pumping costs at one end, while on the opposite end of the Pareto front, a 15.2% increase in reaction rates and an 11.3% reduction in pumping costs are observed.
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