Reduced order CFD modeling approach based on the asymptotic expansion—An application for heterogeneous catalytic systems

Abstract

Recent experimental techniques allow to obtain atomic scale information of heterogeneous catalysts under operando conditions, but, typically require rather complex reactor geometries. To utilize this complementary information in e.g. kinetic model development, Computational Fluid Dynamics (CFD) is needed to address the non-trivial coupling of chemical kinetics and mass transport in such chambers. However, conventional CFD approaches for solving catalytic systems have a drawback of huge computational expense, incurred by trying to solve a stiff problem. In this study, we present a reduced order approach with a significantly lower computational footprint than conventional CFD. The idea behind the approach is to estimate the solution without having to directly couple the mass transport and surface kinetics. This is achieved by a lowest-order asymptotic expansion in the catalyst sample size or, equivalently, the lateral variation of gas phase concentrations above the catalytic surface. This reduces the overall simulation time by orders of magnitude, particularly for inverse problems. We demonstrate the approach for catalytic formation of Methanol from CO₂ and H₂ in a two dimensional channel flow and for different applied reaction conditions, sample sizes and catalyst loadings.