4.4 Article

Limits of Classical Homogenization Procedure for Coupled Diffusion-Heterogeneous Reaction Processes in Porous Media

Journal

TRANSPORT IN POROUS MEDIA
Volume 140, Issue 2, Pages 437-457

Publisher

SPRINGER
DOI: 10.1007/s11242-021-01683-2

Keywords

Diffusion-reaction; Damkohler number; Homogenization

Funding

  1. NEEDS program

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This study focuses on upscaling of coupled diffusion-heterogeneous reaction problem in porous media for different orders of magnitude of the Damkohler number. It is found that the macroscopic model accurately predicts the coupled diffusion-reaction process at the macroscale in the range of small Damkohler number under slow reaction rate conditions, while errors occur under moderate and high reaction rates. Classical homogenization technique fails to capture the complex physics at short time when chemical equilibrium is not reached.
Upscaling of coupled diffusion-heterogeneous reaction problem in porous media is developed for different orders of magnitude of the Damkohler number. At the pore-scale, the mass transfer of two dilute species is ruled by a diffusion mechanism characterized by different diffusion coefficients. The pore-scale model is completed by reversible linear reaction occurring at the solid-fluid interface. Classical homogenization technique is then used to upscale the pore-scale model under three different scenarios: slow, moderate and high reaction rates corresponding to three orders of magnitude of the Damkohler number. The results show that the macroscopic model obtained for a slow reaction rate predicts accurately the coupled diffusion-reaction process at the macroscale in the range of small Damkohler number. However, the classical homogenization procedure for moderate and high reaction rates fails to capture correctly the complex physics at short time when chemical equilibrium is not reached. In these cases, upscaled models impose strictly the chemical equilibrium at the first order due to the dominance of reaction over diffusion. Numerical simulations highlight the error of the macroscopic models compared to direct numerical simulations.

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