Multiscale characterization, modeling and simulation of packed bed reactor for direct conversion of syngas to dimethyl ether

Ginu R. George, Adam Yonge, Meagan F. Crowley, Anh T. To, Peter N. Ciesielski, Canan Karakaya

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This work presents a multiscale Computational Fluid Dynamics (CFD) analysis of direct DME synthesis in a packed bed reactor with physically mixed Cu/ZnO/Al2O3 and γ-Al2O3 catalysts. The model accounts for hierarchical transport behavior by coupling a one-dimensional intraparticle subgrid model to a two-dimensional (axial and radial) model for heat and mass transport along the catalyst bed, with fully integrated chemical reaction kinetics. To enhance the predictive accuracy, the model incorporates directly measured critical bed properties. X-ray computed tomography was performed at the scale of the packed bed reactor and the scale of individual catalyst particles to obtain bed properties such as bed porosity, particle diameter and permeability, as well as catalyst characteristics including intraparticle porosity and pore size. Experiments were conducted in a lab-scale reactor to validate the model, and the model predictions show good agreement with experimental data for the investigated process conditions. The validated model is further exercised to study the influence of process variables such as feed temperature, feed rate, and wall temperature. The results indicate that the pattern of hot spot formation and magnitude of hot spot temperature are sensitive to processing conditions, mainly the feed rate and reactor wall temperature. It has also been found that internal mass transport limitations exist even in smaller particles (∼215 μm), particularly in the hot spot region.

Original languageEnglish
Pages (from-to)856-874
Number of pages19
JournalRSC Sustainability
Volume3
Issue number2
DOIs
StatePublished - Jan 2 2025

Funding

This material is based upon work supported by the U.S. Department of Energy's Bioenergy Technologies Office under contract number DE-AC05-00OR22725. The research was conducted in collaboration with the Consortium for Computational Physics and Chemistry (CCPC) and the Chemical Catalysis for Bioenergy Consortium (ChemCatBio). The authors thank Technology Managers Sonia Hammache and Trevor Smith for their support and guidance. The author G. R. George thanks Dr Aditya Kashi (Computer Scientist, scalable numerical methods, Oak Ridge National Laboratory, USA) for the valuable discussion on the numerical schemes adopted in this work.

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