(638e) Particle-Resolved Simulation of Fixed-Bed Reactors Filled with Complex Particle Shapes — a Validation Study | AIChE

(638e) Particle-Resolved Simulation of Fixed-Bed Reactors Filled with Complex Particle Shapes — a Validation Study

Authors 

Jurtz, N. - Presenter, Technical University Berlin
Kraume, M., Technical University Berlin
Henkel, T., Clariant Corporation
Srivastava, U., Clariant Corporation
Syngas is the feedstock for Gas-to-Liquids Technology (GTL). Common routes for the generation of syngas are Steam Reforming (SRM), Dry Reforming (DRM) or the Partial Oxidation of Methane (CPOX). Catalytic fixed-bed reactors with a low tube-to-particle diameter ratio are widely used for this kind of applications. The heterogeneous packing morphology in this reactor type leads to local flow phenomena that significantly affect the heat and mass transfer and, therefore, the efficiency of the process itself. The choice of an appropriate particle shape can improve the overall process by optimizing the trade-off between: a high active catalytic surface, a low pressure drop, low dispersion and a good heat transfer characteristic.

As recently reviewed by Jurtz et al., particle-resolved computational fluid dynamics (CFD) has become a valuable and predictive numerical method to analyze the flow, temperature and species field as well as local reaction rates in a spatially resolved manner. However, most validation studies that have been presented in the past were limited to simple particle shapes like spheres or cylinders. More complex catalyst shapes, especially those with inner voids and/or an outer surface structure are supposed to increase the performance of the overall process. Therefore, it is of huge interest to prove that particle-resolved CFD is also predictive for this kind of complex particle shapes.

A workflow for the numerical simulation of fixed-bed reactors filled with various industrially relevant complex particle shapes will be presented. Important aspects like packing generation and meshing will be covered. Special emphasis will be given to strategies for the predictive generation of packings with a pre-defined overall bed voidage by using the Discrete Element Method (DEM). The numerical results will be validated with data taken from lab-scale experiments in terms of packing morphology and pressure drop.

Literature
Jurtz, N., Kraume, M. and Wehinger, G. (2018). Advances in fixed-bed reactor modeling using particle-resolved computational fluid dynamics (CFD). Reviews in Chemical Engineering. Published: 2018/02/02. Available at: https://doi.org/10.1515/revce-2017-0059 [Epub ahead of print]