(65a) Determination of Effective Transport Parameters from Particle-Resolved CFD Simulations for a Simplified Fixed-Bed Reactor Modeling

Multitubular fixed-bed reactors are widely used in the chemical industry, esp. in the field of heterogeneous catalysis. Each module consists of a fixed-bed with a low tube-to-particle diameter ratio N and is characterized by a heterogenous packing morphology that lead to a strong interplay between local flow effects and heat and mass transfer within the system.

Particle-resolved computational fluid dynamics (CFD) is a first-principle modeling approach that has been proven to be a reliable and predictive tool to analyze the flow, temperature and species field within fixed-beds in a spatially resolved manner as recently reviewed by Jurtz et al. However, since this approach is numerically demanding it cannot be applied for the simulation of the whole multitubular system in the foreseeable future. Therefore, simplified models, e.g., a pseudo-homogeneous modelling approach, will still be the model of choice to simulate the full reactor.

These simplified models rely on the knowledge of effective transport parameter, e.g., effective thermal conductivity and dispersion coefficient. Most correlations available to estimate these parameters are either not suitable since they were developed for reactors with a high N where the impact of local flow phenomena is not that important and plug-flow assumption can be made or are simply not available for the specific particle shape that is used.

To bridge that gap it will be shown how effective transport parameters can be extracted from particle-resolved CFD simulation. The parameters can than be used in simplified models. The combination of particle-resolved CFD and simplified models is a promising approach to make CFD a design-tool for this kind of applications.

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]