Prediction of Flow Patterns of Rotating Inclined Reactors by Using a Modified Permeability Approach. Issue 11 (11th October 2016)

• Record Type: Journal Article
• Authors: Subramanian, Kumar; Winkler, Manuel; Härting, Hans‐Ulrich; Schubert, Markus
• Other Names: Hinrichsen Kai‐Olaf sponsoringEditor.; Klemm Elias sponsoringEditor.
• Is Part Of: Chemical engineering & technology. Volume 39:Issue 11(2016:Nov.)
• Page Start: 2077
• Page End: 2086
• Publication Date: 2016-10-11
• Subjects: Computational fluid dynamics -- Multiphase flow pattern -- Reactor inclination -- Relative permeability concept -- Rotating fixed bed; Chemical engineering -- Periodicals; Chemical processes -- Periodicals; 660.05
• DOI: 10.1002/ceat.201600202
• Languages: English
• ISSNs: 0930-7516

Abstract

Abstract: A new inclined rotating tubular fixed bed reactor was recently suggested for process intensification of heterogeneous catalytic multiphase reactions. Favorable operating conditions can be achieved by operating the reactor in a wetting intermittency mode by periodic catalyst immersion in a stratified gas‐liquid flow. This flow pattern adjustment, which requires the careful selection of reactor inclination and rotation, eventually enhances the reaction rate. To predict the flow patterns by means of computational fluid dynamics, a 3D model based on the relative permeability approach was developed, in which gas and liquid phases flow concurrently downwards through the inclined rotating tubular fixed bed reactor. The model can clearly predict the four evolving patterns, depending on the operating conditions. The model was capable of correctly predicting the hydrodynamics for aqueous liquid mixtures with varying viscosity and surface tension. Abstract : A new type of reactor concept, a rotating inclined fixed bed reactor, leads to improvements in heterogeneous catalytic multiphase reactions. A comparison between experimental data and modeling by a computational fluid dynamics approach reveals that the model accurately predicts flow patterns. The model can be used to determine optimum operating conditions for various systems.