Preprint Article Version 1 This version is not peer-reviewed

Synthetic Packed-Bed Generation for CFD Simulations: Blender vs. STAR-CCM+

Version 1 : Received: 7 May 2019 / Approved: 8 May 2019 / Online: 8 May 2019 (10:00:00 CEST)

A peer-reviewed article of this Preprint also exists.

Flaischlen, S.; Wehinger, G.D. Synthetic Packed-Bed Generation for CFD Simulations: Blender vs. STAR-CCM+. ChemEngineering 2019, 3, 52. Flaischlen, S.; Wehinger, G.D. Synthetic Packed-Bed Generation for CFD Simulations: Blender vs. STAR-CCM+. ChemEngineering 2019, 3, 52.

Journal reference: ChemEngineering 2019, 3, 52
DOI: 10.3390/chemengineering3020052

Abstract

A common reactor type in the chemical and process industry is the fixed-bed reactor. Accurate modeling can be achieved with particle-resolved Computational Fluid Dynamic (CFD) simulations. However, the underlying bed morphology plays a paramount role. Synthetic bed-generation methods are much more flexible and faster than image-based approaches. In this study, we look critically at the two different bed generation methods: Discrete Element Method (DEM) (in the commercial software STAR-CCM+) and the rigid-body model (in the open-source software Blender). The two approaches are compared in terms of synthetically generated beds with experimental data of overall and radial porosity, particle orientation, as well as radial velocities. Both models show accurate agreement for the porosity. However, only Blender shows similar particle orientation than the experimental results. The main drawback of the DEM is the long calculation time and the shape approximation with composite particles.  

Subject Areas

fixed-bed reactor; blender; Discrete Element Method; CFD

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