Effect of particle shape on methanol partial oxidation in a fixed bed using CFD reactor modeling

Abstract

Particle shape is one of the most important parameters in the design and optimization of fixed‐bed processes. To address the impact of particle shape on methanol partial oxidation to formaldehyde over molybdate catalyst, packings of spheres, cylinders, rings, and trilobes are numerically generated. The generated packings are used to carry out resolved particle Computational Fluid Dynamics (CFD) simulations under industrial conditions. Pressure drop, voidage and velocity profiles, radial heat transfer, and local and overall conversion and selectivity results are presented. Despite their lower particle surface area, lower particle effectiveness and more uneven flow distribution than trilobes, and lower overall heat transfer coefficient than cylinders, rings had the best conversion and selectivity due to their balance between the factors. Three longer tubes of rings, rings and cylinders, and rings and trilobes are simulated and show a small gain in selectivity for the rings and trilobes.

A Review and Experimental Revisit of Alternative Catalysts for Selective Oxidation of Methanol to Formaldehyde

“…The kinetic models developed by Deshmukh et al [60] were incorporated into a particle resolved CFD model for a fixed bed reactor by Partopur and Dixon [74] simulating beds with a length of 0.1 m for four different kinds of pellets generated numerically (Figure 12). The simulations included local and overall conversion, selectivity, pressure drop, voidage, velocity profiles, and heat transfer.…”

Particle-Resolved Computational Fluid Dynamics as the Basis for Thermal Process Intensification of Fixed-Bed Reactors on Multiple Scales

“…As discussed, particle-resolved CFD is a valuable tool to support process intensification on the meso-scale level, e.g., by finding optimized particle shapes [4,[10][11][12] or new reactor concepts, e.g., by applying macroscopic wall structures [20,21] or using internals [19]. However, for process intensification on a macroscopic scale, e.g., by running plants under dynamic operation conditions, developing process integration strategies, or doing plant optimization, different numerical tools are necessary.…”

“…In the last few years, particle-resolved computational fluid dynamics (CFD) was heavily used by numerous authors to develop process intensification strategies with the focus on the effects on the mesoscopic pellet scale. The range of works extends from investigations of the influence of particle shape on bed morphology and fluid dynamics [2][3][4], heat transport [5][6][7][8], and mass transfer processes [9][10][11][12] to the development of novel reactor concepts, such as packed foams [13][14][15], periodic open-cell structures [16][17][18], finned reactors [19], or the use of random macroscopic wall structures [20,21]. However, particleresolved CFD is a numerically very demanding method, and its applicability is currently limited to systems with a few thousand particles [22].…”

Optimizing catalyst supports at single catalyst pellet and packed bed reactor levels: A comparison study

“…In this case, the effect of varied boundary conditions is included in the optimization, which can yield the catalyst design leading to the maximum catalyst performance at reactor level. Partopour and Dixon 15 investigated the impact of pellet shape on the catalyst performance at reactor level, and found that the pellet shape can significantly affect the conversion for methanol partial oxidation. Up to now, few works have optimized catalyst supports at reactor level, let alone compared the optimization results obtained at reactor level with these acquired at pellet level.…”