Computational study of flow and heat transfer in fixed beds with cylindrical particles for low tube to particle diameter ratios

Performance analysis, statistical modeling, and multiple response optimization of a novel fixed-bed quartz reactor packed with Ba-Pt@γ-AL2O3 using response surface methodology

In the present study, a novel fixed-bed continuous reactor with a preheating chamber was designed to be utilized for the practical application of removal studies of dangerous pollutants, especially NOX removal by NOX Storage Reduction (NSR) catalysts on a laboratory scale. The reactor's design and operational parameters, including outer wall temperature (50-600 °C), volumetric flow rate (0.3-3 L/min), wall temperature time (0.16-10 min), and granule surface area inside the preheating chamber (0-270 cm2), were statistically modeled and optimized using Response Surface Methodology (RSM). For more logical and effective parameter optimization, the ratio of gas and catalyst temperatures and pressure drop to the reactor outer wall temperature (GT/ROWT, CT/ROWT, and PD/ROWT) were also included in the optimization process. Experimental results showed that gas temperature, catalyst temperature, and pressure drop ranged from 31 to 177 °C, 51-585 °C, and 7-153 Pa, respectively. Optimal conditions were determined to be an outer wall temperature of 230 °C, a volumetric flow rate of 3 L/min, a wall temperature time of 0.16 min, and a granule surface area of 67.3 cm2. The results demonstrated that outer wall temperature, flow rate, time, and surface area of granules have significant and interaction effects on the responses and should be considered when researchers assess the removal efficiency of thermal catalysts.

Effect of Packing Structure Evolution on the Flow Characteristics in a Binary Composite Packed Bed Based on DEM-CFD Method

The evolution of mesoscale structures of particle packing in binary composite packed beds and their effects on flow characteristics and wall effects were investigated using the discrete element method (DEM) and computational fluid dynamics (CFD). The DEM model was used to build a series of randomly mixed packing structures of particles in accordance with the dynamic change of mass ratio between particles in two size ranges, which were then confirmed by the findings of an X-ray tomography (CT) scan. The results show that the packing structure of b25s75 was conducive to reducing the influence of wall effect in packed bed reactors. For b25s75, the dimensionless distance of radial porosity fluctuation from the wall is 0.3705, which is the smallest among the five packing models, indicating that this structure plays a suppressive role on the wall effect. In addition, the uniformity of velocity and temperature distributions in both the radial and axial directions of different packing structures were compared. The standard deviations of radial relative velocity distributions in the packed beds of b100, b75s25, b25s75 and s100 are 0.28, 0.178, 0.139 and 0.156, respectively, indicating that the stacking mode of b25s75 can make the fluid flow and the gas–solid interactions more uniform.

Research on a New Drag Force Model for Cylindrical Particles in Fixed Bed Reactors

Fixed bed reactors play an important role in converting solid wastes to high-quality products. The solid wastes, as well as the corresponding catalysts, are often made into cylindrical particles. However, research on the drag force for cylindrical particles is still rarely reported. In this work, the fixed bed porosity was firstly predicted with the unresolved CFD-DEM method and validated against experimental data. Then, the Ergun model, Di Felice model, and Ganser model were evaluated against the reported pressure drop data for both the spherical and cylindrical particles, so that a more solid drag force theory could be selected as a candidate for cylindrical particles. Finally, a new Ganser model was proposed for cylindrical particle drag force prediction based on the reported experimental results and validated by other experimental data. It was found that, for the spherical particle bed, the relative prediction errors of the Di Felice model are approximately 10%, while those of the Ergun model are approximately 15%. For the cylindrical particle bed, the relative prediction errors of the Ganser model are approximately 10%, while those of the Di Felice model are much higher than 10%. With the new Ganser model proposed in this work, the maximum error between the predicted pressure drop and the experimental data can be lowered to approximately 5%. The research is of reference value for drag force model selection when simulating similar FBRs with cylindrical particles.

CFD simulation of the ethylbenzene dehydrogenation reaction in the fixed bed reactor with a cylindrical catalyst of various sizes

In this paper, the Discrete Element Method of simulation was used to study the catalytic granule size effect on the efficiency of a bed reactor for the ethylbenzene dehydrogenation reaction. The model constructed for the laboratory experiment was made of catalyst granules of lengths 3, 6 and 9 mm, and diameters 2.8, 3, and 3.2 mm. A detailed evaluation of the catalyst total surface area and porosity effect was conducted owing to the analysis of particles size effect on the packing. Different results were observed for a wide feed gas mixture rate. Calculations performed allowed to deduce dependences of the reaction product concentration, the pressure drops, and the reactor productivity for all the particle sizes investigated.

Computational Fluid Dynamics for Fixed Bed Reactor Design

Flow, heat, and mass transfer in fixed beds of catalyst particles are complex phenomena and, when combined with catalytic reactions, are multiscale in both time and space; therefore, advanced computational techniques are being applied to fixed bed modeling to an ever-greater extent. The fast-growing literature on the use of computational fluid dynamics (CFD) in fixed bed design reflects the rapid development of this subfield of reactor modeling. We identify recent trends and research directions in which successful methodology has been established, for example, in computer generation of packings of complex particles, and where more work is needed, for example, in the meshing of nonsphere packings and the simulation of industrial-size packed tubes. Development of fixed bed reactor models, by either using CFD directly or obtaining insight, closures, and parameters for engineering models from simulations, will increase confidence in using these methods for design along with, or instead of, expensive pilot-scale experiments.

Computational Investigation of Liquid Holdup and Wetting Efficiency Inside Trickle Bed Reactors with Different Catalyst Particle Shapes

Liquid holdup and wetting efficiency are essential parameters for design of trickle bed reactors. Both parameters play an important role in reactor performance including pressure drop, conversion, and heat transfer. Empirical formulas are usually employed to calculate liquid holdup and wetting efficiency. However, factors such as particle shape and the wetting ability of liquid on the particle surface are not described clearly in traditional formulas. In this paper, actual random packing was built by DEM and CFD simulations were performed to investigate the factors affecting liquid holdup and wetting efficiency in trickle bed reactors, including particle shape, surface tension, contact angle, liquid viscosity, liquid density, liquid, and gas superficial velocity. Detailed fluid flow and liquid-solid interaction were described by VOF model. Four different particle shapes were investigated. It showed the particle shape has great effect and the 4-hole cylinder packing gained both highest liquid holdup and wetting efficiency. The overall simulations gave a detailed description of phase interactions and fluid flow in the voids between catalyst particles and these results could give further guidance for the design and operation of trickle bed reactors.