Numerical Analysis of the Impact of Particle Friction on Bed Voidage in Fixed‐Beds

Jurtz, Nico; Waldherr, P.; Kraume, Matthias

doi:10.1002/cite.201800190

Cited by 12 publications

(19 citation statements)

References 13 publications

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“…This may indicate that an existing calibration curve, to some extent, can also be used if particle geometry is slightly modified, for example, small changes in aspect ratio. This is in accordance with results of Jurtz et al who found for cylindrical particles only little effect of aspect ratio on bed voidage if 0.5 < h / d p < 2. Nevertheless, further experimental and numerical investigations are needed to assess the validity and accuracy when using a calibration curve for modified particle shapes, especially for those with additional outer surface structure.…”

Section: Discussionsupporting

confidence: 90%

“…It was recently shown by Jurtz et al that the effect of tamping and surface characteristics can be lumped into the static friction coefficient and that it is possible to generate packings with a desired bed voidage by using an adapted friction coefficient. Nevertheless, their investigations were limited to simple particle shapes as cylinders, hollow‐cylinders and spheres, and the question remained if a once calibrated friction factor can be used to predictively describe the bed voidage of other reactor configuration with the same type of particles.…”

Section: Discussionmentioning

confidence: 99%

“…Ookawara et al found that the static friction coefficient can be used to fine‐tune the packing density to the desired experimental value. Recently, Jurtz et al have proposed correlations to predict bed voidage as a function of tube‐to‐particle diameter ratio and static friction coefficient for spheres, cylinders, and Raschig rings. These equations can be used to pre‐calculate the friction coefficient to achieve a certain bed voidage.…”

Section: Methodsmentioning

confidence: 99%

“…Subsequently, the pressure drop is calculated and compared with experimental results. In the second part of this study, it is investigated if, in analogy to the work of Jurtz et al, it is possible to obtain a correlation for more complex catalyst shapes with a set of DEM simulations and just one filling experiment. To ensure that the correlation only accounts for frictional and vibration effects the loading device will be considered in these simulations.…”

Section: Methodsmentioning

confidence: 99%

“…It is shown that a precise representation of the bed morphology is basis for a predictive CFD simulation. Therefore, special emphasis is given to the aspect of numerical packing generation and a method is presented that improves the match between experimentally and numerically generated packings by calibrating the static friction coefficient . In industrial applications, very often special loading devices are used when the reactor is filled with particles.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Validation of pressure drop prediction and bed generation of fixed‐beds with complex particle shapes using discrete element method and computational fluid dynamics

et al. 2020

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Catalytic fixed-bed reactors with a low tube-to-particle diameter ratio are widely used in industrial applications. The heterogeneous packing morphology in this reactor type causes local flow phenomena that significantly affect the reactor performance.Particle-resolved computational fluid dynamics has become a predictive numerical method to analyze the flow, temperature, and species field, as well as local reaction rates spatially and may, therefore, be used as a design tool to develop new improved catalyst shapes. Most validation studies which have been presented in the past were limited to simple particle shapes. More complex catalyst shapes are supposed to increase the reactor performance. A workflow for the simulation of fixed-bed reactors filled with various industrially relevant complex particle shapes is presented and validated against experimental data in terms of bed voidage and pressure drop. Industrially relevant loading strategies are numerically replicated and their impact on particle orientation and bed voidage is investigated. K E Y W O R D Sbed voidage, fixed-bed reactor, numerical modeling, particle orientation, pressure drop

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Validation of pressure drop prediction and bed generation of fixed‐beds with complex particle shapes using discrete element method and computational fluid dynamics

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Workflow for computational fluid dynamics modeling of fixed‐bed reactors packed with metal foam pellets: Hydrodynamics

George

Bockelmann

Schmalhorst³

et al. 2021

AIChE Journal

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In recent years, the catalyst pellets made of open‐cell metallic foams have been identified as a promising alternative in fixed‐bed reactors. A reliable modeling tool is necessary to investigate the suitability of different foam properties and the shapes of foam pellets. In this article, a workflow for a detailed computational fluid dynamics (CFD) model is presented, which aims to study the flow characteristics in the slender packed beds made of metal foam pellets. The CFD model accounts for the actual random packing structure and the fluid flow throughout the interstitial regions is fully resolved, whereas flow through the porous foam pellets is represented by the closure equations for the porous media model. The bed structure is generated using rigid body dynamics (RBD) and the influence of the catalyst loading method is also considered. The mean bed voidage and the pressure drop predicted by the simulations show good agreement with the experimental data.

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Numerical investigation of mechanical axial dispersion in slender fixed‐beds

2021

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The description of the mixing characteristics is of fundamental interest for modeling mass transport in fixed-bed reactors. A method based on Lagrangian parcel tracking is presented to determine the axial dispersion coefficient in the mechanical dispersion regime from particle-resolved computational fluid dynamics (CFD) results. The impact of fluid dynamic entry effects and the necessary averaging length on the axial dispersion coefficient is studied, showing that the often reported dependency on the entry length is almost not existent, but a result of insufficient averaging, caused by to short bed heights. The axial dispersion coefficients are determined for different particle shapes and a novel reactor wall concept. A strong correlation is found between the relative variance of the axial velocity and the axial dispersion coefficient.

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Numerical Analysis of the Impact of Particle Friction on Bed Voidage in Fixed‐Beds

Cited by 12 publications

References 13 publications

Validation of pressure drop prediction and bed generation of fixed‐beds with complex particle shapes using discrete element method and computational fluid dynamics

Validation of pressure drop prediction and bed generation of fixed‐beds with complex particle shapes using discrete element method and computational fluid dynamics

Workflow for computational fluid dynamics modeling of fixed‐bed reactors packed with metal foam pellets: Hydrodynamics

Numerical investigation of mechanical axial dispersion in slender fixed‐beds

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