DEM simulation of the packing of rodlike particles

Nan, Wenguang; Wang, Yueshe; Liu, Yingwen; Tang, Huiping

doi:10.1016/j.apt.2014.12.012

Cited by 38 publications

(12 citation statements)

References 44 publications

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“…Mindlin-Dersiewicz model is used for the tangential interactions and the maximum tangential force is subject to the Coulomb's friction (Mindlin and Deresiewicz, 1953). It is noted that the combination of JKR normal contact force model and Mindlin-Dersiewicz tangential contact force model is frequently used (Nan et al, 2015;Subero et al, 1999). In addition, the energy dissipation during collisions is taken into consideration by introducing a velocity-dependent damping force.…”

Section: Discrete Element Methodsmentioning

confidence: 99%

Breakage of fractal agglomerates

Deng

Davé

2017

Chemical Engineering Science

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Section: Discrete Element Methodsmentioning

confidence: 99%

Breakage of fractal agglomerates

Deng

Davé

2017

Chemical Engineering Science

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“…Zhao et al [358] Sphero-tetrahedra 0.12-1.84 −0.75-1.000.05 to 10 -✓ ✓ --Lathan et al [359] Tetrahedra 1-1.8 --✓ ---Li et al [360] Tetrahedra 0.5-1.5 --✓ ---Niegodajew and Marek [361] Hollow cylinder 0.33-3.0 const. 0.8 -✓ ✓ -✓ Nan et al [335] Spherocylinder 5-20 -✓ ✓ ---Nan et al [362] Spherocylinder 5-50 -✓ ✓ --✓…”

Section: Source Shapementioning

confidence: 99%

Review on the structure of random packed‐beds

Seckendorff

Hinrichsen

2021

Can J Chem Eng

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Independent from their intended purpose, the understanding of structural characteristics of random packings of particles having defined shapes is important to understand and optimize fluid dynamic behaviour, heat, and mass transfer. The packing structure can be described by the coordination number, local porosity profiles, the average porosity, and pore characteristics, which are influenced by the wall and thickness effect; the material, shape, and size distribution of the packing particles; the packing and compaction mode; and the shape and material of the packing's containing walls. Therefore, existing knowledge on the structure of randomly packed mono-sized particles is reviewed to provide an updated selection of relevant parameters and their derived correlations obtained by experimental, numerical, and analytical means.packed-bed reactor, porosity, random particle packings, review, structure | INTRODUCTIONRandom packings of particles having defined shapes are deployed in all kinds of industrial applications and come in all orders of magnitude. The most prominent examples comprise micro-sized particle beds as commonly used in chromatography packed columns, [1][2][3] packed-bed reactors filled with catalytic shaped bodies having millimetre size, [4,5] packed columns used in separation processes such as distillation incorporating particles in the lower centimetre range, [6,7] and the pebble-bed reactor, which is a gas-cooled nuclear reactor, moderated by a packing of graphite spheres. [8][9][10] In addition to those, numerous less-known applications of packed-beds exist, ranging from powder-bed 3D printers, [11] solar-energy storage systems, [12] earth science, [13] civil engineering, [14,15] and pharmaceutical processing, [16] to the pyrolysis of pelletized wood fuels, [17] to name but a few.Irrespective of its intended purpose, the extent of a packed-bed is limited by a confining wall of commonly cylindrical shape, though flat plates and other container geometries are possible. Despite its generally random nature, close to this confinement the particles' placement is naturally forced to align with the wall's geometry. This imposed order reaches a couple of particle diameters into the packing and is usually named the wall effect. Its influence on the overall packed-bed characteristics decreases with increasing tube-to-particle diameter ratio λ = D d p . While most applications operate in an only sparsely affected λ-range, this effect becomes dominant, for instance, in catalytic multitubular reactors, typically performing at λ = 4-7 [18] or a single-pellet-string reactor with a λ < 2. [19] Moreover, some packed-bed utilizations, especially chromatography columns, have very delicate requirements regarding bed homogeneity and its derived characteristics.Abbreviations: DEM, discrete element method; Erfc, error function; J 0 , Bessel function of first kind and zero order; MRJ, maximally random jammed; RCP, random close packing; RLP, random loose packing.

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“…Using the poured packing method (Nan et al, 2014;Nan et al, 2015), approximately 36,000 spheres with a uniform distribution of diameters in the size range of 0.85-1.0 mm are generated to form a packed bed with height of 52 mm corresponding to experiment with PE particles. As the initial packed bed is almost uniform and has a low porosity of 0.41, the bed preparation procedure (namely the conditioning step) is omitted in the simulations to reduce the computational time.…”

Section: Simulation Conditionsmentioning

confidence: 99%

Analysis of powder rheometry of FT4: Effect of air flow

Nan

Ghadiri

Wang

2017

Chemical Engineering Science

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Understanding of particle flow behaviour as a function of strain rate is of great interest in many items of equipment of industrial processes, such as screw conveyors, impeller mixers, and feeders, etc. The traditional commercial instruments for bulk powder flow characterisation, such as shear cells, operate at low shear strain rates, and are not representative of unit operations under dynamic conditions. In recent years, the FT4 powder rheometer of Freeman Technology has emerged as a widely used technique for characterising particle flow under dynamic conditions of shear strain rate; yet little is known about its underlying powder mechanics. We analyse the effect of gas flow on the flow behaviour of cohesionless particles in FT4 both experimentally and by numerical simulations using the combined discrete element method (DEM) and computational fluid dynamics (CFD). The results show that the effect of gas flow on the flow energy could be described by the resultant fluid-induced drag on the particles above the blade position as the impeller penetrates the bed. The strain rate in front of the blade is mainly determined by the impeller tip speed, and is not sensitive to the gas flow and particle size. The flow energy correlates well with the shear stress in front of the blade. They both increase with the strain rate and are significantly reduced by the upward gas flow.

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DEM simulation of the packing of rodlike particles

Cited by 38 publications

References 44 publications

Breakage of fractal agglomerates

Breakage of fractal agglomerates

Review on the structure of random packed‐beds

Analysis of powder rheometry of FT4: Effect of air flow

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