Binary collision outcomes for inelastic soft-sphere models with cohesion

Murphy, Eric; Subramaniam, Shankar

doi:10.1016/j.powtec.2016.09.010

Cited by 15 publications

(16 citation statements)

References 66 publications

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“…The particle stiffness coefficient has been shown to play a role in recent studies . Simulations using 10 times stiffer particles than the default of our present study show that particle stiffness only marginally affects the results (see Appendix B for details).…”

Section: Resultsmentioning

confidence: 48%

The effect of liquid bridge model details on the dynamics of wet fluidized beds

Khinast

Radl

2017

AIChE Journal

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Wet fluidized beds of particles in small periodic domains are simulated using the CFD-DEM approach. A liquid bridge is formed upon particle-particle collisions, which then ruptures when the particle separation exceeds a critical distance. The simulations take into account both surface tension and viscous forces due to the liquid bridge. We perform a series of simulations based on different liquid bridge formation models: (1) the static bridge model of Shi and McCarthy, (2) a simple static version of the model of Wu et al., as well as (3) the full dynamic bridge model of Wu et al. We systematically compare the differences caused by different liquid bridge formation models, as well as their sensitivity to system parameters. Finally, we provide recommendations for which systems a dynamic liquid bridge model must be used, and for which application this appears to be less important.The work is normalized by with the particle's kinetic energy assuming it is moving with particle terminal setting velocity. [Color figure can be viewed at wileyonlinelibrary.com] AIChE Journal

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Section: Resultsmentioning

confidence: 48%

The effect of liquid bridge model details on the dynamics of wet fluidized beds

Khinast

Radl

2017

AIChE Journal

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“…To test the sensitivity of the simulation predictions over this range of rates of liquid bridge filling, we conducted simulations with instantaneous liquid bridge filling, c f = 1 and c f = 0.025 and present the results in Table . The use of stiffness scaling: stiffness scaling has been shown in previous studies to make both scalar transport and interparticle forces independent of particle softening, yet one could expect that issues could arise in systems with enduring contacts, such as below U mf or in systems with significant agglomeration. A recent paper by Murphy and Subramaniam, which appeared after the present study was completed, concluded that particle softening with or without stiffness scaling could lead to significant errors in simulations of dense particle flows with enduring contacts. Particle softening coupled with stiffness scaling was used in this study as it was found in test simulations to have only a small effect on results, while decreasing the computational cost of exploring a wide range of wetting conditions.…”

Section: Methodsmentioning

confidence: 81%

Analysis of the effect of small amounts of liquid on gas–solid fluidization using CFD‐DEM simulations

et al. 2017

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Gas-solid fluidization involving small amounts of liquid is simulated using a CFD-DEM model. The model tracks the amount of liquid on each particle and wall element and incorporates finite rates of liquid transfer between particles and pendular liquid bridges which form between two particles as well as between a particle and a wall element. Viscous and capillary forces due to these bridges are modeled. Fluidization-defluidization curves show that minimum fluidization velocity and defluidized bed height increase with Bond number (Bo), the ratio of surface tension to gravitational forces, due to cohesion and inhomogeneous flow structures. Under fluidized conditions, hydrodynamics and liquid bridging behavior change dramatically with increasing Bo, and to a lesser extent with capillary number, the ratio of viscous to surface tension forces. Bed fluidity is kept relatively constant across wetting conditions when one maintains a constant ratio of superficial velocity to minimum fluidization velocity under wet conditions. V C 2017 American Institute of Chemical Engineers AIChE J, 63: 5290-5302, 2017

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“…Additionally, it has been found that physically accurate simulations require large spring stiffness, on the order of the stiffness of actual particles (Murphy and Subramaniam, 2016a). As a result very little speed-up can be achieved through softening of the interaction without affecting the physics.…”

Section: Analysis Of Numerical Constraintsmentioning

confidence: 99%

“…3. The cohesion timescale relative to the fluid timescale is defined as (Murphy and Subramaniam, 2016a)…”

Section: Analysis Of Numerical Constraintsmentioning

confidence: 99%

Development of a gas–solid drag law for clustered particles using particle-resolved direct numerical simulation

Mehrabadi

Murphy

Subramaniam

2016

Chemical Engineering Science

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Particle-resolved direct numerical simulation (PR-DNS) is used to quantify the drag force on clustered particle configurations over the solid phase volume fraction range of 0.1 ≤ φ ≤ 0.35 and the mean slip Reynolds number range of 0.01 ≤ Re m ≤ 50. The particle configurations and flow parameters correspond to gas-solid suspensions of Geldart A particles in which formation of clusters have been reported. In our PR-DNS, we use clustered particle configurations that match cluster statistics observed in experimental studies.To generate the particle configurations, we perform discrete element method (DEM) simulations of homogeneous cooling gas (HCG) systems with cohesive and inelastic particles in the absence interstitial fluid. Clustered particle subensembles are then extracted from HCG simulations to match the statistics of cluster size distributions observed in experiments. These sub-ensembles are used for PR-DNS. It is found that the mean drag on clustered configurations decreases when compared to the drag laws for uniform particle configura- * tions. The maximum drag reduction belongs to the configuration with low solid-phase volume fraction φ = 0.1 in Stokes flow, and is about 35%. The drag reduction reduces with increase in both φ and Re m . A clustering metric is introduced to explain the behavior of the drag reduction with respect to solid-phase volume fraction. Also the behavior of the drag reduction with mean slip Reynolds number is related to the Brinkman screening length. PR-DNS results are then used to propose a clustered drag model for the range of flow parameters considered in this study. This clustered drag model provides a smooth transition between the uniform and clustered states by means of a weighting function with two model parameters.

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Binary collision outcomes for inelastic soft-sphere models with cohesion

Cited by 15 publications

References 66 publications

The effect of liquid bridge model details on the dynamics of wet fluidized beds

The effect of liquid bridge model details on the dynamics of wet fluidized beds

Analysis of the effect of small amounts of liquid on gas–solid fluidization using CFD‐DEM simulations

Development of a gas–solid drag law for clustered particles using particle-resolved direct numerical simulation

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