Mesh size effect on CFD simulation of gas-fluidized Geldart A particles

Sande, Priya C.; Ray, Saumi

doi:10.1016/j.powtec.2014.05.019

Cited by 26 publications

(17 citation statements)

References 45 publications

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“…A coarse grid could lead to an overprediction of the solid expansion height of the bed [23]. Sande et al [17] found that the numerical results agree well with the experimental results when the grid size is about 10 times the particle diameter and there is no improvement in capturing homogeneous expansion when the mesh is further refined. Hence, a grid size of 5 mm was chosen in this simulation.…”

Section: Simulation Setupmentioning

confidence: 81%

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An Investigation of the Restitution Coefficient Impact on Simulating Sand-Char Mixing in a Bubbling Fluidized Bed

Zhao¹,

Eri²,

Wang³

2017

Energies

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Abstract:In the present work, the effect of the restitution coefficient on the numerical results for a binary mixture system of sand particles and char particles in a bubbling fluidized bed with a huge difference between the particles in terms of density and volume fraction has been studied based on two-fluid model along with the kinetic theory of granular flow. Results show that the effect of restitution coefficient on the flow characteristics varies in different regions of the bed, which is more evident for the top region of the bed. The restitution coefficient can be categorized into two classes. The restitution coefficients of 0.7 and 0.8 can be included into one class, whereas the restitution coefficient of 0.9 and 0.95 can be included into another class. Moreover, four vortices can be found in the time-averaged flow pattern distribution, which is very different from the result obtained for the binary system with the similar values between particles in density and volume fraction.

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Section: Simulation Setupmentioning

confidence: 81%

“…Many studies [16][17][18] have studied the suitability of different drag models. Generally, the Gidaspow drag model is suitable for simulation in a dense bubbling fluidized bed.…”

Section: Introductionmentioning

confidence: 99%

An Investigation of the Restitution Coefficient Impact on Simulating Sand-Char Mixing in a Bubbling Fluidized Bed

Zhao¹,

Eri²,

Wang³

2017

Energies

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“…For the simulation, the initial hydraulic gradient was set with the water table at 0.025 and 0.09 m for the downstream side and the upstream side, respectively. According to Figure 2, the fluid achieved a relatively static condition at t = 0.5 s. In the CFD approach, the boundary was subdivided into numerous cells to capture the fluid properties, and the dimension of the mesh cell is highly related to the velocity behavior in the literature [40,41]. Benmebarek et al [41] conducted FEM simulations and found that the failure mechanism is difficult to capture using a coarse mesh.…”

Section: Radii Of Particlesmentioning

confidence: 99%

CFD–DEM Simulations of Seepage-Induced Erosion

Xiao

Wang

2020

Water

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Increases in seepage force reduce the effective stress of particles and result in the erosion of particles, producing heave failure and piping. Sheet piles/cutoff walls are often employed in dams to control the seepage. In this study, a computational fluid dynamics solver involving two fluid phases was developed and coupled with discrete element method software to simulate the piping process around a sheet pile/cutoff wall. Binary-sized particles were selected to study the impact of fine particles on the mechanisms of seepage. The seepage phenomenon mainly appeared among fine particles located in the downstream side, with the peak magnitudes of drag force and displacement occurring around the retaining wall. Based on the particle-scale observations, the impact of seepage produced a looser condition for the region concentrated around the retaining wall and resulted in an anisotropic condition in the soil skeleton. The results indicate that heave behavior occurs when the drag force located adjacent to the boundary on the downstream side is larger than the corresponding weight of the bulk soil.

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“…The domain's mesh granularity affects the solution's convergence rate while it can increase numerical stability during the simulation [39]. Coarse meshes yield concentration solutions with over-and undershoots because of the non-smooth transition of the odour-air mixture across the CVs.…”

Section: Simulationmentioning

confidence: 99%

Audio-Visual-Olfactory Resource Allocation for Tri-modal Virtual Environments

Doukakis

Debattista

Bashford-Rogers

et al. 2019

IEEE Trans. Visual. Comput. Graphics

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Virtual Environments (VEs) provide the opportunity to simulate a wide range of applications, from training to entertainment, in a safe and controlled manner. For applications which require realistic representations of real world environments, the VEs need to provide multiple, physically accurate sensory stimuli. However, simulating all the senses that comprise the human sensory system (HSS) is a task that requires significant computational resources. Since it is intractable to deliver all senses at the highest quality, we propose a resource distribution scheme in order to achieve an optimal perceptual experience within the given computational budgets. This paper investigates resource balancing for multi-modal scenarios composed of aural, visual and olfactory stimuli. Three experimental studies were conducted. The first experiment identified perceptual boundaries for olfactory computation. In the second experiment, participants (N = 25) were asked, across a fixed number of budgets (M = 5), to identify what they perceived to be the best visual, acoustic and olfactory stimulus quality for a given computational budget. Results demonstrate that participants tend to prioritize visual quality compared to other sensory stimuli. However, as the budget size is increased, users prefer a balanced distribution of resources with an increased preference for having smell impulses in the VE. Based on the collected data, a quality prediction model is proposed and its accuracy is validated against previously unused budgets and an untested scenario in a third and final experiment.

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Mesh size effect on CFD simulation of gas-fluidized Geldart A particles

Cited by 26 publications

References 45 publications

An Investigation of the Restitution Coefficient Impact on Simulating Sand-Char Mixing in a Bubbling Fluidized Bed

An Investigation of the Restitution Coefficient Impact on Simulating Sand-Char Mixing in a Bubbling Fluidized Bed

CFD–DEM Simulations of Seepage-Induced Erosion

Audio-Visual-Olfactory Resource Allocation for Tri-modal Virtual Environments

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