Dedicated vertical wind tunnel for the study of sedimentation of non-spherical particles

Bagheri, Gholamhossein; Bonadonna, Costanza; Manzella, Irene; Pontelandolfo, P.; Haas, P.

doi:10.1063/1.4805019

Cited by 26 publications

(34 citation statements)

References 61 publications

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“…Finally, secondary motions become fully developed in the Newton's regime (1000 ≤ < 3 × 10 5 ). In addition, in the Newton's regime particle-to-fluid density ratio ′ can significantly affect orientation and secondary motions of particles, and therefore, the drag coefficient [21,22,23,9,46,47,33,15]. Studies on regular-shape particles show that as ′ increases, the secondary motion of particles increases too [22,23,9,33].…”

Section: Surface Roughnessmentioning

confidence: 93%

“…projected area of the particle normal to the falling (or flow) direction, [m] , , semi-axes lengths of ellipsoid, a is also the edge length of cuboctahedron, octahedron, cube or tetrahedron, [m] drag coefficient, see Eq. (15) 1−4 empirical expressions used in Eq. (6) , the drag coefficient of a sphere with same volume and Reynolds number as the particle , ℎ diameter and height of cylinder or disk, [m] diameter of a sphere with the same volume as the particle, m e elongation, / % relative error (see Eq …”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…The most challenging parameter to be determined in Eq. (1) is the drag coefficient , which is dependent on many parameters including particle Reynolds number, shape, orientation, secondary motions, particle-to-fluid density ratio, fluid turbulence intensity and particle/fluid acceleration [9,10,11,12,4,5,13,8,14,15,16]. However, parameters that have a first order influence on are particle Reynolds number, shape, particle-to-fluid density ratio and orientation [8,14,16].…”

Section: Introductionmentioning

confidence: 97%

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On the drag of freely falling non-spherical particles

2016

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We present a new general model for the prediction of the drag coefficient of non-spherical solid particles of regular and irregular shapes falling in gas or liquid valid for sub-critical particle Reynolds numbers (i.e. Re < 3 × 105). Results are obtained from experimental measurements on 300 regular and irregular particles in the air and analytical solutions for ellipsoids. Depending on their size, irregular particles are accurately characterized with a 3D laser scanner or SEM micro-CT method. The experiments are carried out in settling columns with height of 0.45 to 3.60 m and in a 4 m-high vertical wind tunnel. In addition, 881 additional experimental data points are also considered that are compiled from the literature for particles of regular shapes falling in liquids. New correlation is based on the particle Reynolds number and two new shape descriptors defined as a function of particle flatness, elongation and diameter. New shape descriptors are easy-to-measure and can be more easily characterized than sphericity. The new correlation has an average error of ~ 10%, which is significantly lower than errors associated with existing correlations. Additional aspects of particle sedimentation are also investigated. First, it is found that particles falling in dense liquids, in particular at Re > 1000, tend to fall with their maximum projection area perpendicular to their falling direction, whereas in gases their orientation is random. Second, effects of small-scale surface vesicularity and roughness on the drag coefficient of non-spherical particles found to be < 10%. Finally, the effect of particle orientation on the drag coefficient is discussed and additional correlations are presented to predict the end members of drag coefficient due to change in the particle orientation

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Section: Surface Roughnessmentioning

confidence: 93%

Section: Accepted Manuscriptmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

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On the drag of freely falling non-spherical particles

2016

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“…Tran-Cong et al [2]; Dellino et al [3]), wind tunnel testing (e.g. Bagheri et al [24]) or by compiling data from the literature, previous authors (e.g. Chhabra et al [1]; Hölzer and Sommerfeld [21]) have found different correlations between C d , Re and particle shape.…”

Section: Contents Lists Available At Sciencedirectmentioning

confidence: 97%

A new shape dependent drag correlation formula for non-spherical rough particles. Experiments and results

2015

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“…In Eq. (2) we disregard all effects due to the pressure gradient, the added mass, the Basset history and the Saffman terms, because we are considering heavy particles: ρ s /ρ g 1 (see Ferry and Balachandar, 2001;Bagheri et al, 2013). Equation (2) has a linear dependence on the fluidparticle relative velocity only when Re s 1, so that φ c 1 and the classic Stokes drag expression is recovered.…”

Section: The Multiphase Flow Modelmentioning

confidence: 99%

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

2016

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Abstract.A new fluid-dynamic model is developed to numerically simulate the non-equilibrium dynamics of polydisperse gas-particle mixtures forming volcanic plumes. Starting from the three-dimensional N-phase Eulerian transport equations for a mixture of gases and solid dispersed particles, we adopt an asymptotic expansion strategy to derive a compressible version of the first-order non-equilibrium model, valid for low-concentration regimes (particle volume fraction less than 10 −3 ) and particle Stokes number (St -i.e., the ratio between relaxation time and flow characteristic time) not exceeding about 0.2. The new model, which is called ASHEE (ASH Equilibrium Eulerian), is significantly faster than the N-phase Eulerian model while retaining the capability to describe gas-particle non-equilibrium effects. Direct Numerical Simulation accurately reproduces the dynamics of isotropic, compressible turbulence in subsonic regimes. For gas-particle mixtures, it describes the main features of density fluctuations and the preferential concentration and clustering of particles by turbulence, thus verifying the model reliability and suitability for the numerical simulation of highReynolds number and high-temperature regimes in the presence of a dispersed phase. On the other hand, Large-Eddy Numerical Simulations of forced plumes are able to reproduce the averaged and instantaneous flow properties. In particular, the self-similar Gaussian radial profile and the development of large-scale coherent structures are reproduced, including the rate of turbulent mixing and entrainment of atmospheric air. Application to the Large-Eddy Simulation of the injection of the eruptive mixture in a stratified atmosphere describes some of the important features of turbulent volcanic plumes, including air entrainment, buoyancy reversal and maximum plume height. For very fine particles (St → 0, when non-equilibrium effects are negligible) the model reduces to the so-called dusty-gas model. However, coarse particles partially decouple from the gas phase within eddies (thus modifying the turbulent structure) and preferentially concentrate at the eddy periphery, eventually being lost from the plume margins due to the concurrent effect of gravity. By these mechanisms, gas-particle non-equilibrium processes are able to influence the large-scale behavior of volcanic plumes.

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Dedicated vertical wind tunnel for the study of sedimentation of non-spherical particles

Cited by 26 publications

References 61 publications

On the drag of freely falling non-spherical particles

On the drag of freely falling non-spherical particles

A new shape dependent drag correlation formula for non-spherical rough particles. Experiments and results

ASHEE-1.0: a compressible, equilibrium–Eulerian model for volcanic ash plumes

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