Research Papers: Fundamental Issues and Canonical Flows

Experimental Investigation on the Motion of Particle Cloud in Viscous Fluids

[+] Author and Article Information
Amir H. Azimi

Department of Civil Engineering,
Lakehead University,
Thunder Bay, ON P7B 5E1, Canada
e-mail: azimi@lakeheadu.ca

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received April 16, 2018; final manuscript received August 3, 2018; published online September 10, 2018. Assoc. Editor: Wayne Strasser.

J. Fluids Eng 141(3), 031202 (Sep 10, 2018) (14 pages) Paper No: FE-18-1273; doi: 10.1115/1.4041121 History: Received April 16, 2018; Revised August 03, 2018

Laboratory experiments were conducted to study the dynamics of particle clouds in viscous fluids. Different shapes of frontal head and trailing stems were observed, and particle clouds were classified using data mining methodology. The stability of the frontal head of particle clouds was found to be correlated with the nozzle diameter and mass of sand particles in the form of an initial aspect ratio. The formation of particle clusters into a torus and the split of the frontal head into two or three clusters were investigated in detail. The cluster of particles flow through viscous fluid experienced partial separation due to the release of air bubbles from the rear of frontal head. It was observed that the time and location of major particle separation increase linearly with the aspect ratio. The oscillatory motion of the frontal head, caused by an uneven release of air bubbles from the rear of the frontal head, was found to be correlated with the initial aspect ratio. Both amplitude and wavelength exhibited a linear relationship with nondimensional time. The average drag coefficient of particle clouds Cd in viscous fluids was calculated for different aspect ratios, and the results were compared with the drag coefficient of individual particles. It was found that the averaged drag coefficients of particle clouds were smaller than the drag coefficient of individual particles, and Cd slightly increases with the increasing initial aspect ratio.

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Fig. 1

Correlation of the plume Richardson number (Ri = 1/Fr2) and Reynolds number Re for particle cloud in viscous fluid. Correlations of Ri with Re for single-phase laminar starting plume (dashed line) and dense suspension jets with nondimensional relative viscosity of 93 (solid line), and turbulent jets passing through immiscible layer (dotted line) were added for comparison.

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Fig. 2

Regime classification of particle cloud based on the cloud Reynolds number Rep and the ratio of cloud diameter to the particle size do/D50. Regime I is the Stokes cloud, regime II is the macroscale inertia, regime III is the microscale inertia, and regime IV is the turbulent thermal.

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Fig. 3

Schematic of experimental setup and cylindrical coordinate system

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Fig. 4

Effects of nozzle size on evolution of transient particle clouds with time. Images indicate the separation and sinusoidal motion of the frontal head. The time interval between each adjacent image is 0.25 s. The initial sand mass for all tests is 10 g: (a) test S13, L/do= 23.4, Fr = 0.91; (b) test M9, L/doi = 8.1, Fr = 0.84; and (c) test L12, L/do = 2.4, Fr = 0.69.

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Fig. 5

Effect of sand mass on formation of transient oily sand cloud for the M-series (i.e., do = 10.1 mm). All images were taken 1 s after the release: (a) test M1, L/do = 0.8; (b) test M2, L/do = 1.6; (c) test M3, L/do = 2.4; (d) test M5, L/do = 4.1; (e) test M7, L/do = 5.7; (f) test M9, L/do = 8.1; (g) test M15, L/do = 12.2; (h) test M16, L/do = 16.2; (i) test M17, L/do = 20.3; and (j)test M18, L/do = 24.3.

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Fig. 6

Snapshot images of sand particles passing through oil to form transient particle cloud: (a) stable regime: test L17, L/do = 7.3, Fr = 0.94; (b) unstable regime: test M3, L/do = 2.4, Fr = 0.55; (c) unstable regime: test S12, L/do = 16.3, Fr = 0.82; (d) split regime: test S13, L/do = 23.4, Fr = 0.91; (e) sinusoidal regime: test L12, L/do = 2.4, Fr = 0.69; (f) partial particle separation regime: test L14, L/do = 3.6, Fr = 0.74; (g) moderate particle separation regime: test L15, L/do = 4.9, Fr = 0.80; and (h) complete particle separation regime: test S22, L/do = 35, Fr = 1.09

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Fig. 7

Boundary visualization of various shapes of oily particle cloud at different times. Naïve Bayes model was employed for boundary classification in Weka software package: (a) effect of nozzle diameter on oil particle cloud classification and (b) effects of the pipe aspect ratio L/do on classification of oily particle cloud.

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Fig. 8

Effects of sand mass and nozzle size on variations of the ratio of Weber number We to Bond number Bo

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Fig. 9

Effect of aspect ratio L/do on variation of normalized penetration distance with normalized time

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Fig. 10

Variations of the normalized time with normalized penetration distance for particle cloud in water and viscous fluid

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Fig. 11

Effects of pipe aspect ratio L/do on correlation of the normalized cloud width b/do with the normalized longitudinal distance from the nozzle x/do

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Fig. 12

Effect of pipe aspect ratio L/do on the major particle separation of particle clouds in oil: (a) variations of the normalized separation time ts/T with L/do and (b) variations of the normalized separation location xs/T with L/do

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Fig. 13

Development of the trailing instability of oily particle cloud with time: (a) growth of the normalized amplitude a/do of the sinusoidal trailing motion of particle clouds with normalized time t/T and (b) growth of the normalized wavelength λ/do of the sinusoidal trailing motion of particle clouds with normalized time t/T

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Fig. 14

Schematic diagram of force balance to calculate drag coefficient of oily particle cloud and cylindrical coordinate system

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Fig. 15

Grouping effects and drag reduction in oily particle cloud. Variations of drag coefficient with particle Reynolds number for L-Series (do = 15.1 mm).



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