ON THE DRAG COEFFICIENT OF NON- SPHERICAL PARTICLES -...

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ON THE DRAG COEFFICIENT OF NON- SPHERICAL PARTICLES Gholamhossein Bagheri 1 Costanza Bonadonna 1 Irene Manzella 1 Piero Pontelandolfo 2 Pierre Vonlanthen 3 Patrick Haas 2 1 Section of Earth Science, University of Geneva, Switzerland 2 hepia/CMEFE, Geneva, Switzerland 3 Institut des sciences de la Terre, Lausanne, 1015, Switzerland

Transcript of ON THE DRAG COEFFICIENT OF NON- SPHERICAL PARTICLES -...

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ON THE DRAG COEFFICIENT OF NON-SPHERICAL PARTICLES Gholamhossein Bagheri1

Costanza Bonadonna1 Irene Manzella1 Piero Pontelandolfo2

Pierre Vonlanthen3 Patrick Haas2 1Section of Earth Science, University of Geneva, Switzerland 2hepia/CMEFE, Geneva, Switzerland 3Institut des sciences de la Terre, Lausanne, 1015, Switzerland

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Outline

 Introduction

 objectives  Methodology

 Analytical solutions (Re << 1)

 Settling columns (10 < Re < 103)

 Vertical wind tunnel (103 < Re < 105)

 Results

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Particle size and shape  The most important factors to determine particle velocity and its atmospheric residence time

 Particle terminal velocity can be evaluated if its drag coefficient (CD) is known

Introduction

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Objectives  Effect of particle shape and surface vesicularity on the drag force?

 Benchmarking existing models and shape descriptors

 Presenting a new model based on easy-to-measure shape descriptors

Introduction

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Sphere drag

Methodology

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Approaching the problem

Methodology

  CD of any arbitrary shape particle at intermediate Re is a function of its CD at very low Re and very high Re

Re<<1

1000<Re<3×105

1<Re<1000

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Approaching the problem

Methodology

  In other words: CD=f (Re, K1, K2) where K1 and K2 are functions of particles shape

K1=CD/CD,Sphere

K2=CD/CD,Sphere

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Approaching the problem

Methodology

  In other words: CD=f (Re, K1, K2) where K1 and K2 are functions of particles shape

K1 = CD / CD,Sphere

K2 = CD / CD,Sphere

CD =24K1Re

(1+0.15(ReK2 / K1)0.687 )+

0.46K2

1+ 42500(ReK2 / K1)

1.16

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Approaching the problem

Methodology

Analytical solution

Wind tunnel

settling columns

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Re<<1

Methodology

  Analytical solution exists only for sphere and ellipsoid

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10<Re <103

Methodology

  Experiments in settling columns   117 particles (100 volcanic), 150 µm< diameter< 1 mm 3.6 m

0.45 m

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Particle Characterization

Samples: Settling columns

  117 particles (100 volcanic)

  150 µm < diameter< 1 mm

  SEM micro-CT and Image analysis

Bagheri et al., Powder Technology (2014), 270(A)

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104<Re <105

Methodology

  Experiments in vertical wind tunnel   177 particles (116 volcanic), 11 mm< diameter< 36 mm

Bagheri et al., Rev. Sci. Instrum. (2013), 84 (5)

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Particle Characterization

Samples: Settling columns

  177 particles (116 volcanic)

  11 mm < diameter < 36 mm

  3D laser scan and Image analysis

Bagheri et al., Powder Technology (2014), 270(A)

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Why vertical wind tunnel?

Methodology

Falling columns: A spherical particle with

diameter of 2 cm and density of 2700 kgm-3

Air (density ratio = 2700) Water (density ratio = 2.7)

324 m

0.5 m

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Particle secondary motion

Bagheri et al., Rev. Sci. Instrum. (2013), 84 (5)

100 cm

25 frame per second

Methodology: The vertical Wind tunnel

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Particle secondary motion

Methodology: The vertical Wind tunnel

Bagheri et al., Rev. Sci. Instrum. (2013), 84 (5)

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Particle secondary motion

Methodology: The vertical Wind tunnel

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Wind Tunnel setup

Bagheri et al., Rev. Sci. Instrum. (2013), 84 (5)

Methodology: The vertical Wind tunnel

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Particle tracking code

  d = 2 cm   L = 4.7 cm   m = 9.3 gr

L

d

Bagheri et al., Rev. Sci. Instrum. (2013), 84 (5)

Methodology

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Which shape descriptor correlates with K1?

Results C

D /

CD

, Sph

ere

=K1

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Which shape descriptor correlates with K1?

Results C

D /

CD

, Sph

ere

=K1

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Results C

D /

CD

, Sph

ere

=K1

Which shape descriptor correlates better with K1?

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Surface roughness effects at Re<<1

 Hill & Power theorem (1956):

Results

CD / CD, Sphere=1.04

CD / CD, Sphere=1.07

CD / CD, Sphere≈1.05

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Which shape descriptor correlates with K2?

Results C

D =

0.4

63×K

2

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Which shape descriptor correlates with K2?

Results C

D =

0.4

63×K

2

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Results C

D =

0.4

63×K

2

Which shape descriptor correlates better with K2?

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Surface roughness effect at high Re At least at high Re the effect of surface roughness is almost negligible

(< 7 %)

Rough: Without Parafilm wrap

Smooth: With Parafilm wrap

Results

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New model of CD

Results

  K1 = f ( )

  K2 = g ( )

S I L

S 3 I L2

CD =24K1Re

(1+0.15(ReK2 / K1)0.687 )+

0.46K2

1+ 42500(ReK2 / K1)

1.16

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New model of CD

Results

  K1 = f ( )

  K2 = g ( )

S I L

S 3 I L2

CD =24K1Re

(1+0.15(ReK2 / K1)0.687 )+

0.46K2

1+ 42500(ReK2 / K1)

1.16

3.6 m

0.45 m

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Intermediate Re: estimations vs. measurements

Results

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Intermediate Re: estimations vs. measurements

Results

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Intermediate Re: estimations vs. measurements

Results

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  First model of drag coefficient for freely moving non-spherical

particles in air

Ø  Valid in a wide range of Reynolds number (Re<105)

Ø  Valid for spherical, regular and irregular particles

Ø  Easy-to-measure shape factors (for low and high Re)

Ø  Lowest value of estimation error and uncertainty

New drag coefficient model

Conclusions