chapter 9 mixing and segregation - cheric · standard deviation,σ and standard variance,σ2 -...

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C h a p t e r 9 M i x i n g a n d S e g r e g a t i o n 9 . 1 I n t r o d u c t i o n - h t t p : / / s o l . r u t g e r s . e d u / ~ s h i n b r o t / G r o u p _ I n d e x . h t m l h t t p : / / w w w - e c . n j i t . e d u / e c _ i n f o / i m a g e 2 / p t c / m p e g / s c r a t c h 1 1 . M p e g M i x i n g v s . S e g r e g a t i o n M i x i n g s t a t i s t i c s M i x e r s 9 . 2 T y p e s o f M i x t u r e * P e r f e c t m i x t u r e R a n d o m m i x t u r e S e g r e g a t i n g m i x t u r e F i g u r e 9 . 1 9 . 3 S e g r e g a t i o n : 1 ) C a u s e s a n d C o n s e q u e n c e s o f S e g r e g a t i o n W h e n p a r t i c l e s t o b e m i x e d h a v e t h e s a m e i m p o r t a n t p h y s i c a l p r o p e r t i e s * ( s i z e , d e n s i t y a n d s h a p e ) , E x t e n s i v e m i x i n g r e s u l t s i n r a n d o m m i x t u r e . . . * D i f f e r e n c e i n p a r t i c l e s i z e : m o s t i m p o r t a n t c a u s e f o r s e g r e g a t i o n F o r t h e p a r t i c l e s w i t h d i f f e r e n t p r o p e r t i e s - T h e p h e n o m e n a b y w h i c h t h e p a r t i c l e s w i t h t h e s a m e p h y s i c a l p r o p e r t y c o l l e c t t o g e t h e r i n o n e p a r t o f t h e m i x t u r e . - U s u a l l y i t o c c u r s d u r i n g m o v i n g , p o u r i n g , c o n v e y i n g , p r o c e s s i n g - I t s d e g r e e d e p e n d s o n p a r t i c l e - p a r t i c l e i n t e r a c t i o n * * F r e e - f l o w i n g p o w d e r o r c o a r s e p a r t i c l e s s e g r e g a t i n g r a t h e r t h a n m i x i n g

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Page 1: Chapter 9 Mixing and Segregation - CHERIC · Standard deviation,σ and standard variance,σ2 - Estimated standard variance(S2) S2=1 N ∑ N i=1 (yi-μ) 2 if true mean is known, otherwise

Chapter 9 Mixing and Segregation

9.1 Introduction -

☞http://sol.rutgers.edu/~shinbrot/Group_Index.html

☞http://www-ec.njit.edu/ec_info/image2/ptc/mpeg/scratch11.Mpeg

Mixing vs. Segregation

Mixing statistics

Mixers

9.2 Types of Mixture

* Perfect mixture

Random mixture

Segregating mixture

Figure 9.1

9.3 Segregation:

1) Causes and Consequences of Segregation

When particles to be mixed have the same important physical

properties* (size, density and shape),

Extensive mixing results in random mixture...

* Difference in particle size : most important cause for segregation

For the particles with different properties

- The phenomena by which the particles with the same physical

property collect together in one part of the mixture.

- Usually it occurs during moving, pouring, conveying, processing

- Its degree depends on particle-particle interaction*

* Free-flowing powder or coarse particles → segregating rather than

mixing

Page 2: Chapter 9 Mixing and Segregation - CHERIC · Standard deviation,σ and standard variance,σ2 - Estimated standard variance(S2) S2=1 N ∑ N i=1 (yi-μ) 2 if true mean is known, otherwise

Cohesive powder or fine particles → mixing rather than

segregating but easily

aggregating

Segregation resultes in problems in product quality....

2) Mechanisms of Segregation

Figure 9-2

- Trajectory segregation

From Chapter 3 in lecture note,

Stop distance s= τU=ρpd

2pU

18μ, 큰 입자가 멀리 간다.

- Percolation of fine particles - Figure 9.3

작은 입자가 큰입자의 사이를 고 들고 큰입자가 겉, 작은 입자가

속을 차지한다.

Rise of coarse particles on vibration - Figure 9.4

- Elutriation segregation

기체는 침강속도가 작은 입자를 들어올리나 침강속도가 큰 입자는 그

로 내려 오게 한다.

9.4 Reduction of Segregation

Make the sizes of the components as close as possible

Reduce the absolute size of the particles

(< 30 μm with density about ρ p= 2000-3000kg/m3)

- Use of interparticulate forces

- Critical diameter lowered as the density increases.

Add a small amount of liquid.

- Use of liquid-bridge force

Make one of the components very fine (less than 5 μm)

- Ordered mixing*

Figure 9.5

Page 3: Chapter 9 Mixing and Segregation - CHERIC · Standard deviation,σ and standard variance,σ2 - Estimated standard variance(S2) S2=1 N ∑ N i=1 (yi-μ) 2 if true mean is known, otherwise

Avoid to promote the segregation

e.g. use mass flow instead of core flow

Use continuous mixing for very segregating materials

9.5 Equipment for Particulate Mixing

1) Mechanisms of Mixing

Diffusive mixing: random walk phenomenon

- Essential for microscopic homogenization

- Not suitable for segregating particles

e.g. Tumbling mixers : Figure 9.6

Shear mixing: induced by the momentum exchange of powders having

different velocities

- Semimicroscopic mixing

e.g. High-velocity rotating blade

Low velocity-high compression rollers

☞ Chapter 10

Convective mixing: circulation of powders

- Beneficial for batch mode, not for continuous mixing

- Suitable for segregating particles

e.g. Ribbon blender : Figures 9.7, 9.8

Fluidized-bed mixer

Effect of particle size on mixing patterns

2) Types of Mixers

Tumbling mixers, Figure 9.6

- Closed vessel rotating about axis

- dominant in diffusive mixing

- makes segregation for free flowing particles

- baffle installed has little effect

Convective mixers, Figures 9.7, 9.8

Page 4: Chapter 9 Mixing and Segregation - CHERIC · Standard deviation,σ and standard variance,σ2 - Estimated standard variance(S2) S2=1 N ∑ N i=1 (yi-μ) 2 if true mean is known, otherwise

- static shell by rotating blades or paddles, < 1rps

- accompanied by some diffusive and shear mixing

Fluidized mixers

- largely convective by bubble motion

- mixing, reaction coating, drying etc.:carried out in the same

vessel

High shear mixers

- high shear created by high velocity rotating blades

low velocity-high compression rollers

- breaking down agglomerates of cohesive powders

* Ordered mixture

- Dry impact blending method

- Mechanofusion method

3) Power Requirement for Mixing

P=2πNsT

where Ns: rotation speed(rps)

T ?

- Horizontal Cylinder Mixer

T

R 3Lρ bg=A+B

N2sR

g

where R : radius of rotation

A and B : depend on powder properties

- V-Type Mixer

Tj

R4maxρbg

=Aj+B jN

2sR max

g

where A and B : depend on powder properties

Page 5: Chapter 9 Mixing and Segregation - CHERIC · Standard deviation,σ and standard variance,σ2 - Estimated standard variance(S2) S2=1 N ∑ N i=1 (yi-μ) 2 if true mean is known, otherwise

- Stationary Vessel Mixer-ribbon and paddle impeller

T=Kdα

1

pρα

2

bμα

3

s Zα

4

5( SD )α

6

7

8, (N․m)

where dp: particle diameter(m)

ρb: bulk density(kg/m3)

μ0: internal friction coefficient

S: pitch of ribbon impeller(m)

b: width of impeller(m)

D: diameter of impeller(m)

f: charge ratio

Z: height of powder bed(m)

K, α i's: depend on the type of mixers

9.6 Statistics of Solid Mixing- Assessment for Mixing

For Binary mixture(2 components)

If yi(i=1,2,……N): composition of the key component in the i-th

sample,

Sample mean

y=1N ∑

N

i= 1y i

True mean

μ=y±tSN

where t : percentile value for student's t distribution

☞ Shaum's-Mathematical handbook

depends on the level of confidence and the

number of freedom(N)

e.g. for 97.5% confidence and N=60

t=2.00

S : the estimated standard deviation

Page 6: Chapter 9 Mixing and Segregation - CHERIC · Standard deviation,σ and standard variance,σ2 - Estimated standard variance(S2) S2=1 N ∑ N i=1 (yi-μ) 2 if true mean is known, otherwise

Standard deviation, σ and standard variance, σ 2

- Estimated standard variance( S 2)

S 2=1N ∑

N

i=1(y i-μ)

2

if true mean is known, otherwise

S 2=1N ∑

N

i=1(y i- y)

2

- Theoretical Limits of variance

Upper limit: true standard deviation for a completely unmixed

system, σ0

σ20= p(1-p)

Lower limit: true standard deviation of random binary

mixture, σr

σ2R=

p(1-p)n

where p, 1-p : fractions of two components in the whole mixture

- True variance, σ

when N > 50

σ 2=S

2±[ t×E(S

2)]

where E(S 2)=S 2 2N

When N < 50

Lower limit: σL=

S2(N-1)χ2α

Upper limit: σU=

S2(N-1)χ2

1-α

where χα: chi-squared distribution for significance level, α

α=0.5(1-c) where c: confidence range

e.g. c=0.9 → α=0.05 → χ 20.05= 34.8 for N=50

Page 7: Chapter 9 Mixing and Segregation - CHERIC · Standard deviation,σ and standard variance,σ2 - Estimated standard variance(S2) S2=1 N ∑ N i=1 (yi-μ) 2 if true mean is known, otherwise

- Degree of Mixing(Mixing indices)

the ratio of mixing achieved to mixing possible

Lacey : σ2

0-σ2

σ20-σ

2r

Poole : σσr

Worked Example 9.1, 9.2, 9.3