Classifying – separating – and assorting solids – Fluid suspension – Liquid
Reexamination Certificate
2002-06-03
2004-05-25
Walsh, Donald P. (Department: 3653)
Classifying, separating, and assorting solids
Fluid suspension
Liquid
C209S139100, C209S710000, C209S713000, C209S717000, C209S734000
Reexamination Certificate
active
06739456
ABSTRACT:
TECHNICAL FIELD
The present invention relates generally to particle classification. More particularly, the present invention relates to the classification of particles from a fluid stream via centrifugal separation imparted by boundary layers developed between rotating parallel disks, whereby the primary airflow runs counter to the ejected trajectory of the particles larger than the cut-size of the device. Fine particles smaller in diameter than the cut-size of the classifier follow the primary airflow streamlines to a collection vessel.
BACKGROUND ART
Air classifiers can be used to classify, or selectively filter, airborne particles according to their size, density, or shape based on a balance between inertial and fluid forces acting on the particles in a flow field. Air classifiers are used primarily to produce particles in a limited size range. Production of powders in a limited size range is important in many different types of industries (e.g., electronics, food, chemical, petroleum, and pharmaceuticals), where product quality depends on the size distribution of the powder used to make the product. Size distribution affects powder properties such as homogeneity, flowability, taste, texture, and surface area. A narrow size distribution can give the final product more uniformity to improve product quality. Industries commonly use air classifiers to classify dry powders because they can handle higher mass throughputs than other methods such as screening. In the production of fine powders, air classification often follows a comminution, or grinding, process. Powder generated from the grinding process is sent to an air classifier to remove the coarser particles.
Most air classifiers separate the feed material into two size groups: a coarse fraction and a fine fraction. Separation is typically measured by efficiency, which can be generally defined as the fraction of particles of a given size (d) in the feed reporting to the coarse fraction,
Efficiency
(
d
)
=
f
c
q
c
(
d
)
q
F
(
d
)
(1-1)
where f
c
is the overall efficiency, or the overall mass fraction of particles in the feed reporting to the coarse fraction, and q
C
(d) and q
F
(d) are the differential size distributions of the coarse fraction and feed, respectively. Cut size is most often defined as the particle size with 50% efficiency (d
50
), efficiency (d =d
50
)=0.50.
The ideal efficiency curve is a unit step function at the cut size. That is, all particles below the cut size leave with the air in the fine fraction, while all particles above the cut size are collected from the air as the coarse fraction. Theoretically, particles at the cut size should be suspended in the classification zone since the forces acting on the particles are balanced. In reality, 50% of particles at the cut size leave with the coarse fraction, and 50% leave with the fine fraction. Air classifiers do not give an ideal separation of particles at the cut size because of random fluctuations in the flow field, particle-particle interactions, and variations in the forces acting on the particles in relation to the position of the particles in the classifier. The quality of the separation, or cut sharpness, is commonly represented by the values K
25/75
and K
10/90
, which are respectively defined as:
K
25/75
=d
25
/d
75
(1-2)
K
10/90
=d
10
/d
90
(1-3)
where d
10
, d
25
, and d
90
are the particle diameters with 10, 25, 75 and 90% efficiency, respectively. Under normal circumstances, K
25/75
and K
10/90
can have values between 0 and 1, where 1 represents an ideal separation.
The extent to which particles are dispersed in air contributes to cut sharpness. To accurately classify a powder, each particle must travel through the flow field independent of other particles. Therefore, to minimize the amount of particle agglomerates entering the classifier, the feed should be dispersed before classification. The energy necessary to disperse a powder can be supplied mechanically (e.g., a mixing blade) or by shear force (e.g., feeding the particles into a high-velocity air stream). Since agglomeration is often caused by moisture in the air, the relative humidity of the air should be sufficiently low. However, if humidity is too low, the particles can become electrostatically charged, which also hinders dispersion. The optimum relative humidity for classification is approximately 50 to 70%. Particle size also affects dispersion, since attractive forces between particles increase as particle size decreases. Because of the difficulty in dispersing very fine particles, especially below 1 &mgr;m, these particles are commonly collected with the coarse fraction as agglomerates. As solids loading, or particle concentration, increases, adequate dispersion becomes more difficult. Consequently, cut sharpness must be compromised for a higher particle loading. This is a dilemma for industries, which need to classify particles at high throughputs to minimize energy consumption.
The lower limit on cut size for air classifiers is typically 1 or 2 &mgr;m. For particles less than 1 &mgr;m, extremely high tangential velocities are required for the inertial force to overcome the fluid forces on the particles. Random particle motion caused by diffusion and Brownian motion also becomes significant below 1 &mgr;m. See Leschonski, K., “Classification of particles in the submicron range in an impeller wheel air classifier,” KONA, No. 14, pp. 52-60 (1996). This is more of a problem if the flow is turbulent. Submicron cut sizes have been achieved by air classification, but only for limited throughputs. In addition, achieving sharp cuts at these small cut sizes is a challenge because of the difficulty in dispersing submicron particles.
Separation of particles from the air stream can be either counterflow or crossflow. In counterflow classifiers, particles are removed from the fluid in the direction opposite to the main flow. In crossflow classifiers, particles are removed perpendicular to the main flow. Particle removal is usually accomplished by gravity or inertial forces, such as centrifugal force, which isdue to the angular momentum of the flow. Because centripetal acceleration can be much stronger than gravitational acceleration at high tangential velocities, centrifugal classifiers are able to remove smaller particles from the flow than gravity-based classifiers. In general, counterflow classifiers can provide smaller cut sizes than crossflow classifiers, with the counterflow centrifugal classifier providing the smallest cut sizes. The approximate cut size range for counterflow centrifugal air classifiers is 1 to 100 &mgr;m for mineral particle densities (~2000 to 3000 kg/m
3
). The only other type of classifier that has achieved cut sizes as small as the counterflow centrifugal classifier is the crossflow elbow classifier. See Maly, K., “Untersuchung der partikel-strömungsmittel-wechselwirkung im strahlumlenk-windsichter,” Dissertation, Techn. Hochschule Karlsruhe, Germany (1979); Rumpf, H. and Leschonski, K., “Prinzipien und neuere verfahren der windsichtung, Chemie-Ing.-Technik,” Vol. 39, pp. 1231-1241 (1967). However, the crossflow elbow classifier cannot handle as high throughputs.
The basic principle of centrifugal counterflow classification can be understood from a force balance on the particle in the radial direction. For a particle in a rotating flow field, neglecting gravity and assuming particle density (&rgr;
p
) is much greater than fluid density (&rgr;), the equation of motion in the r-direction is given by:
m
p
ⅆ
v
r
,
p
ⅆ
t
=
F
D
+
m
p
v
θ
,
p
2
r
=
F
D
+
F
C
;
F
C
=
m
p
v
θ
,
p
2
r
(1-4)
where m
p
is the particle mass, v
r,p
and v
&thgr;,p
are the particle radial and tangential velocities, F
D
is the drag force, and F
C
is the centifugal force. For a spherical particle,
m
p
=&pgr;/6&rgr;
p
D
p
3
(1-5)
where D
p
is the particle diameter. Considering o
Crouch H. Steven
El-Shall Hassan El-Sayed
Powers Kevin W.
Scheiffele Gary Wayne
Svoronos Spyros A.
Akerman & Senterfitt
Rodriguez Joseph
University of Florida Research Foundation Inc.
Walsh Donald P.
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