1.1. Research Background
Fluidization can be observed in several natural phenomena such as avalanches, sandstorms, pyroclastic flows, and ground liquefaction. This characteristic is utilized in industrial processes as fluidized beds, where a balance between the drag and gravitational forces acting on the particle bed fluidizes the particles when the fluid velocity from the bottom wall exceeds a certain limit. The velocity at this instant is termed the minimum fluidization velocity, umf.
There are two kinds of fluidization: homogenous or particulate fluidization, where the particle bed expands homogeneously and bubbling or aggregative fluidization, where voids (bubbles) occur in the particle bed as the injected fluid velocity increases. Geldart  classified particles into Groups C, A, B, and D, in ascending order of particle size based on fluidization behavior. The powder bed of Group A homogeneously fluidized above the umf, and bubbles were observed at a certain fluid velocity, which is called the minimum bubbling fluidization velocity, umb. However, homogeneous fluidization did not occur in the powder beds of Groups B and D. Moreover, bubbling fluidization is generally not observed in liquid systems such as glass bead-water systems.
1.2. Literature Review
As summarized in Table 1, two approaches have been widely used to address the abovementioned issue. The first approach derives a discriminant equation to determine the criteria for the transition between homogeneous and bubbling fluidizations. The first discriminant equation was derived by Wilhelm and Kwauk , and numerous criteria have been proposed in the last 60 years     . Notably, most of these studies used Froude or Reynolds numbers based on the minimum fluidization velocity to estimate the fluidization state. Although the state of homogeneous or bubbling fluidization can be estimated under each condition, the estimation of the minimum bubbling fluidization velocity with these methods is difficult.
The second approach derives an equation to estimate the minimum bubbling fluidization velocity umb. Primarily, Geldart  derived the following simple equation:
Subsequently, Abrahamsen and Geldart  obtained the following equation based on an extensive dataset:
where F45 is the mass fraction of particles with diameters less than 45 μm. The equation derived by Abrahamsen and Geldart  is frequently used to study gas-fluidized beds. Although they used dimensional analysis, the derived equation was not expressed using dimensionless parameters. Kuwagi et al.  conducted a dimensional analysis using the governing equations of discrete element method (DEM) and computational fluid dynamics (CFD) coupling model  to describe the phenomenon of fluidization. They plotted the fluidization state
Table 1. Research on the difference between homogeneous and bubbling fluidization.
on a three-dimensional (3-D) graph consisting of three dimensionless numbers—Re, Ar, and ρ*. Thus, the following equation was derived from the boundary plane between homogeneous and bubbling fluidization states:
The derivation method is similar to that of Abrahamsen and Geldart  because the fitting equation was obtained from an extensive simulation and experimental data. In contrast, Kogane et al.  revealed that the dimensionless gravity term, , distinguishing the two states of fluidization can be rewritten as
Certain explanations have been proposed to adequately clarify the basic mechanisms that differentiate homogeneous and bubbling fluidization. Researchers   have argued on the influence of interparticle forces and the insignificant effect of hydrodynamics. Although we can agree with this opinion when treating cohesive powders, Di Renzo and Di Maio  and Thornton et al.  have successfully simulated homogeneous fluidization without any cohesive forces. Thus, interparticle forces do not seem to be a determining parameter for fluidization. Nevertheless, we again emphasize on considering interparticle forces, such as van der Waals forces, during simulation of cohesive powder, i.e., Group C of Geldart’s classification. In other words, interparticle forces are an additional distinguishing factor between the two fluidization states. In addition, homogeneous fluidization can occur in a liquid system with large particles, which is difficult to explain from the standpoint of cohesive forces.
In this study, we used larger particles, i.e., Groups A, B, and D to determine the differences between the two fluidization states. The interparticle force includes a repulsion force resulting from the collision of particles, and the repulsion force can be calculated in a numerical simulation using softer springs to reduce computational time . Nonetheless, the simulated results accurately described the real phenomenon for noncohesive fluidized particles . Ye et al.  used a Hookean spring model with kn = 7 or 3.5 N/m for calculating the repulsion force, whereas kn = 800 N/m in the current study. In addition, Thornton et al.  used E = 100 MPa in a Hertzian spring model. Notably, these studies successfully simulated the difference between homogeneous and bubbling fluidizations. Thus, the repulsion force between particles would not dominantly influence the differences between the two fluidizations.
Furthermore, as mentioned before, dimensional analysis has not been effectively utilized in previous studies for derivation of the discriminant equation to determine the criterion for transition between homogeneous and bubbling fluidizations. When the Froude number or Reynolds number is defined using the minimum fluidization velocity as a reference velocity, the dimensionless number is treated as a physical property, such as the Prandtl number. On the other hand, the velocity of the injected fluid, i.e., the fluidizing velocity, can be used as a reference velocity for the dimensionless numbers. Valverde et al.  and Ye et al.  concluded that the criterion with the Froude number  fails to distinguish between the two fluidized states. In this study, we attempt to alter this perspective by defining the Froude number with the fluidizing velocity instead of the minimum fluidization velocity.
The analogy between the dimensional and dimensionless simulations has already been presented . In the study, a 3-D graph incorporating three dimensionless numbers—Re, Ar, and ρ*—showed a clear boundary between the two states of fluidization. The dimensionless gravity term included these dimensionless numbers and clearly distinguished the two fluidization states in our previous study . Furthermore, the results were in good agreement with prior experimental data. The definition of the dimensionless gravity term was examined in this study to form a basis of understanding and confirm the applicability of dimensional analysis on fluidization.
2.1. Dimensional Analysis
The governing equations for the DEM-CFD coupling model  were assigned to equations describing the fluidization phenomenon.
There are two definitions of pressure: pressure perturbation, p', and the summation of the pressure in the hydrostatic equilibrium and the pressure perturbation, p. Equations (6) and (7) are expressed with terms in relation to p.
However, Equations (6) and (7) can be expressed with terms in relation to p' as
Thereafter, the following equations were derived by nondimensionalizing Equations (5)-(8).
Furthermore, Equations (9) and (10) can be rewritten as
In addition, the following reference qualities were used in the nondimensionalization process:
Further details on the related nondimensionalization procedure can be found in our previous study . The Archimedes number can be confused with the Galilei number . However, the distinction between the two dimensionless numbers can be easily understood from the nondimensionalization procedure. The Archimedes number signifies the buoyancy force in the gravity term of the particle motion equation, whereas the Galilei number considers only the gravity force in the gravity term and the buoyancy as a static force, thus reflecting the total pressure in the expression.
2.2. Numerical Simulation
The fluidization behavior of homogeneous or bubbling fluidization was determined under each condition by performing a DEM-CFD simulation , as it was difficult to conduct numerous experiments under various conditions. The simulations were conducted with an in-house code. The accuracy of the simulation code used in this study has been validated in our previous study  . The ratio of bed (container) size to particle size was chosen to be constant. The analysis domain is 200dp in width, 700dp in height, and dp in thickness. This indicates that the present simulations are two-dimensional. Since the simulation mesh size was set to 5dp, the grid numbers are 40 × 140 for the horizontal direction and vertical direction, respectively. The fluid was uniformly injected from the bottom wall at various velocities u0.
2.3. Analysis Conditions
3. Results and Discussion
3.1. Comparison of Estimation Equations
Equations (3) and (4) were compared with Equations (1) and (2) to be rewritten with dimensional numbers (physical properties) as follows:
Table 2. Properties of particles.
Table 3. Properties of fluids.
The indices of dp, ρf, and μf are listed in Table 4. Although Equation (2) includes the term describing the ratio of fine powder, the indices of dp are 1 and 0.836, those of ρf are 0.06 and 0.165, and those of μf are 0.347 and 0.224 in Equations (2) and (18), respectively. Notably, Equation (2) is based on experimental data and Equation (18) is based on simulated data, but the derivation method is similar for fitting the data. When assuming all the fluid property values as constants, Equation (18) becomes a function of , which is close to the index of 1.0 in Equation (1). Moreover, the absence of the fluid viscosity μf term in Equation (19) indicates that the fluid viscosity is not an essential parameter. Furthermore, the fluid density ρf was expressed only in the buoyancy term: (1 − ρf/ρp). Therefore, the form of Equation (19) is similar to Equation (1).
3.2. Comparisons of Criteria
Certain equations from Table 1 were compared using our simulated data. The distribution of the Froude number Frmf based on umf  is presented in Figure 1. The blue and red circles indicate homogeneous and bubbling fluidizations, respectively; the filled circles indicate a fixed bed (nonfluidization). The fluidization states plotted in Figure 1 were obtained through simulations. In addition, the minimum bubbling fluidization velocity representing the boundary between homogeneous and bubbling fluidizations measured in previous studies     is plotted in Figure 1. Although Wilhelm and Kwauk  set the boundary at Frmf= 1, bubbling fluidization occurs at Frmf> 0.1, as shown in Figure 1. Furthermore, the distinction of the fluidization type becomes difficult under
Figure 1. Relationship between Froude numbers based on umf  and fluidization behaviors.
Table 4. Comparison of property indices inumb equations.
Frmf < 0.1. The experimental data obtained from the literature     are indicated with vacant symbols in Figure 1. The boundary between the two fluidization states ranged from 10−1 to 10−3 . However, differentiating the two fluidization behaviors from the results was difficult with the Froude number Frmf based on umf. Therefore, the conclusion that the Froude number criterion fails to estimate the difference   is plausible.
The values of Ue − Uε calculated using the criterion from Foscolo and Gibilaro  are depicted in Figure 2, which shows certain outlying formations of bubbling fluidization (red circles) in the region above the dashed line. All the outlying phenomena occurred with particles from Group C of Geldart’s classification, indicating that this criterion cannot be applied to particles from Group C. Moreover, Valverde et al.  specified that Foscolo and Gibilaro  had neglected particle inertia. However, their criterion can distinguish between the two forms of fluidization.
Furthermore, Figure 3 shows the discrimination number Dn proposed by Liu et al. . They concluded that homogeneous fluidization occurs at Dn < 104, transitional region ranges from 104 to 106, and bubbling fluidization occurs at Dn > 106. However, the boundary between the bubbling fluidization and transitional states evaluated from our simulation was at 107, as shown in Figure 3. Moreover, experimental data existed beyond the order of 107.
Figure 2. Relationship between the criterion of Foscolo and Gibilaro  and fluidization behaviors.
Figure 3. Relationship between discrimination number  and fluidization behaviors.
The values of the dimensionless gravity term proposed by the present authors  are illustrated in Figure 4. Both Frmf and Dn are based on umf, and therefore cannot be used as the discriminant in varying the fluidizing velocity or superficial velocity u0. On the contrary, the dimensionless gravity term is a dimensionless parameter based on u0; thus, it can be applied to alter the fluidization pattern by varying u0. The homogeneous and bubbling fluidizations were well separated in the obtained results, and the boundary value was consistent with the experimental values of umb referred from the literature    . Upon further examination, the boundary value was found to decrease with an increasing Reynolds number. This tendency is attributed to the assumption of Stokes flow in the derivation of the dimensionless gravity term . In particular, this could be an effect of particle inertia. Thus, we derived a modified dimensionless gravity term  as a solution.
Figure 4. Relationship between dimensionless gravity term  and fluidization behaviors.
Figure 5. Relationship between Froude numbers based on fluidizing velocity, u0, and fluidization behaviors.
the homogeneous and bubbling fluidizations were well separated by a boundary value of 0.1. Moreover, this result is similar to that presented in Figure 4. Furthermore, the relationship between Fr and can be expressed using the dimensionless numbers as
These equations correspond to the expressions of gravity in Equations (13) and (16). Therefore, both Fr and were derived from the dimensionless governing equations discussed earlier, and the distinction is highlighted from the treatment of pressure, i.e., p or p', as shown in Equations (7) and (10). Notably, Fr comprises two dimensionless numbers, whereas comprises three dimensionless numbers. The dimensional analysis requires three dimensionless parameters , and satisfies this condition but Fr does not. Nevertheless, Fr can distinguish the two fluidization states, as shown in Figure 5, and the reason has to be clarified with further studies.
3.3. Accuracy of Estimation Equation
The estimation equation for umb was quantitatively verified by comparing the experimental values with that referred from the literature    . The values calculated using Equations (2), (3), and (4) are presented in Figure 6, Figure 8 and Figure 9, respectively. In addition, the values calculated using the equation of Foscolo and Gibilaro  are presented in Figure 7. In each figure, the ordinate indicates the calculated value, whereas the abscissa indicates the experimental value.
Figure 6. Comparison of umb values predicted by equation of Abrahamsen and Geldart  (Equation (2)) with experimental data.
Figure 7. Comparison of umb values predicted by equation of Foscolo and Gibilaro  with experimental data.
As shown in Figure 6, the values calculated using Equation (2) were in poor agreement with the experimental values for the liquid system (blue circles) because Abrahamsen and Geldart  obtained their equation based on data of fluidizing fine powder under gas flow. As shown in Figure 7, the equation of Foscolo and Gibilaro  provided a better correlation in the case of the liquid system, but the overall variance was large. Moreover, a considerable agreement can be observed in Figure 8 because Equation (3) was obtained from an extensive dataset comprising 3-D flow regime map , including that of a liquid system. Figure 9 displays another disagreement for the liquid system owing to its larger particle diameters and higher fluidizing velocities, i.e., high Reynolds numbers. As the dimensionless gravity term in our study was derived by assuming Stokes flow, we used the modified dimensionless gravity term . However, the dimensionless gravity term should be used to determine the fundamental mechanisms differentiating between homogeneous and bubbling fluidizations. Regardless, the disagreement is unimportant in terms of analyzing the fundamental mechanisms of the two fluidization behaviors.
The deviation from the experimental data is summarized in Table 5. Although Equation (3) can be applied to a wide range of conditions including liquid systems, its application in fine powders without modification is difficult. In Figure 9, the deviation between the predicted and experimental values broadened as umb increased; a large umb indicates a high Reynolds number. Moreover, the reason for the deviation is the same as that discussed in Figure 4.
Figure 8. Comparison of umb values predicted by equation of Kuwagi et al.  (Equation (3)) with experimental data.
Table 5. Deviation from experimental data.
Figure 9. Comparison of umb values predicted by equation of Kogane et al.  (Equation (4)) with experimental data.
In this study, the distinct fundamental mechanisms of the homogeneous and bubbling fluidization behaviors were determined using a dimensionless gravity term that was derived to distinguish the two fluidization states as per our previous report . The dimensionless gravity term was validated with results of prior research.
The estimation equations for dimensional analysis were derived from a 3-D flow regime map and the dimensionless gravity term was compared with the criteria reported in previous studies. A comparative analysis on the indices of physical properties confirmed that our derived equations were almost equivalent to the equations established in prior research. Thus, the dimensionless gravity term is signified as a dominant parameter for distinguishing between homogeneous and bubbling fluidization. In addition, the dimensionless gravity term was expressed in the dimensionless governing equations. In comparison to interparticle forces, the results of the current research indicated that hydrodynamic force is the most important and dominant factor in differentiating the two fluidized states. However, interparticle forces, such as cohesive and repulsion forces and the effect of particle inertia can be considered as additional factors to demonstrate more accurate simulations. Notably, the distinction between the two fluidization states can be simulated and observed without considering these additional factors as well.
Furthermore, the estimation equations were compared with existing discriminant equations. The minimum bubbling fluidization velocities estimated in the current study were consistent with the experimental data, and the estimation equations accurately distinguished the two fluidization behaviors.
Ar Archimedes number, –
dp diameter of particle, m
fpf particle-fluid interaction force per unit volume, N/m3
dimensionless particle-fluid interaction force, –
Fpp particle-particle interaction force, N
dimensionless particle-particle interaction force, –
Fpf particle-fluid interaction force, N
dimensionless particle-fluid interaction force, –
Fr Froude number, –
Ft tangential soft sphere interaction at contact, N
dimensionless tangential soft sphere interaction at contact, –
g gravitational acceleration, m/s2
GaGalilei number, –
I inertial moment of particle, kg·m2
m mass, kg
p pressure, Pa
p' pressure perturbation, Pa
P dimensionless pressure, –
P' dimensionless pressure perturbation, –
rp radius of particle, m
R dimensionless radius of particle, –
Re particle Reynolds number, –
T dimensionless time, –
ufluid velocity, m/s
U dimensionless fluid velocity, –
u0fluidizing velocity, m/s
utterminal velocity, m/s
vparticle velocity, m/s
V dimensionless particle velocity, –
Vpvolume of particle, m3
X dimensionless coordinate, –
ε voidage, –
μ viscosity, Pa·s
ρ density, kg/m3
ρ* density ratio (=ρp/ρf), –
ω angular velocity, rad/s
ω* dimensionless angular velocity
mf minimum fluidization
mb minimum bubbling fluidization
o arbitrary reference quality
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