Influence of particle size distribution on the performance of fluidized bed reactors

Grace, John R.; Sun, Guikai

doi:10.1002/cjce.5450690512

Cited by 175 publications

(80 citation statements)

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“…Experimental results have been presented on the impact of continuous-size distributions on the fluid mechanical behavior of bubbling beds, with effects ranging from minimum fluidization velocity, [10][11][12] bubble sizes, 13 pressure fluctuations, 14 presence of particles in bubbles, 10,15 etc. The contribution by Grace and Sun 14 represents one of the earliest reviews on the influence of particle-size distribution (PSD) on the quality of fluidization, and they summarized that a wider PSD (of Geldart Group A particles) culminates in enhanced reactor efficiency through improved interphase mass transfer and better gas-solid contacting.…”

Section: Introductionmentioning

confidence: 99%

“…The contribution by Grace and Sun 14 represents one of the earliest reviews on the influence of particle-size distribution (PSD) on the quality of fluidization, and they summarized that a wider PSD (of Geldart Group A particles) culminates in enhanced reactor efficiency through improved interphase mass transfer and better gas-solid contacting. One factor impacting gas-solid interaction is the degree of species segregation, and a few efforts have reported on species segregation for continuous size distributions.…”

Section: Introductionmentioning

confidence: 99%

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Axial segregation in bubbling gas‐fluidized beds with Gaussian and lognormal distributions of Geldart Group B particles

2010

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in Wiley Online Library (wileyonlinelibrary.com).Bubbling, gas-fluidized bed experiments involving Geldart Group B particles with continuous-size distributions have been carried out. Sand of various widths of Gaussian or lognormal distributions were completely fluidized, then axial concentration profiles were obtained from frozen-bed sectioning. Similar to previous works on binary systems, results show that mean particle diameter decreases with increasing bed height, and that wider Gaussian distributions show increased segregation extents. Surprisingly, however, lognormal distributions exhibit a nonmonotonic segregation trend with respect to distribution widths. In addition, the shape of the local-size distribution is largely preserved with respect to that of the overall distribution. These findings on the nature of local-size distribution provide experimental confirmation of previous results for granular and gas-solid simulations. Lastly, an interesting observation is that although monodisperse Geldart Group D particles cannot be completely fluidized, their presence in lognormal distributions investigated still results in complete fluidization of all particles.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Axial segregation in bubbling gas‐fluidized beds with Gaussian and lognormal distributions of Geldart Group B particles

2010

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“…Subsequently, some studies have shown that a wide size distribution usually give the highest reactor efficiency, while the narrow blend give the lowest (Sun and Grace 1990), possibly associated with bubbling patterns in bed (Zenz and Othmer 1960, page 278). DEM simulations (Tagami, Mujumdar et al 2009) have also shown that systems with a wide PSD exhibit higher particle velocities around bubbles, while FINAL TECHNICAL REPORT 139 experiments (Grace and Sun 1991;Beetstra, Nijenhuis et al 2009) corroborated the enhancement of mixing through the production of smaller and faster-moving bubbles. However, it can be argued that if the lognormal distribution with σ/d sm = 70% exhibits the least extent of segregation due to its greatest width, why is it that the Gaussian distribution with the greatest width of σ/d sm = 30% did not similarly exhibit a well-mixed system?…”

Section: Axial Concentration Profilesmentioning

confidence: 85%

“…However, it can be argued that if the lognormal distribution with σ/d sm = 70% exhibits the least extent of segregation due to its greatest width, why is it that the Gaussian distribution with the greatest width of σ/d sm = 30% did not similarly exhibit a well-mixed system? Grace and Sun (Grace and Sun 1991) reviewed the influence of PSD on fluidized bed reactors and asserted that fines content per se is not a sufficient parameter to characterize segregation: their nature and the overall size distribution have to be considered. Correspondingly, future work is needed to get a clearer physical picture of the mechanisms leading to the non-monotonic segregation patterns observed here.…”

Section: Axial Concentration Profilesmentioning

confidence: 99%

Development, Verification, and Validation of Multiphase Models for Polydisperse Flows

Hrenya¹,

Cocco²,

Fox³

et al. 2011

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This report describes in detail the technical findings of the DOE Award entitled "Development, Verification, and Validation of Multiphase Models for Polydisperse Flows." The focus was on high-velocity, gas-solid flows with a range of particle sizes. A complete mathematical model was developed based on first principles and incorporated into MFIX. The solid-phase description took two forms: the Kinetic Theory of Granular Flows (KTGF) and Discrete Quadrature Method of Moments (DQMOM). The gas-solid drag law for polydisperse flows was developed over a range of flow conditions using Discrete Numerical Simulations (DNS). These models were verified via examination of a range of limiting cases and comparison with Discrete Element Method (DEM) data. Validation took the form of comparison with both DEM and experimental data. Experiments were conducted in three separate circulating fluidized beds (CFB's), with emphasis on the riser section. Measurements included bulk quantities like pressure drop and elutriation, as well as axial and radial measurements of bubble characteristics, cluster characteristics, solids flux, and differential pressure drops (axial only). Monodisperse systems were compared to their binary and continuous particle size distribution (PSD) counterparts. The continuous distributions examined included Gaussian, lognormal, and NETLprovided data for a coal gasifier.FINAL TECHNICAL 4 DE-FC26-07NT43098 5 EXECUTIVE SUMMARYThis report is the final technical report for the award DE-FC26-07NT43098 entitled "Development, Verification, and Validation of Multiphase Models for Polydisperse Flows." Below is a summary of work completed under the grant for each of the major goals. Goal I: Continuum Theory for Solid PhaseTwo separate and complementary continuum theories were derived to model polydisperse solids: the kinetic theory of granular flow (KTGF) and the discrete quadrature method of moments (DQMOM). Both theories are based on first principles with no adjustable parameters. The polydisperse KTGF and DQMOM were then encoded in MFIX, and underwent a wide range of verification testing to ensure, to the best possible extent, that no coding errors were present. These verification tests included both granular and gas-solid flows, including cases where an analytical solution and/or DEM (discrete element method) data and/or simple test cases. For the case of KTGF, another set of constitutive equations were derived which rigorously incorporated the gas phase for a simplified case of monodisperse systems at low Reynolds numbers. This derivation used the acceleration model developed in Task 2 from direct numerical simulations (DNS) in the starting kinetic equation, and indicated the effect of the fluid phase on the resulting constitutive relations. Goal II: Improved Gas-Particle Drag Laws -effect of particle size distributionIn this portion of the effort, two types of direct numerical simulations (DNS) were used to extract the drag force experienced by particles in a polydisperse suspension. These two methods, na...

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“…For example, a wide size distribution has been observed to lead to smoother fluidization and better gas-solid contacting [12], whereas a narrow distribution may enhance bed stability (e.g., reduce segregation) [13]. In addition, the presence of fines (particles of 45μm diameter or less) may improve the performance of fluidized-bed mediums [14,15]; however, excessive fines may cause the powder to be too cohesive for proper fluidization [16].…”

Section: -Theoretical Relationsmentioning

confidence: 99%

A CFD Study of Industrial Double-Cyclone in HDPE Drying Process

Alavi

Lay

Makhmali

2018

ESJ

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Double-cyclone in fluidized bed drying is an important equipment which reflects the conditions of drying in HDPE slurry process. Cyclone is an important unite of fluidized bed drying in order to move the solid particles outward to its wall. Therefore, flow pattern created in fluidized bed will affect industrial cyclones installed in dryer for dust removing. Pressure drop of the cyclones is an effective parameter represents the drying behavior. Substantially, geometry of cyclone, inlet flow rate of gas, density and particle size distribution (PSD) can affect the pressure drop value. Fluidized bed hydrodynamic regime is very complex and must be understood to improve fluidized bed operations through theoretical, industrial and CFD study of double-cyclone. Pressure drop is introduced as parameter related to the cyclone efficiency can be calculated with ANSYS Fluent software in the Eulerian-Lagrangian framework with RNG k-ɛ turbulence model used as a mathematical method. Proper pressure drop concluded from industrial experiments and CFD calculation shows good fluidization of HDPE particles in the bed of nitrogen and powder to reach the best fluidized bed situation and suitable quality of HDPE powdery product. Keywords:CFD; HDPE Particles; Double-Cyclone; Pressure Drop. Article History:Received: 28 July 2017Accepted: 01 January 2018 1-IntroductionHDPE Particles of fluid bed drying in the gas entering double-cyclone are subjected to centrifugal forces which move them radially outwards, against the inward flow of gas and towards the inside surface of the cyclone on which the solids separate [1]. The performance of cyclone is in a relationship with its static pressure drop between input and output [2]. The factors affecting the rate of entrainment of solids from a fluidized bed dryer named particle size distribution (PSD), terminal velocity, superficial gas velocity, particle density, gas properties and gas flow regime. Therefore, it is necessary to understand the gas-particle flow and separation characteristics of the cyclone.With computational fluid dynamics (CFD techniques), it is now possible to sufficiently calculate the pressure drop created in cyclone. Fluid flows have been mathematically described by a set of nonlinear and partial differential equations named the continuity and Navier-Stokes equation [3]. ANSYS Fluent solves conservation equations for mass and momentum and additional transport equations are also solved when the flow is turbulent. Different CFD calculation have been successfully applied by employing the related mathematic model to determine the features of gas-solid flow field for cyclones [4,5]. Turbulence models such RNG-based k-ɛ model which was derived using a statistical technique called renormalization group theory is one of the proper models in this field. In Fluent, the Lagrangian discrete phase based partly on the physical properties of dust particles and partly on the mathematical modeling with reasonable assumptions made to describe the particles transport in a fluid medium [6]....

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Influence of particle size distribution on the performance of fluidized bed reactors

Cited by 175 publications

References 16 publications

Axial segregation in bubbling gas‐fluidized beds with Gaussian and lognormal distributions of Geldart Group B particles

Axial segregation in bubbling gas‐fluidized beds with Gaussian and lognormal distributions of Geldart Group B particles

Development, Verification, and Validation of Multiphase Models for Polydisperse Flows

A CFD Study of Industrial Double-Cyclone in HDPE Drying Process

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