Computation of gas and solid dispersion coefficients in turbulent risers and bubbling beds

Jiradilok, Veeraya; Gidaspow, Dimitri; Breault, Ronald W.

doi:10.1016/j.ces.2007.01.084

Cited by 58 publications

(30 citation statements)

References 34 publications

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“…The dispersion coefficients for the bubbling bed at 25 atmospheres are much higher than at atmospheric pressure due to the high bed expansion with smaller bubbles. The computed dispersion coefficients are in reasonable agreement with the experimental measurements reported over the last half century and those measured at IIT and in the NETL riser in Morgantown (Jiradilok et al, 2007(Jiradilok et al, , 2008). …”

Section: Discussionsupporting

confidence: 79%

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Gasificaton Transport: A Multiphase CFD Approach & Measurements

Gidaspow¹,

Jiradilok²,

Kashyap³

et al. 2009

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OBJECTIVEThe objective of this project was to develop predictive theories for the dispersion and mass transfer coefficients and to measure them in the turbulent fluidization regime, using existing facilities. A second objective was to use our multiphase CFD tools to suggest optimized gasifier designs consistent with aims of Future Gen. CONCLUSIONSWe have shown that the kinetic theory based CFD codes correctly compute:(1) Dispersion coefficients (2) Mass transfer coefficients Hence, the kinetic theory based CFD codes can be used for fluidized bed reactor design without any such inputs.We have also suggested a new energy efficient method of gasifying coal and producing electricity using a molten carbonate fuel cell. The principal product of this new scheme is carbon dioxide which can be converted into useful products such as marble, as is done very slowly in nature. We believe this scheme is a lot better than the cancelled FutureGen, since the carbon dioxide is safely sequestered. OBJECTIVEThe objective of this project was to develop predictive theories for the dispersion and mass transfer coefficients and to measure them in the turbulent fluidization regime, using existing facilities. A second objective was to use our multiphase CFD tools to suggest optimized gasifier designs consistent with aims of Future Gen. SUMMARY OF ACCOMPLISHMENTS • Dispersion coefficientsThe dispersion coefficient is a measure of the quality of mixing. We have identified two types of solids dispersion coefficients: those due to random particle oscillations, "laminar" type, and those due to cluster or bubble motion, "turbulent" type. A literature review shows that dispersion coefficients in fluidized beds differ by more than five orders of magnitude. To understand the phenomena, two types of hydrodynamics models that compute turbulent and bubbling behavior were used to estimate radial and axial gas and solids dispersion coefficients. The 6 autocorrelation technique was used to compute the dispersion coefficients from the respective computed turbulent gas and particle velocities.The computations show that the gas and the solids dispersion coefficients are close to each other in agreement with measurements. The simulations show that the radial dispersion coefficients in the riser are two to three orders of magnitude lower that the axial dispersion coefficients, but less than an order of magnitude lower for the bubbling bed at atmospheric pressure. The dispersion coefficients for the bubbling bed at 25 atmospheres are much higher than at atmospheric pressure due to the high bed expansion with smaller bubbles. The computed dispersion coefficients are in reasonable agreement with the experimental measurements reported over the last half century and those measured at IIT and in the NETL riser in Morgantown (Jiradilok et al., 2007(Jiradilok et al., , 2008).• Optimized gasifier designs (Gasifier -fuel cell)For carbon capture fossil fuel electric power generation plants will have to be made more efficient. Department of Energy vision 21 c...

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Section: Discussionsupporting

confidence: 79%

“…We have shown that the kinetic theory based CFD codes correctly compute: We have recently shown that the particle and the gas axial and radial dispersion coefficients (Jiradilok et al, 2007(Jiradilok et al, , 2008, and the mass transfer coefficients …”

Section: Discussionmentioning

confidence: 99%

Gasificaton Transport: A Multiphase CFD Approach & Measurements

Gidaspow¹,

Jiradilok²,

Kashyap³

et al. 2009

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“…More recently they have used a laser doppler velocimetry (LDV) technique to measure the instantaneous particle velocities of cork particles (Breault et al, 2005). The measurements of instantaneous particle velocities enable us to compute the dispersion coefficients using the autocorrelation technique (Breault et al, 2008;Jiradilok et al, 2006Jiradilok et al, , 2007.…”

Section: Introductionmentioning

confidence: 99%

“…Jiradilok et al (2006) have briefly illustrated how to compute solids dispersion coefficients for flow of FCC particles in the turbulent fluidization regime. Gas dispersion coefficients and the dispersion coefficients in bubbling beds were recently computed by Jiradilok et al (2007). For flow of FCC particles in the turbulent fluidization regime the standard drag law had to be modified to match the experimentally measured particle concentration profiles.…”

Section: Introductionmentioning

confidence: 99%

Computation of turbulence and dispersion of cork in the NETL riser

Jiradilok

Gidaspow

Breault

et al. 2008

Chemical Engineering Science

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“…These heterogeneous structures cause issues when using standard averagedbased TFM approaches as disparity between the dilute core annulus and dense wall regions are so dramatic. The EMMS drag model has been applied by key researchers within the field of fluidisation hydrodynamics [14,12,15], calculations were made and compared for the slip velocities and drag coefficients for the different interaction phases of dense clusters, dilute broth phases and interactions between them both [13]. This was further extended to show the strong dependence of the drag coefficient on simple structural differences [16] and later a decrease in drag coefficient due to local and global structural changes.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Modelling on the Hydrodynamics of a Circulating Fluidised Bed

Armstrong¹,

Luo²,

Gu³

2009

Inaugural US-EU-China Thermophysics Conference-Renewable Energy 2009 (UECTC 2009 Proceedings)

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The rapid depletion of oil and the environmental impact of combustion has motivated the search for clean combustion technologies. Fluidised bed combustion (FBC) technology works by suspending a fuel over a fast air inlet whilst sustaining the required temperatures. Using biomass or a mixture of coal/biomass as the fuel, FBC provides a low-carbon combustion technology whilst operating at low temperatures. Understanding the hydrodynamic processes in fluidised beds is essential as the flow behaviours causing heat distributions and mixing determine the combustion processes. The inlet velocities and different particle sizes influence the flow behaviour significantly, particularly on the transition from bubbling to fast fluidising regimes. Computational modelling has shown great advancement in its predictive capability and reliability over recent years. Whilst 3D modelling is preferred over 2D modelling, the majority of studies use 2D models for multiphase models due to computational cost consideration. In this paper, two-fluid modelling (TFM) is used to model a 3D circulating fluidised bed (CFB) initially focussing on fluid catalytic cracker (FCC) particles. The transition from bubbling to fast fluidisation over a range of velocities is explored, whilst the effects on the bubble diameter, particle distributions and bed expansion for different particle properties including particle sizes are compared. Drag models are also compared to study the effects of particle clustering at the meso-scale.

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Computation of gas and solid dispersion coefficients in turbulent risers and bubbling beds

Cited by 58 publications

References 34 publications

Gasificaton Transport: A Multiphase CFD Approach & Measurements

Gasificaton Transport: A Multiphase CFD Approach & Measurements

Computation of turbulence and dispersion of cork in the NETL riser

Three-Dimensional Modelling on the Hydrodynamics of a Circulating Fluidised Bed

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