Engineering Conferences International ECI Digital Archives Fluidization XV Proceedings 5-26-2016 Micro/Meso simulations of a fluidized bed with heat transfer Florian Euzenat IFP Energies Nouvelles; Fluid Mechanics Department; Rond-Point de l échangeur de Solaize, 69360, Solaize, France, florian.euzenat@ifpen.fr Anthony Wachs University of British Columbia; Departments of Mathematics and Chemical & Biochemical Engineering; Vancouver BC, Canada Abdelkader Hammouti IFP Energies Nouvelles; Fluid Mechanics Department; Rond-Point de l échangeur de Solaize, 69360, Solaize, France Pascal Fede Institut de Mécanique des Fluides de Toulouse; Spray, Particles and Combustion Group; Allée du Professeur Camille Soula, 31400 Toulouse, France Eric Climent Institut de Mécanique des Fluides de Toulouse; Spray, Particles and Combustion Group; Allée du Professeur Camille Soula, 31400 Toulouse, France Follow this and additional works at: http://dc.engconfintl.org/fluidization_xv Part of the Chemical Engineering Commons Recommended Citation Florian Euzenat, Anthony Wachs, Abdelkader Hammouti, Pascal Fede, and Eric Climent, "Micro/Meso simulations of a fluidized bed with heat transfer" in "Fluidization XV", Jamal Chaouki, Ecole Polytechnique de Montreal, Canada Franco Berruti, Wewstern University, Canada Xiaotao Bi, UBC, Canada Ray Cocco, PSRI Inc. USA Eds, ECI Symposium Series, (2016). http://dc.engconfintl.org/fluidization_xv/172 This Abstract and Presentation is brought to you for free and open access by the Proceedings at ECI Digital Archives. It has been accepted for inclusion in Fluidization XV by an authorized administrator of ECI Digital Archives. For more information, please contact franco@bepress.com.
Renewable energies Eco-friendly production Innovative transport Eco-efficient processes Sustainable resources Micro/Meso simulations of a uidized bed with heat transfer F. Euzenat 1,*, A. Wachs 2, A. Hammouti 1, É. Climent 3, P. Fede 3 1 Fluid Mechanics Department IFP Énergies Nouvelles France 2 Department of Chemical Engineering Department of Mathematics University of British Columbia Canada 3 Particles, Spray and Combustion Group IMFT France Fluidization XV. 2016 Montebello, Canada ANR MORE4LESS
Gas-solid ows in industry Fields : Energy Chemistry Petrochemicals Pharmaceutics Food Cracking Reactors Drying AA-CAES Regenerator Granulation Solar plant Adsorption Coating Technologies : Fluidized beds Fixed beds
Gas-solid ows in industry Inlet (m) Height (m) N particles Pilot plant 1 0.254 0.432 3 10 9 10 11 Industrial plant 2 5 22 10 13 10 15 PeliGRIFF (IFPEN) YALES2 (CORIA) NEPTUNE _CFD (IMFT ) ANR project MORE4LESS : IFPEN, CORIA, IMFT 1 Fournol and Bergougnou. In: Can. J. Chem. Eng. 51 (1973), pp. 401404. 2 Farrauto Bartholomew. Fundamentals of Industrial Catalytic Processes.
PeliGRIFF : Mass and momentum equations I Microscale : Local conservation equations uc = 0 Amir Esteghamatian rd 3 3 year PhD student ρc uc + (ρc uc uc ) + P µc 2 uc ρc g + Floc = 0 t I Mesoscale : Averaged conservation equations 2014 - IFP Energies nouvelles αc + (αc uc ) = 0 t αc ρc uc + (αc ρc uc uc )+ P (αc τc )+ Fpc αc g = 0 t 3 Esteghamatian et al. Micro/Meso simulation of a uidized bed in a homogeneous bubbling regime. In: Int. J. Mult. Fl. (2016).
PeliGRIFF : Temperature equation Micro Meso Microscale : Local conservation equations ρ c Cp c T c t + (ρ c Cp c T c u c ) (λ c T c ) Q loc = 0 Mesoscale : Averaged conservation equations α c ρ c Cp c T c t + (α c ρ c Cp c T c u c ) (α c λ c T c ) Q = 0
Plan I- Microscale simulations I-1. PeliGRIFF tools I-2. Random beds I-3. From DNS to DEM/CFD II- Comparison DNS-DEM/CFD II-1. Mesoscale : Closure laws II-2. Random beds II-3. Fluidized beds Conclusion/Perspectives
Plan I- Microscale simulations I-1. PeliGRIFF tools I-2. Random beds I-3. From DNS to DEM/CFD II- Comparison DNS-DEM/CFD II-1. Mesoscale : Closure laws II-2. Random beds II-3. Fluidized beds Conclusion/Perspectives
I-1. PeliGRIFF tools : Validation (Isolated sphere) Convergence order p 1.5 Error to correlations : ɛ < 1% avec Feng ɛ 3% autres Thermal boundary layer : 4 points to get ɛ < 2% 10 9 Z [-] 0.0050 0.0045 0.0040 8 7 Nu [-] 6 5 4 3 2 1 PeliGRIFF Ranz Clift Feng Whitaker 0 20 40 60 80 100 120 140 160 Re [-] 0.0035 Re=40 Re=150 Re=500 Particle 0.0030 0.0000 0.0002 0.0004 0.0006 0.0008 0.0010 0.0012 0.0014 0.0016 X [-]
I-2. PeliGRIFF tools : Validation (Random beds) 0.04 Tavassoli cases 4 : Bi-periodic box : 6d p 6d p 8d p Grid size : d p /h [8; 64] Richardson extrapolation φ tot : φ tot (h) = φ tot,0 + A tot h p Ai[W/m 2.77 ] 0.02 0.00 0.02 0.04 0.06 0.08 0.10 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 z [m] 0.04 0.03 Individual convergence φ i d p /h = 48 to get ɛ < 5% Ai[W/m 3.68 ] 0.02 0.01 0.00 0.01 4 Tavassoli et al. In: Int. J. Mult. Fl. 57 (2013), pp. 2937. 0.02 1 2 3 4 5 6 7 8 9 z/r [-]
I-2. Random beds Nu (7 10/αd+5α d 2 ) P r 1/3 10 2 10 1 10 0 Deen αd = 0.9 Deen αd = 0.7 Deen αd = 0.5 Gunn αd = 0.9 Gunn αd = 0.9 Gunn αd = 0.9 αd =0.5 αd =0.7 Nu [-] 10 2 10 1 Our, αc =0.5 Our, αc =0.7 Our, αc =0.9 PeliGRIFF, αc=0.5 PeliGRIFF, αc=0.7 PeliGRIFF, αc=0.9 αd =0.9 10 1 10 0 10 1 10 2 Re [-] 10 0 10 0 10 1 10 2 10 3 P e [-] Closure laws : Comparison to literature correlations : Gunn 5, Deen 6 Proposition of a new closure law : Nu(α d, Pe) = (1.92α 2 d + 2.27α d + 4.97)Pe 0.42α2 d 0.43α d +0.36 5 Gunn. In: Int. J. H. M. Tr. 21 (1978), pp. 467476. 6 Deen and Kuipers. In: Chem. Eng. Sc. 116 (2014), pp. 645656.
I-2. Random beds Probability 0.09 0.08 0.07 0.06 0.05 0.04 0.03 PDF of heat transfer coefficient : 2.5% 1dp (158), h=-58.793 2dp (201), h=-32.378 3dp (210), h=-30.724 4dp (218), h=-29.09 5dp (230), h=-27.911 0.02 0.01 0.00 100 80 60 40 20 0 h [W/m 2.K 1 ] Nusselt number denition : Nu i = h i S i (T d,i T c,bulk ) Volume averaging on boxes around particles : V T c,bulk = box α c (r )T c (r )dr V box α c (r )dr
I-2. Random beds 0.05 0.04 PDF of heat transfer coefficient : 2.5% Re=18 2dp (201), h=-32.378 Re=36 2dp (318), h=-39.575 Re=72 2dp (485), h=-51.479 10 2 Probability 0.03 0.02 h [W/m 2.K 1 ] 0.01 0.00 120 100 80 60 40 20 0 h [W/m 2.K 1 ] 10 1 1dp (0.172) 2dp (0.334) 3dp (0.358) 4dp (0.378) 5dp (0.392) 10 1 10 2 Re [-] New closure law formulation h with Re : h = ARe α(l box /d p) High impact of box size on α(l box /d p ) Trend with Re similar to 1D-balance, Gunn 7 and Deen 8 7 Gunn. In: Int. J. H. M. Tr. 21 (1978), pp. 467476. 8 Deen and Kuipers. In: Chem. Eng. Sc. 116 (2014), pp. 645656.
I-3. From DNS to DEM-CFD 1.4 1.2 1.0 Kernel 0 Kernel 1 Kernel 2 Kernel 3 Kernel 4 Kernel 5 Kernel 6 Kernel 7 Kernel 8 Kernel 9 g(r) [-] 0.8 0.6 0.4 0.2 Micro Meso 0.0 3 2 1 0 1 2 3 r/dp [-] Use of kernel weighting g( r r p ) : V T c,bulk = box α c (r )g( r r p )T c (r )dr V box α c (r )g( r r p )dr 10 kernel types : 5 function of box size, 5 with xed decreasing rate Estimation of new closure laws depending on kernel denition
Plan I- Microscale simulations I-1. PeliGRIFF tools I-2. Random beds I-3. From DNS to DEM/CFD II- Comparison DNS-DEM/CFD II-1. Mesoscale : Closure laws II-2. Random beds II-3. Fluidized beds Conclusion/Perspectives
II-1. Closure laws for mesoscale Flow : Beetstra 9, Di Felice 10,... f hd = f (α d, Re) Temperature : Gunn 11, Deen 12,... T i,j+1 Particle uid information : Linear interpolation Nu hd = f (α d, Re, Pr) Nu pd = 1 V θnu hd T i,j 1 9 Beetstra, Van der Hoef, and Kuipers. In: Chem. Eng. Sc. 62 (2007), pp. 246255. 10 Di Felice. In: Int. J. Mult. Fl. 20 (1994), pp. 153159. 11 Gunn. In: Int. J. H. M. Tr. 21 (1978), pp. 467476. 12 Deen and Kuipers. In: Chem. Eng. Sc. 116 (2014), pp. 645656. N p θ 1,i,j T i,j θ 2,i,j
II-2. Quid for hydrodynamic forces 14? Impact of closure laws on global parameters Eect of meshes to particle ratio 13 Convergence for x /d p [1.8; 3] 13 Manuel Bernard. Approche Multi-échelle pour les écoulements uide-particules. PhD thesis. MEGEP, 2014. 14 Esteghamatian et al. Micro/Meso simulation of a uidized bed in a homogeneous bubbling regime. In: Int. J. Mult. Fl. (2016).
II-2. Comparison of homogeneous uidization DNS 2014 - IFP Energies nouvelles Ncells Nprocs Time [h] I Heat closure law : Ranz-Marshall, Gunn I Fluid closure law : Di Felice Homogeneous uidization : I I I Particle motion and agitation : Heat transfer mechanisms : 50.106 128 360 DEMCFD 756 1 2
II-2. Comparison of bubbling uidization DNS 2014 - IFP Energies nouvelles Ncells Nprocs Time [h] I Heat closure law : Ranz-Marshall, Gunn I Fluid closure law : DiFelice Bubbling uidization : I I I Particle motion and agitation : X Heat transfer mechanisms : X 70.106 256 1500 DEMCFD 625 1 2
Conclusion and Perspectives Micro-analysis of heat transfer closure laws Improvement for DEM-CFD : Closure laws Modeling (equations) Direct comparison of DNS/DEM-CFD simulations on going Perspectives : Closure laws for wall-gas heat transfer from DNS Eect of bi-dispersity MORE4LESS Project : Closure laws implementation in YALES2 (CORIA) Fluidized bed with complex geometries simulations DEM-CFD Euler-Euler transition on NEPTUNE_CFD (IMFT)
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Appendix 1. DLM/FD points distribution over a sphere Strategies : (layers, spiral), spacing (s = h,2h) Spatial convergence : isolated sphere, domain (6d p 6d p 8d p ) Bi-perdiodic Spiral distribution chosen Spacing s : 2h, 3h Richardson : φ(h) = φ h=0 + Bh p 10 1 10 0 10 2 10 1 ɛ [-] 10 3 ɛ [-] 10 2 10 4 k =1.85, σ =0.05 Order 1 Order 2 10 5 10 0 10 1 10 2 10 3 Np [-] 10 3 k =1.492, σ =0.09 Order 1 Order 2 10 4 10 0 10 1 10 2 10 3 Np [-]
Appendix 2 : Fixed beds spatial convergence Total heat transfer : N p N p φ tot = φ h=0 + B i h p i i=1 i=1 7 meshes (CFL constante) Convergence on φ tot ɛ [-] 10 1 10 2 10 3 10 4 10 5 10 6 10 1 10 2 Np [-] 10 1 k =1.677, σ =0.02 Order 1 Order 2 10 2 10 3 10 2 ɛ [-] ɛ [-] 10 4 10 5 k =0.77, σ =0.07 Order 1 Order 2 10 6 10 1 10 2 Np [-] 10 3 k =1.069, σ =0.107 Order 1 Order 2 10 4 10 1 10 2 Np [-]
Appendix 3 : Fixed beds heat transfer Deen 15 test case : 1326 spheres of 6mm, α d = 0.3 with walls ρus dp Re s = µ f [36; 144] Tavassoli 16 test case : αd [0.1; 0.3] (55 to 265 spheres of 1mm) Bi-periodic Res [10; 100] 15 Niels G. Deen et al. In: Chem. Eng. Sc. 81 (2012), pp. 329344. 16 Tavassoli et al. In: Int. J. Mult. Fl. 57 (2013), pp. 2937.
Appendix 4 : Macro/micro heat transfer analysis comparison Authors Tavassoli 17 Deen 18 α p [0.1; 0.5] 0.3 N p [55; 265] 1326 Re p [10;100] [36;144] 10 2 eps=0.5 (0.296 ) eps=0.7 (0.325 ) eps=0.9 (0.383 ) 10 2 Nu [-] 10 1 Nu [ ] 10 1 10 10 0 0 10 1 10 2 10 3 P e [-] 1dp (0.179) 2dp (0.296) 3dp (0.31) 4dp (0.324) 5dp (0.338) 10 0 10 1 10 2 10 3 P e [ ] 17 Tavassoli et al. In: Int. J. Mult. Fl. 57 (2013), pp. 2937. 18 Niels G. Deen et al. In: Chem. Eng. Sc. 81 (2012), pp. 329344.
Appendix 5. Wall-Fluid heat transfer Literature Glicksman 19 : { hw dp 5 + 0.05Rep Pr si Rep < 150 Nu = λ c = 0.18Re 0.8 p Pr 0.33 si Rep 150 19 Kunii and Levenspiel. Fluidization Engineering. Ed. by H. Brenner. Butterworth-Heinemann, 1991.