Micro/Meso simulations of a fluidized bed with heat transfer

Transcription

1 Engineering Conferences International ECI Digital Archives Fluidization XV Proceedings 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, Toulouse, France Eric Climent Institut de Mécanique des Fluides de Toulouse; Spray, Particles and Combustion Group; Allée du Professeur Camille Soula, Toulouse, France Follow this and additional works at: 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). 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.

2 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 Montebello, Canada ANR MORE4LESS

3 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

4 Gas-solid ows in industry Inlet (m) Height (m) N particles Pilot plant Industrial plant 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 Farrauto Bartholomew. Fundamentals of Industrial Catalytic Processes.

5 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 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).

6 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

7 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

8 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

9 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 [-] Nu [-] PeliGRIFF Ranz Clift Feng Whitaker Re [-] Re=40 Re=150 Re=500 Particle X [-]

10 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 ] z [m] Individual convergence φ i d p /h = 48 to get ɛ < 5% Ai[W/m 3.68 ] Tavassoli et al. In: Int. J. Mult. Fl. 57 (2013), pp z/r [-]

11 I-2. Random beds Nu (7 10/αd+5α d 2 ) P r 1/ 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 [-] 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 = Re [-] 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 α d )Pe 0.42α2 d 0.43α d Gunn. In: Int. J. H. M. Tr. 21 (1978), pp Deen and Kuipers. In: Chem. Eng. Sc. 116 (2014), pp

12 I-2. Random beds Probability PDF of heat transfer coefficient : 2.5% 1dp (158), h= dp (201), h= dp (210), h= dp (218), h= dp (230), h= 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

13 I-2. Random beds PDF of heat transfer coefficient : 2.5% Re=18 2dp (201), h= Re=36 2dp (318), h= Re=72 2dp (485), h= Probability h [W/m 2.K 1 ] h [W/m 2.K 1 ] dp (0.172) 2dp (0.334) 3dp (0.358) 4dp (0.378) 5dp (0.392) 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 Deen and Kuipers. In: Chem. Eng. Sc. 116 (2014), pp

14 I-3. From DNS to DEM-CFD Kernel 0 Kernel 1 Kernel 2 Kernel 3 Kernel 4 Kernel 5 Kernel 6 Kernel 7 Kernel 8 Kernel 9 g(r) [-] Micro Meso 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

15 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

16 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 Di Felice. In: Int. J. Mult. Fl. 20 (1994), pp Gunn. In: Int. J. H. M. Tr. 21 (1978), pp Deen and Kuipers. In: Chem. Eng. Sc. 116 (2014), pp N p θ 1,i,j T i,j θ 2,i,j

17 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, Esteghamatian et al. Micro/Meso simulation of a uidized bed in a homogeneous bubbling regime. In: Int. J. Mult. Fl. (2016).

18 II-2. Comparison of homogeneous uidization DNS 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 : DEMCFD

19 II-2. Comparison of bubbling uidization DNS 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 DEMCFD

20 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)

21 Renewable energies Eco-friendly production Innovative transport Eco-efficient processes Sustainable resources

22 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 ɛ [-] 10 3 ɛ [-] k =1.85, σ =0.05 Order 1 Order Np [-] 10 3 k =1.492, σ =0.09 Order 1 Order Np [-]

23 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 [-] Np [-] 10 1 k =1.677, σ =0.02 Order 1 Order ɛ [-] ɛ [-] k =0.77, σ =0.07 Order 1 Order Np [-] 10 3 k =1.069, σ =0.107 Order 1 Order Np [-]

24 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 Tavassoli et al. In: Int. J. Mult. Fl. 57 (2013), pp

25 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 [ ] P e [-] 1dp (0.179) 2dp (0.296) 3dp (0.31) 4dp (0.324) 5dp (0.338) P e [ ] 17 Tavassoli et al. In: Int. J. Mult. Fl. 57 (2013), pp Niels G. Deen et al. In: Chem. Eng. Sc. 81 (2012), pp

26 Appendix 5. Wall-Fluid heat transfer Literature Glicksman 19 : { hw dp Rep Pr si Rep < 150 Nu = λ c = 0.18Re 0.8 p Pr 0.33 si Rep Kunii and Levenspiel. Fluidization Engineering. Ed. by H. Brenner. Butterworth-Heinemann, 1991.