Best Practice Guidelines for Computational Turbulent Dispersed Multiphase Flows. René V.A. Oliemans

Transcription

1 Best Practice Guidelines for Computational Turbulent Dispersed Multiphase Flows René V.A. Oliemans ERCOFTAC Seminar, Innventia, Stockholm, June 7-8, Vermelding onderdeel organisatie Department of Multi-Scale Physics Acknowledgements Prof. Jos Derksen Un. of Alberta Dr. Muhamed Hadziabdic Un. Serajevo Prof. Hans Kuipers/dr. Niels Deen Un. Eindhoven Prof. Rob Mudde Delft Un. of Technology Prof. Dirk Roekaerts Delft Un. of Technology Prof. Alfredo Soldati/dr. Marchioli Un. Udine Prof. Martin Sommerfeld Martin-Luther Un. Prof. Berend van Wachem Imperial College Vermelding onderdeel organisatie 1

2 Contents Industrial flow challenges Requirements for CFD of dispersed multiphase flow Fundamentals Some Examples (bubbles, drops and particles flows) Sources of Errors Checklist of Best Practice Advice 3 Dispersed two-phase systems Gas-solid Gas-Droplet Liquid-solid Liquid-droplet Pneumatic conveying, cyclones, fluidized beds Spray-drying, -cooling, -painting,- scrubbers Hydraulic conveying, particle dispersion in stirred vessels, liquid-solid separation Stirred tank reactor, liquid-liquid extraction Liquid-bubble Bubble columns, aeration of sewage water, flotation, gas lift 4 2

3 CFD simulation of bubble column Lehr et al. (2002) 5 Grid configuration for bubble column CFD simulations by Laborde-Boutet et al. (2009) cells, no wall refinement cells+wall refinement 6 3

4 RANS (standard k-ε) simulations Laborde-Boutet et al. (2009) 7 Turbulence modelling and bubble population balance Computed liquid eddy length scales: Av. Eddy Size: 22 mm 19 mm 10 mm Measured average bubble size: 4.5 mm 8 4

5 3D simulation with bubble population balance and ten-fold bubble breakage Chen et al. 2005b 9 Liquid turbulent shear stress RANS + Exp. by Ong (2003) Chen et al. 2005b 10 5

6 Fluidized Beds 11 Fluidized Riser Flow Particle segregation dependent on size and turbulence Schuurmans (1980) 12 6

7 Riser reactor performance Conversion variation along the riser height Schuurmans (1980) 13 Contents Industrial flow challenges Requirements for CFD of dispersed multiphase flow Fundamentals Some Examples (bubbles, drops and particles flows) Sources of Errors Checklist of Best Practice Advice 14 7

8 Requirements for CFD of Industrial Turbulent Dispersed Multiphase Flows Aim:Mixing to optimize heat/mass transfer Fluid Flow aspects: Particles with various sizes in wall bounded flow fields Spatial and temporal distribution of the phases Particle coalescence and break-up Fluid/particle interactions Model validation Upscaling from laboratory 15 CFD Requirements for industrial dispersed multiphase flows Tool to examine complex, large scale systems Produce accurate wall-bounded turbulent flow fields Spatial and time-dependent distribution of phases Closure relations for averaged equations Fast, reliable and accurate computations Guide to handle enormous amount of simulation data 16 8

9 Particle volume fractions and sizes Bubble column α p = d= 1-30 mm Stirred tank reactor α p = d= µm Fluidized Beds α p = 0.40 d = µm Cyclone α p = d = 1-50 µm 17 Particle/Fluid interactions 18 9

10 Turbulence modulation (Gore and Crowe, 1989) 19 Contents Industrial flow challenges Requirements for CFD of dispersed multiphase flow Fundamentals Some Examples (bubbles, drops and particles flows) Sources of Errors Checklist of Best Practice Advice 20 10

11 Fundamentals Turbulence model? Particle/Fluid and Particle/Particle interactions? Computational Multiphase Flow Model? Numerical Solver and Grid Generator? 21 Turbulence Model for carrier fluid Numerical model Details of turbulence RANS (Reynolds Average Navier Stokes) No dynamics: just an integral length scale LES (Large Eddy Simulation) DNS (Direct Numerical Simulation) Dynamics of the most energetic eddies Dynamics of all eddies 22 11

12 Dispersed Phase fraction Volume fraction Mass fraction N i = number of particles in size fraction i V Pi = π D pi 3 /6 = particle volume U P, U F are particle/fluid velocities 23 Inter-particle spacing For p = 0.01: spacing ~ 4 D p For p = 0.10: spacing ~ 2 D p 24 12

13 Dispersed two-phase flow regimes Dilute Dispersed Two-Phase Flow Dense Dispersed Two-Phase Flow One-Way Coupling Two-Way Coupling Four-Way Coupling 25 Particle Tracking coupling mechanisms 26 13

14 Particle Response time Particle response time Stokes number Fluid flow time scale: 27 Models for Computational Dispersed Multiphase Flows DNS resolving the particles Extremely demanding in computing time and memory Discrete Particle Model (DPM) Used as learning tool in academia to study closure relations Euler-Lagrange (Particle Tracking) For dilute flows with various turbulence models: LES, RANS Euler-Euler (Two-Fluid) For intermediate to dense loadings with RANS 28 14

15 Eulerian-Lagrangian RANS: k-ε model with particles 29 Euler-Euler (Two-Fluid) simulations k=1: continuous phase; k=2:dispersed phase 30 15

16 Contents Industrial flow challenges Requirements for CFD of dispersed multiphase flow Fundamentals Some Examples (bubbles, drops and particles flows) Sources of Errors Checklist of Best Practice Advice 31 Bubbles in a Bubble column 1. Turbulence generated by bubbles injected at bottom 2. Radial distribution? 3. How to maximize bubble liquid interface? 4. Residence time of bubbles? 5. Flow regime affected by upscaling? 32 16

17 Simulation approach Euler-Euler needed due to high loading Turbulence with RANS Drag and gravity forces Wide size distribution: broad range of bubble velocities 2D steady state simulation on 20,000 nodes takes several hrs. On a single processor (1GHz) 3D transient simulations needed for oscillations 3D transient requires weeks per simulation! Compared to single-phase Two-Fluid model has to use coarse grids to keep computing times realistic 33 Influence of sparger Flow field Gas fraction (Double and single ring spargers, left and right, resp.) 34 17

18 Axial time-averaged liquid velocity Sanyal et al. (1999) 35 Gas fraction profile Sanyal et al

19 3D simulation Bubble column RANS with drag and gravity forces Lift force, needed for near-wall behaviour, unreliable Two-Fluid model with all bubbles moving at ensemble averaged mean velocity of dispersed phase Mixture model with all bubbles moving at ensemble averaged mean velocity of dispersed phase Mixture model with N+1 phases and different bubble size moving at different velocities 37 Radial gas fraction Chen et al. (2005) 38 19

20 Axial liquid velocity profiles Deen et al Turbulent kinetic energy profiles Deen et al

21 Status Bubble column simulation Mixture model is a cheap way for qualitative trends For dense bubbly flows coalescence and break-up can seriously change the flow field Multi-Fluid model for quantitative results Computational costs of adding more phases is large Bubble-break-up model needs attention Break-up and coalescence very sensitive to surfactants Euler-Euler with LES turbulence model promising 41 Stirred tank with glass beads in water LES snapshot Derksen (2003) 42 21

22 Stirred Tank Reactor Complex turbulent flow field Drop size Shape of drop size distribution Flow field variation with stirrer speed 43 Drops in a stirred tank reactor Experimental findings: Drop size decrease with increasing vessel size Shape of drop size distribution independent of vessel size and stirrer speed After change in stirrer speed a new steady state drop size distribution requires more stirrer revolutions for larger vessels (Colenbrander, 2000) 44 22

23 RANS results for bubbles in liquid Sliding mesh with matching frames and 48,000 cells Drag and gravity forces for particles in k-ε turbulent field (Issa, 1998) 45 Summary RANS findings Fine to establish impeller location Multiple frame approach useful Convergence problems due to equation coupling Liquid velocity close to impeller erroneous Gas hold-up values only qualitatively correct Turbulence intensities not accurate enough for break up and coalescence sub-models (Montante et al. (2001) and Issa (1998)) 46 23

24 LES for drops in stirred vessel Flow driven by Rushton turbine Lattice Boltzmann scheme Smagorinski constant 0.12 Uniform, cubic grid with 6 million nodes Parallel shared memory: CPU= 34 hrs./simulation Adaptive force fields for impeller and walls (Derksen et al. (1998,1999) 47 Angle resolved results simulation experiment simulation experiment k/v 2 tip Kinetic energy at 19 o behind the blade 48 24

25 Average turbulent fields Dissipation rate / av Turbulent kinetic energy k/v tip Evaluation of LES and RANS Guha et al. AIChE Journal 54 (2008) Experiments with Computer Automated Radioactive Particle Tracking (CARPT) Euler-Lagrange simulation with LES Euler-Euler simulation with RANS Overall solids hold-up of 1% by volume in STR with impeller speed of 17 revolutions/s and Re=74000 T=0.2 m, H=T; turbine blade D=T/3; water with solids of mean diameter of 0.3 mm 50 25

26 Simulated Flow pattern CARPT RANS LES 51 Radial profiles of solids radial velocity 52 26

27 Radial profiles of solids turbulent kinetic energy 53 Slip Reynolds number at impeller cross section 54 27

28 Axial variation of mean sojourn time 55 Conclusions LES/RANS evaluation Guha et al. (2008) Observed bottom recirculation loop stronger than top not found in either simulation Azimuthally averaged solid velocities with LES slightly better than with Euler-Euler RANS Solids turbulent kinetic energies, similar for both models, over-predict at impeller plane and underpredict at all other axial locations Slip velocities from RANS order of magnitude lower than those from LES Mean sojourn times from LES agree with experiments 56 28

29 Euler-Lagrange with bubble breakup and coalescence (Sungkorn et al 2011) 57 Euler-Lagrange with bubble breakup and coalescence (Sungkorn et al 2011) 58 29

30 Status stirred tank simulations Currently only data for bubbles and particles RANS fails to correctly predict both k and LES required for proper turbulence intensity LES applied in Euler-Lagrange with solids and gas With Bubble break-up and coalescence implemented, mean-diameter and av. liquid velocities agree with measurements in laboratory-scale reactors LES in lattice Boltzmann technique ready for higher loading of industrial interest 59 Recent literature on Stirred Tank Reactor simulations J.J. Derksen, Numerical simulation of solids suspension in a Stirred Tank, AIChE Journal 49 (2003) D.Gunha, P.A. Ramachandran, M.P. Dudukovic and J.J. Derksen, Evaluation of Large Eddy Simulation and Euler-Euler CFD models for solids flow dynamics in a stirred Tank reactor, AIChE Journal 54 (2008) R. Sungkorn, J.J. Derksen and J.G. Khinast, Euler-Lagrange modeling of gas-liquid stirred reactor with consideration of bubble breakage and coalescence, accepted paper AIChE Journal (2011) 30

31 Particle flow in a riser LES/DNS for continuous phase One-way coupling with gravity, drag, lift forces in a riser or channel Two-way coupling effects Collisions 61 Particle Tracking for riser flow One-way coupling Uijttewaal and Oliemans,

32 Particle dispersion 63 Particle deposition Dotted: exp. Diamonds: DNS 64 32

33 Particle wall transfer in upward turbulent pipe flow (Marchioli et al. (2003)) 65 Elongated particle clusters in a channel From top to bottom: t + = 0, 706, 1412, 2118 One-way DNS in vertical upward channel flow with Stokes drag, gravity and lift (Marchioli and Soldati (2002)) 66 33

34 Particle near-wall behaviour 67 Near-wall particle distribution and turbulent coherent structures t + = 1412 t + =1450 Green:counterclockwise Red: clockwise rotating vortices Blue dots:descending, black dots: ascending particles 68 34

35 Particle-Tracking results for wallbounded flows LES/DNS for continuous phase One-way coupling with gravity, drag, lift forces in a riser Two-way coupling effects in channel flow Collisions 69 Two-way point particle results Channel flow with point particles Normalwise Turbulence Intensity for increasing particle density (Portela, 2000) 70 35

36 Low speed streaks 71 unladen laden Particle-Tracking with collisions (Li et al., 2001) 72 36

37 Particle affected C µ 0.09 for Single phase flow 73 Status particle pipe flow simulation LES well established for Euler-Lagrange scheme Dispersion depends on particle size and turbulence Only point particles considered Drag, gravity and lift forces determine particle distribution in inhomogeneous turbulence Physics close to the wall important Particle wall accumulation affected by two-way coupling and collisions LES still too expensive for industrial use 74 37

38 Contents Industrial flow challenges Requirements for CFD of dispersed multiphase flow Fundamentals Some Examples (bubbles, drops and particles flows) Sources of Errors Checklist of Best Practice Advice 75 Sources of Errors Physical Mechanisms Closure models Time and length scales Governing Equations Numerical errors User errors 76 38

39 Contents Industrial flow challenges Requirements for CFD of dispersed multiphase flow Fundamentals Some Examples (bubbles, drops and particles flows) Sources of Errors Checklist of Best Practice Advice 77 Best Practice Advice Determine size distribution and volume fraction of particles injected 2. Assess particle forces: drag, gravity, lift,..? 3. Select appropriate models for the particle forces 4. For dilute flows ( d <10-3 ) use Euler-Lagrange 5. For intermediate flow (10-3 < d <4x10-1 ): Euler-Euler 6. Assess whether dynamics of carrier phase is needed 7. Select turbulence model 78 39

40 Best Practice Advice Make sure wall roughness is accounted for 9. For bubbles or droplets ensure break-up and coalescence models are available 10.Start with single-phase mesh-independent simulation 11.Continue multiphase simulations until for converged results sufficient data are available for particle statistics 79 Possibilities Multi-Fluid model for dense dispersed flow with turbulence modulation and collisions Euler-Lagrange models with LES/DNS for understanding basic physics Particle segregation in riser flow quantified Dependence of turbulence model constants on particle loading and size can be established 80 40

41 Limitations Closure of Multi-Fluid model Euler-Lagrange for point particles with volume fractions up to 0.01 Computing time/memory Validation Dealing with large amount of simulation data Transfer from Academia to Industry 81 Best Practice Guidelines Best Practice Guidelines for Industrial Computational Fluid Dynamics, ERCOFTAC (2000) Best Practice Guideliens for Computational Dispersed Multiphase Flows, ERCOFTAC-SIAMUF (2008) Available via ERCOFTAC website (

42 Technology Transfer? 83 Technology Transfer? 84 42