best practice guidelines for computational turbulent ... · gas-solid gas-droplet pneumatic...

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Vermelding onderdeel organisatie

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Best Practice Guidelines for Computational Turbulent Dispersed Multiphase Flows

René V.A. Oliemans

ERCOFTAC Seminar, Innventia, Stockholm, June 7-8, 2011

Department of Multi-Scale Physics

Vermelding onderdeel organisatie

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

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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

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Dispersed two-phase systems

Gas-solid

Gas-Droplet

Pneumatic conveying, cyclones, fluidized beds Spray-drying, -cooling, -painting,- scrubbers

Liquid-solid Hydraulic conveying, particle dispersion in stirred vessels, liquid-solid separation

Liquid-droplet Stirred tank reactor, liquid-liquid extraction

Liquid-bubble Bubble columns, aeration of sewage water, flotation, gas lift

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CFD simulation of bubble column

Lehr et al. (2002)

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Grid configuration for bubble column

36288 cells, no wall refinement 247050 cells+wall refinement

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CFD simulations by Laborde-Boutet et al. (2009)

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RANS (standard k-ε) simulations

Laborde-Boutet et al. (2009)

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Turbulence modelling and bubble population balance

Av. Eddy Size: 22 mm 19 mm 10 mm

Measured average bubble size: 4.5 mm

Computed liquid eddy length scales:

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3D simulation with bubble population balance and ten-fold bubble breakage

Chen et al. 2005b

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Liquid turbulent shear stress

Chen et al. 2005b

RANS +

Exp. by Ong (2003)

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Fluidized Beds

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Fluidized Riser Flow

Particle segregation dependent on size and turbulence

Schuurmans (1980)

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Riser reactor performance

Conversion variation along the riser height

Schuurmans (1980)

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Contents


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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

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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

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Particle volume fractions and sizes

Bubble column αp = 0.10-0.40 d= 1-30 mm

Stirred tank reactor αp = 0.02-0.40 d= 5 – 500 µm

Fluidized Beds αp = 0.40 d = 50 – 1000 µm

Cyclone αp = 0.001 d = 1 - 50 µm

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Particle/Fluid interactions

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Turbulence modulation

(Gore and Crowe, 1989)

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Contents


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Fundamentals

•  Turbulence model? •  Particle/Fluid and Particle/Particle interactions? •  Computational Multiphase Flow Model? •  Numerical Solver and Grid Generator?

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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) Dynamics of the most energetic eddies

DNS (Direct Numerical Simulation)

Dynamics of all eddies

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Dispersed Phase fraction

Ni = number of particles in size fraction i

VPi = π Dpi3 /6 = particle volume

Volume fraction Mass fraction

UP , UF are particle/fluid velocities

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Inter-particle spacing

For αp = 0.01: spacing ~ 4 Dp

For αp = 0.10: spacing ~ 2 Dp

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Dispersed two-phase flow regimes

Dilute Dispersed Two-Phase Flow

One-Way Coupling

Two-Way Coupling

Dense Dispersed Two-Phase Flow

Four-Way

Coupling

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Particle Tracking coupling mechanisms

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Particle Response time

Particle response time Stokes number

Fluid flow time scale:

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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

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Eulerian-Lagrangian RANS: k-ε model with particles

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Euler-Euler (Two-Fluid) simulations

k=1: continuous phase; k=2:dispersed phase

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Contents


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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?

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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

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Influence of sparger

Flow field Gas fraction (Double and single ring spargers, left and right, resp.)

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Axial time-averaged liquid velocity

Sanyal et al. (1999)

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Gas fraction profile

Sanyal et al. 1999

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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

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Radial gas fraction

Chen et al. (2005)

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Axial liquid velocity profiles

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Deen et al 2001

Turbulent kinetic energy profiles

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Deen et al 2001

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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

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Stirred tank with glass beads in water LES snapshot

Derksen (2003)

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Stirred Tank Reactor

•  Complex turbulent flow field •  Drop size •  Shape of drop size distribution •  Flow field variation with stirrer speed

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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)

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RANS results for bubbles in liquid

Sliding mesh with matching frames and 48,000 cells

(Issa, 1998)

Drag and gravity forces for particles in k-ε turbulent field

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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))

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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)

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Angle resolved results simulation

experiment

0.0

0.045 0.030

0.075 0.060

0.090

0.015

0.135 0.120 0.105

k/vtip2 simulation

experiment

Kinetic energy at 19o behind the blade

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Average turbulent fields Turbulent kinetic energy

k/vtip2

0.1

0.025

0.006

0.003

0.0015

0.0004

Dissipation rate ε/εav

10.0 3.0 1.0 0.3 0.1 0.03 0.01 0.003 0.001

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Evaluation of LES and RANS Guha et al. AIChE Journal 54 (2008) 766-778

•  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

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Simulated Flow pattern

CARPT RANS LES

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Radial profiles of solids radial velocity

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Radial profiles of solids turbulent kinetic energy

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Slip Reynolds number at impeller cross section

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Axial variation of mean sojourn time

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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 under-predict 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

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

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

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Status stirred tank simulations

•  Currently only data for bubbles and particles •  RANS fails to correctly predict both k and ε •  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

Recent literature on Stirred Tank Reactor simulations

•  J.J. Derksen, “Numerical simulation of solids suspension in a Stirred Tank”, AIChE Journal 49 (2003) 2700-2714

•  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) 766-778

•  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)

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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

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Particle Tracking for riser flow

Uijttewaal and Oliemans, 1996

One-way

coupling

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Particle dispersion

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Particle deposition

Dotted: exp.

Diamonds: DNS

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Particle wall transfer in upward turbulent pipe flow

(Marchioli et al. (2003))

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Elongated particle clusters in a channel

From top to bottom: t+= 0, 706, 1412, 2118

(Marchioli and Soldati (2002))

One-way DNS in vertical upward channel flow with Stokes drag, gravity and lift

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Particle near-wall behaviour

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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

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Particle-Tracking results for wall-bounded 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

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Two-way point particle results

(Portela, 2000)

Normalwise Turbulence Intensity

for increasing particle density

Channel flow with point particles

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Low speed streaks

unladen laden

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Particle-Tracking with collisions

(Li et al., 2001)

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Particle affected Cµ

0.09 for Single phase flow

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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

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Contents


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Sources of Errors

•  Physical Mechanisms •  Closure models •  Time and length scales •  Governing Equations •  Numerical errors •  User errors

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Contents


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Best Practice Advice -1

1.  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 (αd<10-3) use Euler-Lagrange 5.  For intermediate flow (10-3< αd<4x10-1): Euler-Euler 6.  Assess whether dynamics of carrier phase is needed 7.  Select turbulence model

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Best Practice Advice -2

8. 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

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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

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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

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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 (www.ercoftac.org)

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Technology Transfer?

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Technology Transfer?

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