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Energy Technology and Innovation Initiative Faculty of Engineering Comparison of RANS and LES Turbulence Models for Predicting Air-coal and Oxy-coal Combustion Behaviours 2 nd International Oxyfuel Combustion Conference 12 th – 16 th September 2011, Yeppoon, Australia Co-authors: D. Caridi a , D. Couling b , M. Gharebaghi, S.R. Gubba, R.M.A. Irons b , L. Ma, M. Pourkashanian and A. Williams a ANSYS UK b E.ON New Build and Technology, UK Alessandro Pranzitelli

Comparison of RANS and LES Turbulence Models for ...Conclusions and way forward Hybrid turbulence models Reduction of the number of cells / reduction of the CPU time . Conclusions

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  • School of something FACULTY OF OTHER

    Energy Technology and Innovation Initiative Faculty of Engineering

    Comparison of RANS and LES Turbulence Models for Predicting Air-coal and Oxy-coal

    Combustion Behaviours

    2nd International Oxyfuel Combustion Conference 12th – 16th September 2011, Yeppoon, Australia

    Co-authors: D. Caridia, D. Coulingb, M. Gharebaghi, S.R. Gubba, R.M.A. Ironsb,

    L. Ma, M. Pourkashanian and A. Williams

    a ANSYS UK b E.ON New Build and Technology, UK

    Alessandro Pranzitelli

  • Outline

    Introduction

    The E.ON Combustion Test Facility

    Numerical modelling

    Air-coal combustion

    Oxy-coal combustion

    Conclusions

  • Introduction

    Low

    Low

    High

    Conc

    ern

    Ove

    r av

    aila

    bilit

    y of

    Phy

    sica

    l Mod

    el s

    Radiation

    HT

    NOx-SOx

    Soot Formation

    Fouling Char

    Oxidation

    RANS Devolatilisation

    TRI

    Slagging TCI

    LES

    Volatile Combustion

    Hg/Cl Metal release

    LT Corrosion

    Particle tracking

    Ignition

    Impact On Oxy-Fuel CFD Simulation Accuracy

    High

  • E.ON Combustion Test Facility (CTF)

    Located in Ratcliffe-on-Soar, UK

    1 MWth

    Single, wall-fired, low NOx burner

    Variety of fuels (coal, gas, biomass, … )

    Time-temperature scaled to 500 MW facility

    Particle separation by cyclones

  • Test conditions

    Air-coal (Thoresby)

    Thoresby (UK) El Cerrejon (S. America) Cutacre (UK)

    Ultimate analysis (%) DAF

    C 80.6 78.9 78.5

    H 6.2 5.5 4.9

    O 9.6 13 7.5

    N 1.9 1.7 1.7

    S 1.7 0.9 7.4

    Proximate analysis (%) AR

    Ash 15.8 7.5 24.7

    Moisture 2.8 3.4 6.1

    VM 30 36.9 27.7

    HCV(MJ/kg) 27.1 27.2 32.6

    Oxy-coal (El Cerrejon + Cutacre)

    Coal analysis

    Flow rate (kg/h) Temperature (K)

    Coal 131.5 ± 0.1 353

    Primary 260 ± 4 353 ± 0.1

    Secondary 1120 ± 12 563 ± 0.8

    Flow rate (kg/h) Temperature (K)

    Coal 146.3 ± 0.1 353

    Primary 183 ± 4 353 ± 0.1

    Secondary 1033 ± 12 509 ± 0.8

  • CFD simulations: approach

    commercial code: ANSYS® FLUENT V12.1

    Preparation of the geometry

    Mesh generation

    Steady RANS simulation

    LES

    Hardware: • RANS: 1 quad-core intel® Q9550, 2.83GHz processor, 8GB RAM • LES: Leeds’ ARC1 HPC cluster, 50 intel® Nehalem X5560, 2.8GHz CPU cores, 2GB RAM/core

    CPU time: • RANS: ≈25 days • LES: ≈15 days/second of simulation

  • Grid, the EON CTF

    3M cells, RANS and LES

    Unstructured, regular cell distribution Mostly hexahedral cells, small number of polyhedral cells High quality, low cell aspect ratio and squish, no tetrahedral cells

    80% of Turbulent Kinetic Energy should be resolved

    in the LES

    Complex geometry for CFD simulations

    Complex problem, several models required

    High quality mesh required for the LES

    ε

    5.1

    0

    kL =

    120Llcell =Cell sizing:

  • Computational grid

  • Sub-models

    RANS: steady, standard k-ε, wall functions

    LES: WALE sub-grid scale model

    Radiation: discrete ordinate, WSGGM

    Turbulence-chemistry interaction: eddy dissipation

    Two-step global reaction for volatile combustion

    Devolatilization: single rate

    Char combustion: intrinsic model

  • Air-coal combustion RANS

    top view

    side view

    Predicted Temperature (K)

  • Air-coal combustion RANS vs LES

    RANS LES (instantaneous values)

    Predicted Temperature distribution (K)

  • Oxy-coal combustion RANS vs LES

    RANS LES (instantaneous values)

    Temperature distribution (K)

  • Oxy-coal combustion flame

    RANS LES (inst.) LES (mean)

  • Oxy-coal combustion LES

  • Gas temperature air- and oxy-coal combustion

    vertical mid plane, distance from the burner centre line

    Oxy-coal Air-coal

  • Mean values at the exhaust

    Exp. RANS LES

    Air-fired

    Temperature (k) 1180±50 1232 1282

    O2 (%, dry) 3.1±0.5 3.7 2.2

    CO (ppm) 11±5 25 50

    NO (mg/MJ) 310±10 340 365

    LOI (%) 3.9 3.0 2.0

    Oxy-fired

    Temperature (k) 1383±50 1533 1523

    O2 (%, dry) 4.5±0.5 6.0 6.0

    CO (ppm) 35±5 68 50

    NO (mg/MJ) 151±10 406 380

    LOI (%) NA 4.6 6.1

  • Conclusions and way forward

    Hybrid turbulence models Reduction of the number of cells / reduction of the CPU time

    Conclusions

    Good results by RANS for air-coal combustion

    Improvement of the results by LES for air-coal combustion

    Temperature overestimation for oxy-coal combustion

    Need of specific sub-models for oxy-coal combustion, i.e. non-gray

    gas radiation model

    Way forward

    Non-gray gas model (FSK) Improvement of the results

  • Acknowledgements

    Financial support from UK EPSRC (OXY-CAP UK/RCUK-China), Dorothy Hodgkin Postgraduate Awards/EON is gratefully acknowledged.

    Contact details: Dr Alessandro Pranzitelli [email protected]

    References: M. Gharebaghi, R.M.A. Irons, L. Ma, M. Pourkashanian, A. Pranzitelli “Large eddy simulation of oxy-coal combustion in an industrial combustion test facility”. Int. J. Greenhouse Gas Control (2011), doi:10.1016/j.ijggc.2011.05.030

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