Advertisement

An assessment of k-ε turbulence models for gas distribution analysis

  • Muhammad Saeed
  • Ji-Yang Yu
  • Aniseh Ahmed Atef Abdalla
  • Xian-Ping Zhong
  • Mahmood Ahmad Ghazanfar
Article
  • 52 Downloads

Abstract

This paper presents the gas distribution analysis by injecting air fountain into the containment and simulations with the HYDRAGON code. Turbulence models of standard k-ε (SKE), re-normalization group k-ε (RNG) and a realizable k-ε (RLZ) are used to assess the effects on the gas distribution analysis during a severe accident in a nuclear power plant. By comparing with experimental data, the simulation results of the RNG and SKE turbulence models agree well with the experimental data on the prediction of dimensionless density distributions. The results illustrate that the turbulence model choice had a small effect on the simulation results, particularly the region near to the air fountain source.

Keywords

Turbulence model Hydrogen combustion Nuclear power Plant accident HYDRAGON Air fountain 

Notes

Acknowledgements

The authors highly acknowledge the support of the National key Lab of Reactor System Design Technology Chengdu, China. Mr. Muhammad Saeed also acknowledges the Chinese Scholarship Council for the award of Doctoral study.

Supplementary material

41365_2017_304_MOESM1_ESM.docx (1.1 mb)
Supplementary material 1 (DOCX 1125 kb)

References

  1. 1.
    D.C. Visser, M. Houkema, N.B. Siccama et al., Validation of a FLUENT CFD model for hydrogen distribution in a containment. Nucl. Eng. Des. 245, 161 (2012). doi: 10.1016/j.nucengdes.2012.01.025 CrossRefGoogle Scholar
  2. 2.
    IAEA, Mitigation of hydrogen hazard in severe accident in nuclear power plants, International Atomic Energy Agency, Vienna (2011). IAEA TECDOC No. 1661Google Scholar
  3. 3.
    J. Zhang, M.A. Delichatsios, A.G. Venetsanos, Numerical studies of dispersion and flammable volume of hydrogen in enclosures. Int. J. Hydrog. Energy 35(12), 6431 (2010). doi: 10.1016/j.ijhydene.2010.03.107 CrossRefGoogle Scholar
  4. 4.
    J. Deng, X. Cao, Hydrogen and steam distribution following a small-break LOCA in large dry containment. Nucl. Sci. Tech. 18(3), 181 (2007). doi: 10.1016/S1001-8042(07)60043-8 CrossRefGoogle Scholar
  5. 5.
    Z.J. Xiao, S.Z. Qiu, W.B. Zhuo et al., The development and verification of thermal-hydraulic code on passive residual heat removal system of Chinese advanced PWR. Nucl. Sci. Tech. 17(5), 301 (2006). doi: 10.1016/S1001-8042(06)60057-2 CrossRefGoogle Scholar
  6. 6.
    T.F. Kanzleiter, K.O. Fischer, Multi-Compartment hydrogen deflagration experiments and model development. Nucl. Eng. Des. 146, 417 (1994). doi: 10.1016/0029-5493(94)90347-6 CrossRefGoogle Scholar
  7. 7.
    R.E. Henry, C.Y. Paik, M.G. Plys, MAAP4-modular accident analysis program for LWR plants code manual, FAI (1994)Google Scholar
  8. 8.
    H.A. Olvera, A.R. Choudhuri, Numerical simulation of hydrogen dispersion in the vicinity of a cubical building in stable stratified atmospheres. Int. J. Hydrog. Energy 31(15), 2356 (2006). doi: 10.1016/j.ijhydene.2007.08.028 CrossRefGoogle Scholar
  9. 9.
    A.G. Venetsanos, T. Huld, P. Adams et al., Source, dispersion and combustion modelling of an accidental release of hydrogen in an urban environment. J. Haz. Mater. 105(1), 1 (2003). doi: 10.1016/j.jhazmat.2003.05.001 CrossRefGoogle Scholar
  10. 10.
    Z. Cheng, V. Agranat, A.V. Tchouvelev et al., PRD hydrogen release and dispersion, a comparison of CFD results obtained from using ideal and real gas law properties. First international conference on hydrogen safety (Pisa, Italy, 8–10 Sept 2005)Google Scholar
  11. 11.
    H. Wilkening, D. Baraldi, CFD modelling of accidental hydrogen release from pipelines. Int. J. Hydrog. Energy 32(13), 2206 (2007). doi: 10.1016/j.ijhydene.2007.04.022 CrossRefGoogle Scholar
  12. 12.
    R. Fotis, S. Sklavounos, Evaluation of hazards associated with hydrogen storage facilities. Int. J. Hydrog. Energy 30(13), 1501 (2005). doi: 10.1016/j.ijhydene.2005.06.004 Google Scholar
  13. 13.
    J. Kim, S.W. Hong, S.B. Kim et al., Three-dimensional behaviors of the hydrogen and steam in the APR1400 containment during a hypothetical loss of feed water accident. Ann. Nucl. Energy 34, 992 (2007). doi: 10.1016/j.anucene.2007.05.003 CrossRefGoogle Scholar
  14. 14.
    P. Middha, O.R. Hansen, CFD simulation study to investigate the risk from hydrogen vehicles in tunnels. Int. J. Hydrog. Energy 34(14), 5875 (2009). doi: 10.1016/j.ijhydene.2009.02.004 CrossRefGoogle Scholar
  15. 15.
    P. Middha, O.R. Hansen, I.E. Storvik, Validation of CFD-model for hydrogen dispersion. J. Haz. Mater. 22(6), 1034 (2009). doi: 10.1016/j.jlp.2009.07.020 Google Scholar
  16. 16.
    P. Middha, O.R. Hansen, J. Grune et al., CFD calculations of gas leak dispersion and subsequent gas explosions: validation against ignited impinging hydrogen jet experiments. J. Haz. Mater. 179(1), 84 (2010). doi: 10.1016/j.jhazmat.2010.02.061 CrossRefGoogle Scholar
  17. 17.
    M. Heitsch, R. Huhtanen, Z. Techy et al., CFD evaluation of hydrogen risk mitigation measures in a VVER-440/213 containment. Nucl. Eng. Des. 240(2), 385 (2010). doi: 10.1016/j.nucengdes.2008.07.022 CrossRefGoogle Scholar
  18. 18.
    D.M. Prabhudharwadkar, K.N. Iyer, N. Mohan et al., Simulation of hydrogen distribution in an Indian nuclear reactor containment. Nucl. Eng. Des. 241, 832 (2011). doi: 10.1016/j.nucengdes.2010.11.012 CrossRefGoogle Scholar
  19. 19.
    D. Baraldi, A. Kotchourko, A. Lelyakin, An inter-comparison exercise on CFD model capabilities to simulate hydrogen deflagrations in a tunnel. Int. J. Hydrog. Energy 34(18), 7862 (2009). doi: 10.1016/j.ijhydene.2009.06.055 CrossRefGoogle Scholar
  20. 20.
    J. Xiao, J.R. Travis, How critical is turbulence modeling in gas distribution simulations of large-scale complex nuclear reactor containments? Ann. Nucl. Energy 56, 227 (2013). doi: 10.1016/j.anucene.2013.01.016 CrossRefGoogle Scholar
  21. 21.
    E. Deri, M. Bucci, E. Studer et al., Analytical and computational analysis of turbulent buoyant jets in the containment atmosphere, in Proceedings of the 16th International Conference on Nuclear Engineering, ICONE16-48237: 689698 (2008). doi: 10.1115/ICONE16-48237
  22. 22.
    A.A. Abdalla, J. Yu, M. Alrwashdeh, Application of some turbulence models to simulate buoyancy-driven flow, in Proceedings of the 2014 22nd International Conference on Nuclear Engineering (2014). doi: 10.1115/ICONE22-30060
  23. 23.
    M. Saeed, J. Yu, B. Hou et al., Numerical distribution of hydrogen inside a compartment using HYDRAGON code, in Proceedings of the 2016 24th International Conference on Nuclear Engineering, ICONE24-60610 (2016). doi: 10.1115/ICONE24-60610
  24. 24.
    E. Deri, B. Cariteau, D. Abdo, Air fountain in the erosion of gaseous stratification. Int. J. Heat Fluid Flow 31, 935 (2010). doi: 10.1016/j.ijheatfluidflow.2010.05.003 CrossRefGoogle Scholar
  25. 25.
    V. Agarant, Z. Cheng. A. Tchouvelev. CFD modeling of hydrogen releases and dispersion in hydrogen energy station, in Proceeding of WHEC-15, Yokohama (2004)Google Scholar
  26. 26.
    D.C. Wilcox, Formulation of the kω turbulence model revisited. AIAA J. 46(11), 2823–2838 (2008). doi: 10.2514/6.2007-1408 CrossRefGoogle Scholar
  27. 27.
    Z.U.A. Warsi, Fluid dynamics: theoretical and computational approaches, 3rd edn. (CRC press, 2006). ISBN 9780849333972 - CAT# 3397Google Scholar
  28. 28.
    J.P.S. Sanders, B. Sarh, H. Gokalp, Variable density effects in axisymmetric isothermal turbulence jet: a comparison between a first and second order turbulence model. Int. J. Heat Mass Transf. 40(4), 823 (1997). doi: 10.1016/0017-9310(96)00151-2 CrossRefMATHGoogle Scholar
  29. 29.
    M. Latif, C. Masson, T. Stathopoulos et al., Comparison of various types of k-ε models for pollutant emissions around a two-building configuration. J. Wind Eng. Ind. Aerodyn. 115, 9–21 (2013). doi: 10.1016/j.jweia.2013.01.001 CrossRefGoogle Scholar
  30. 30.
    Z. Xie, Y. Yang, H. Gu et al., Numerical analysis of turbulent mixed convection air flow in inclined plane channel with k-ɛ type turbulence model. J Nucl. Sci. Techol. 19(2), 121 (2008). doi: 10.1016/S1001-8042(08)60036-6 CrossRefGoogle Scholar
  31. 31.
    W.P. Jones, B.E. Lanuder, The prediction of laminarization with a two-equation model of turbulence. Int. J. Heat Mass Transf. 15(2), 301 (1972). doi: 10.1016/0017-9310(72)90076-2 CrossRefGoogle Scholar
  32. 32.
    G. Biswas, V. Eswaran, Turbulent Flow, Fundamental, Experiments and Modeling (England) (Alpha Science International Ltd, Pangbourne, 2002)MATHGoogle Scholar
  33. 33.
    M. Andreani, R. Kapulla, R. Zboray, Gas Stratification break-up by a vertical jet: simulations using the GOTHIC Code. Nucl. Eng. Des. 249, 71 (2012). doi: 10.1016/j.nucengdes.2011.06.004 CrossRefGoogle Scholar
  34. 34.
    F.S. Lien, E. Yee, H. Ji et al., Progress and challenges in the development of physically-based numerical models for prediction of flow and contaminant dispersion in the urban environment. Int. J. Comput. Fluid Dyn. 20, 323 (2006). doi: 10.1080/10618560600898528 CrossRefMATHGoogle Scholar
  35. 35.
    V.O. Yakhot, S.A. Orszag, S. Thangam et al., Development of turbulence models for shear flows by a double expansion technique. Phys. Fluids A4, 1510 (1992). doi: 10.1063/1.858424 CrossRefMATHMathSciNetGoogle Scholar
  36. 36.
    T.H. Shih, W.W. Liou, A. Shabbir et al., A new k-ε eddy viscosity model for high Reynolds number turbulent flows. Comput. Fluids 24, 227 (1995). doi: 10.1016/0045-7930(94)00032-T CrossRefMATHGoogle Scholar
  37. 37.
    W.P. Jones, B.E. Launder, The prediction of laminarization with a two-equation model of turbulence. Int. J. Heat Mass Transf. 15, 301 (1995). doi: 10.1016/0017-9310(72)90076-2 CrossRefGoogle Scholar
  38. 38.
    A. Suryan, H.D. Kim, T. Setoguchi, Comparative study of turbulence models performance for refueling of compressed hydrogen tanks. Int. J. Hydrog. Energy 38, 9562 (2013). doi: 10.1016/j.ijhydene.2012.07.055 CrossRefGoogle Scholar
  39. 39.
    S.M. Tauseef, D. Rashtchian, S.A. Abbasi, CFD-based simulation of dense gas dispersion in presence of obstacles. J. Loss Prev. Process Ind. 24(4), 371 (2011). doi: 10.1016/j.jlp.2011.01.014 CrossRefGoogle Scholar
  40. 40.
    T.R. Marrero, E.A. Mason, Gaseous diffusion coefficients. J. Phys. Chem. Ref. Data 1, 3 (2009). doi: 10.1063/1.3253094 CrossRefGoogle Scholar

Copyright information

© Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Chinese Nuclear Society, Science Press China and Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Muhammad Saeed
    • 1
  • Ji-Yang Yu
    • 1
  • Aniseh Ahmed Atef Abdalla
    • 1
  • Xian-Ping Zhong
    • 1
  • Mahmood Ahmad Ghazanfar
    • 1
  1. 1.Department of Engineering PhysicsTsinghua UniversityBeijingChina

Personalised recommendations