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On the inverse kinetic energy cascade in premixed isotropic turbulent flames

Author

Listed:
  • Xiang Qian

    (State Key Laboratory of Coal Combustion, School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, P. R. China)

  • Hao Lu

    (State Key Laboratory of Coal Combustion, School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, P. R. China)

  • Chun Zou

    (State Key Laboratory of Coal Combustion, School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, P. R. China)

  • Hong Yao

    (State Key Laboratory of Coal Combustion, School of Energy and Power Engineering, Huazhong University of Science and Technology, Wuhan 430074, P. R. China)

Abstract

The understanding of energy transfer in fluids is important for the accurate modeling of turbulent reacting flows. In this study, we investigate interscale kinetic energy transfer and subgrid-scale (SGS) backscatter using data from direct numerical simulations (DNSs) of premixed isotropic turbulent flames. Results reveal that in the examined premixed flames, the pressure transfer term appearing in the transport equation of turbulent kinetic energy dominates the nonlinear advection and the dissipation at large scales, and noticeably contributes to the inverse kinetic energy cascade. Filtered DNS data show that SGS backscatter is correlated with the appearance of positive pressure-dilatation work, i.e. thermal expansion. A priori test results of three SGS stress models reveal that the Smagorinsky stress model is unable to capture SGS backscatter, but that two nonlinear structural stress models are able to predict SGS backscatter.

Suggested Citation

  • Xiang Qian & Hao Lu & Chun Zou & Hong Yao, 2022. "On the inverse kinetic energy cascade in premixed isotropic turbulent flames," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 33(01), pages 1-16, January.
    • Handle: RePEc:wsi:ijmpcx:v:33:y:2022:i:01:n:s0129183122500152
    DOI: 10.1142/S0129183122500152
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