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Transient growth in turbulent particle-laden channel flow

  • Yang Song
  • Chunxiao XuEmail author
  • Weixi Huang
  • Lili Wang
Research Paper
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Abstract

Linear transient growth of optimal perturbations in particle-laden turbulent channel flow is investigated in this work. The problem is formulated in the framework of a Eulerian–Eulerian approach, employing two-way coupling between fine particles and fluid flow. The model is first validated in laminar cases, after which the transient growth of coherent perturbations in turbulent channel flow is investigated, where the mean particle concentration distribution is obtained by direct numerical simulation. It is shown that the optimal small-scale structures for particles are streamwise streaks just below the optimal streamwise velocity streaks, as was previously found in numerical simulations of particle-laden channel flow. This indicates that the optimal growth of perturbations is a dominant mechanism for the distribution of particles in the near-wall region. The current study also considers the transient growth of small- and large-scale perturbations at relatively high Reynolds numbers, which reveals that the optimal large-scale structures for particles are in the near-wall region while the optimal large-scale structures for fluid enter the outer region.

Keywords

Optimal transient growth Wall turbulence Coherent structures Particle-laden turbulence 

Notes

Acknowledgements

We would like to express our sincere gratitude to Professor Luca Brandt, who gave us great help by providing us with necessary materials and valuable advice.

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Copyright information

© The Chinese Society of Theoretical and Applied Mechanics and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Yang Song
    • 1
    • 2
  • Chunxiao Xu
    • 2
    Email author
  • Weixi Huang
    • 2
  • Lili Wang
    • 1
  1. 1.Institute of Applied Physics and Computational MathematicsBeijingChina
  2. 2.AML, Department of Engineering MechanicsTsinghua UniversityBeijingChina

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