Using RANS turbulence models and Lagrangian approach to predict particle deposition in turbulent channel flows

Naiping Gao, Jianlei Niu, Qibin He, Tong Zhu, Jiazheng Wu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

74 Citations (Scopus)


This study investigates the capability and accuracy of three Reynolds-Averaged Navier-Stokes (RANS) turbulence models, i.e. a Reynolds stress model (RSM), a RNG k-ε model, and an SST k-ω model in the prediction of particle deposition in vertical and horizontal turbulent channel flows. The particle movement was simulated using a Lagrangian-based discrete random walk (DRW) model. The performances of the three RANS turbulence models with and without near-wall turbulence corrections were evaluated. A new modification method for turbulence kinetic energy was proposed for the RNG k-ε model and the SST k-ω model. The results were compared with previous experimental data, empirical equation as well as simulation outcomes. It is found that the isotropic SST k-ω model and the RSM model can successfully predict the transition from the diffusion region to the inertia-moderated region. The RNG k-ε model with near-wall modifications can also reflect the V-shape deposition curve although without modifications it greatly over-predicts the deposition velocity and shows an almost straight deposition line. For all of the three turbulence models, application of near-wall corrections is able to improve the simulation results to different extents.
Original languageEnglish
Pages (from-to)206-214
Number of pages9
JournalBuilding and Environment
Issue number1
Publication statusPublished - 1 Feb 2012


  • Discrete random walk model
  • Near-wall correction
  • Particle deposition
  • RANS turbulence models

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Geography, Planning and Development
  • Building and Construction


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