Particle concentration variation for inflow profiles in high reynolds number turbulent boundary layer
KAUST DepartmentFluid and Plasma Simulation Group (FPS)
Mechanical Engineering Program
Physical Science and Engineering (PSE) Division
KAUST Grant NumberURF/1/1704-01-01
Online Publication Date2020-10-12
Print Publication Date2020-07-13
Permanent link to this recordhttp://hdl.handle.net/10754/665881
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AbstractLarge-eddy simulations (LES) of incompressible turbulent boundary-layer flows can simulate a fundamental unsteady turbulent flow, including time-variant streamwise and wall-normal velocity as well as the near-wall locations of significant turbulence intensities. A typical illustration of turbulent flows with such high Reynolds numbers can be roughly approximated to atmospheric boundary-layer flows. To bypass the demanding mesh criteria of near-ground field and direct numerical simulations, we adopt a virtual-wall model with a stretched-vortex subgrid-scale model. We simulate the dynamics of solid particles in this wall-modeled LES approach toward incompressible flow. The particles considered are both charged and uncharged, and have a fixed concentration profile with no fluctuations at the inflow. An extended streamwise simulation domain is implemented as an alternative to rerunning the simulation with a turbulent inflow profile from the simulation of the previous downstream profile. By extending the streamwise domain, the fluctuation dynamics of the particles reach a steady state far downstream from the inflow. The streamwise and altitude variation of the particle parameters are compared for various particle-concentration inflow profiles. Furthermore, an estimate of the streamwise variation of parameters is also observed. This study is the first step towards enhancing our understanding of the particle dynamics in turbulent flows.
CitationRahman, M. M., & Samtaney, R. (2020). Particle Concentration Variation for Inflow Profiles in High Reynolds Number Turbulent Boundary Layer. Volume 2: Fluid Mechanics; Multiphase Flows. doi:10.1115/fedsm2020-20293
SponsorsThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST) through the KAUST Office of Competitive Research Funds (OCRF) under Award No. URF/1/1704-01-01 and KAUST baseline research fund BAS/1/1349-01-1. The Cray XC40 Shaheen II at KAUST was utilized for the simulations. Some of the results documented here were also presented at the ASME AJKFLUIDS 2019 .
Conference/Event nameASME 2020 Fluids Engineering Division Summer Meeting, FEDSM 2020, collocated with the ASME 2020 Heat Transfer Summer Conference and the ASME 2020 18th International Conference on Nanochannels, Microchannels, and Minichannels