DNS coupled with a Point-Particle based model (PP) is used to study and predict particle-turbulence interactions in an open channel flow at Reynolds number of 811 (based on the friction velocity) corresponding to the experimental observations of [Righetti & Romano, JFM 2004]. Large particles of diameter 200 microns (8.1 in wall units) with average volume loading on the order of 0.001 are simulated using four-way coupling with closure models for drag, added mass, lift, pressure, and inter-particle/particle-wall collision forces. The point-particle model is able to accurately capture the effect of particles on the fluid flow in the outer layer where particles are under resolved. However, the dynamical interaction of particle-turbulence is under predicted in the near wall region where particles size are much larger than Kolmogorov scale and grid resolution in wall-normal direction, but smaller in both stream and span wise directions. It is conjectured that due to the large size particles compared to the Kolmogorov length scale near the bed, the effect of disturbances and deflections in the flow due to presence of such large particles is not captured using Lagrangian Point-Particle approach. For this configuration, the point-particle model is not appropriate in the near wall region and a hybrid resolved particle approach may be necessary.
- Fluids Engineering Division
On the Predictive Capability of DNS-DEM Applied to Suspended Sediment-Turbulence Interactions
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Pakseresht, P, Apte, SV, & Finn, JR. "On the Predictive Capability of DNS-DEM Applied to Suspended Sediment-Turbulence Interactions." Proceedings of the ASME 2017 Fluids Engineering Division Summer Meeting. Volume 1B, Symposia: Fluid Measurement and Instrumentation; Fluid Dynamics of Wind Energy; Renewable and Sustainable Energy Conversion; Energy and Process Engineering; Microfluidics and Nanofluidics; Development and Applications in Computational Fluid Dynamics; DNS/LES and Hybrid RANS/LES Methods. Waikoloa, Hawaii, USA. July 30–August 3, 2017. V01BT11A025. ASME. https://doi.org/10.1115/FEDSM2017-69449
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