Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session A32: Applied Computational Fluid Dynamics I
8:00 AM–9:57 AM,
Sunday, November 18, 2018
Georgia World Congress Center
Room: B404
Chair: Omar Matar, Imperial College London
Abstract ID: BAPS.2018.DFD.A32.4
Abstract: A32.00004 : Simulation of turbulent mixing of confined co-axial jets with disparate viscosity*
8:39 AM–8:52 AM
Presenter:
Vincent Lee
(Georgia Institute of Technology)
Authors:
Vincent Lee
(Georgia Institute of Technology)
Dennis E. Oztekin
(Georgia Institute of Technology)
Mustafa Usta
(Georgia Institute of Technology)
Devesh Ranjan
(Georgia Institute of Technology)
Cyrus K Aidun
(Georgia Institute of Technology)
Irfan Khan
(Dow Chemical Co)
Viscosity variations have shown to affect the mixing behavior and chemical yield in industrial processes. This study investigates the mixing of two miscible liquids of different viscosity in a co-axial jet mixer. The computational approach is based on large-eddy simulation (LES) using the opensource software OpenFOAM. The computational domain is decomposed with a structured grid and optimized for parallel performance. Theoretical turbulent flow profile is imposed at the inlet boundary. Three different LES sub-grid scale (SGS) models, namely the regular Smagorinsky (SM), dynamic (DM) and dynamic mixed (DMM) models have been compared. It appears that at moderate Reynolds number considered here, both DM and DMM results compare well with experiments at viscosity ratio of one. The time-averaged mixture fractions, velocity, and RMS values for mixing fluids with uniform viscosity are compared with literature and experimental data. The numerical results for viscosity ratios from 1 to 1000 will be discussed.
*We gratefully acknowledge support from The Dow Chemical Company under the University Project Initiative.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.A32.4
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