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Numerical Visualizations of Mixing Enhancement in a 2D Supersonic Ejector

by M. D,ani1, V. Lepiller2, A. Ghezal3, P. Desevaux4

LMFTA, USTHB, Algiers, Algeria.
FEMTO-ST-UMR 6174, Energy Dept, University of Bourgogne Franche-Comté, Belfort F-90000, France.
LMFTA, USTHB, Algiers, Algeria.
FEMTO-ST-UMR 6174, Energy Dept, University of Bourgogne Franche-Comté, Belfort F-90000, France.

* Corresponding author: M. Dandani. Email: email.

Fluid Dynamics & Materials Processing 2018, 14(1), 23-37. https://doi.org/10.3970/fdmp.2018.014.023

Abstract

The present study deals with the numerical visualization of the mixing process in a 2D supersonic ejector. The mixing process is visualized using two CFD flow visualization methods. The first method consists in introducing discrete particles in the secondary flow and computing their trajectories. The second method consists in modeling the diffusion of a passive scalar introduced in one of the two flows. The mixing process is investigated in the case of a conventional 2D supersonic ejector and a second case of an ejector equipped with transverse micro jets. Flow visualizations obtained show the existence of a significant mixing enhancement when the ejector mixing chamber is equipped with wall slot injectors.

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Cite This Article

APA Style
Dandani, M., Lepiller, V., Ghezal, A., Desevaux, P. (2018). Numerical visualizations of mixing enhancement in a 2D supersonic ejector. Fluid Dynamics & Materials Processing, 14(1), 23-37. https://doi.org/10.3970/fdmp.2018.014.023
Vancouver Style
Dandani M, Lepiller V, Ghezal A, Desevaux P. Numerical visualizations of mixing enhancement in a 2D supersonic ejector. Fluid Dyn Mater Proc. 2018;14(1):23-37 https://doi.org/10.3970/fdmp.2018.014.023
IEEE Style
M. Dandani, V. Lepiller, A. Ghezal, and P. Desevaux, “Numerical Visualizations of Mixing Enhancement in a 2D Supersonic Ejector,” Fluid Dyn. Mater. Proc., vol. 14, no. 1, pp. 23-37, 2018. https://doi.org/10.3970/fdmp.2018.014.023



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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