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Research Papers: Multiphase Flows

Identification of Pulsation Mechanism in a Transonic Three-Stream Airblast Injector

[+] Author and Article Information
Wayne Strasser

Fellow ASME
Eastman Chemical Company,
Kingsport, TN 37660
e-mail: strasser@eastman.com

Francine Battaglia

Fellow ASME
Department of Mechanical Engineering,
Virginia Polytechnic Institute
and State University,
Blacksburg, VA 24061
e-mail: fbattaglia@vt.edu

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received August 6, 2015; final manuscript received April 5, 2016; published online July 15, 2016. Assoc. Editor: Samuel Paolucci.

J. Fluids Eng 138(11), 111303 (Jul 15, 2016) (15 pages) Paper No: FE-15-1540; doi: 10.1115/1.4033422 History: Received August 06, 2015; Revised April 05, 2016

Acoustics and ligament formation within a self-generating and self-sustaining pulsating three-stream injector are analyzed and discussed due to the importance of breakup and atomization of jets for agricultural, chemical, and energy-production industries. An extensive parametric study was carried out to evaluate the effects of simulation numerics and boundary conditions using various comparative metrics. Numerical considerations and boundary conditions made quite significant differences in some parameters, which stress the importance of using documented and consistent numerical discretization recipes when comparing various flow conditions and geometries. Validation exercises confirmed that correct droplet sizes could be produced computationally, the Sauter mean diameter (SMD) of droplets/ligaments could be quantified, and the trajectory of a droplet intersecting a shock wave could be accurately tracked. Swirl had a minor impact by slightly moving the ligaments away from the nozzle outlet and changing the spray to a hollow cone shape. Often, metrics were synchronized for a given simulation, indicating that a common driving mechanism was responsible for all the global instabilities, namely, liquid bridging and fountain production with shockletlike structures. Interestingly, both computational fluid dynamics (CFD) and the experimental non-Newtonian primary droplet size results, when normalized by distance from the injector, showed an inversely proportional relationship with injector distance. Another important outcome was the ability to apply the models developed to other nozzle geometries, liquid properties, and flow conditions or to other industrial applications.

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References

Figures

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Fig. 1

Geometry and mesh for three-stream injector

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Fig. 2

Time-averaged spray profiles from axisymmetric air–water simulations

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Fig. 3

Sample instantaneous volume fraction contours CICSAM Case A10; blue represents water, while red represents gas

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Fig. 4

Injector silver model for testing shape length scale quantification

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Fig. 5

CFD results compared to experimental results of non-Newtonian primary atomization from Aliseda et al. [66]

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Fig. 6

Vector plot colored by Mach number of a normal shock wave in air just having passed over a single droplet of water

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Fig. 7

Dimensionless lateral trajectory of a droplet having been exposed to a shock wave

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Fig. 8

Sample instantaneous contours from nonswirl (left, case A19) and swirl (right, case A7) flows showing the swirl opening of the spray from axisymmetric air–water simulations

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Fig. 9

Typical time sequence using volume fraction contours from axisymmetric air–water simulations (case A5), starting from top-left and proceeding to bottom-right. The number near the top of each frame represents the approximate time (t/H) that frame captures in a given cycle, starting with 0 for the upper left-hand frame.

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Fig. 10

Instantaneous contours at t/H = 0.3 of volume fraction, pressure front, and Mach number from axisymmetric air–water simulations (case A5). The cycle time is just before the bridge forms. The left image is volume fraction (blue = liquid and red = gas), the middle shows the resulting pressure front (purposely undisclosed, red = high and blue = low), and the right image provides Mach number contours (blue = 0, while red designates ≥ 1).

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Fig. 11

Mach number contours at time samples from three uncorrelated cycles from axisymmetric air–water simulations (case A5). The cycle time is close to t/H = 0.3 just before the bridge forms upstream of the nozzle outer face. The dotted line shows a very slight cycle time progression from left to right.

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Fig. 12

Instantaneous contours showing Mach number (left) scaled from blue = 0.0 to red ≥ 1.0 and the ratio of negative dilatation to vorticity magnitude (right, same time sample) scaled from blue = 0.0 to red = 1.0 at the same time instant from axisymmetric air–water simulations (case A5)

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Fig. 13

Swirl-inducing mechanism examples; lower figure is colored by undisclosed pressure from low (blue) to red (high)

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