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TECHNICAL PAPERS

Velocity Field Reconstruction in the Mixing Region of Swirl Sprays Using General Regression Neural Network

[+] Author and Article Information
K. Ghorbanian, M. R. Soltani, M. R. Morad

Department of Aerospace Engineering, Sharif University of Technology, Tehran, Iran

M. Ashjaee

Department of Mechanical Engineering, University of Tehran, Tehran, Iran

J. Fluids Eng 127(1), 14-23 (Mar 22, 2005) (10 pages) doi:10.1115/1.1852472 History: Received December 17, 2002; Revised September 27, 2004; Online March 22, 2005
Copyright © 2005 by ASME
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References

Amir, M. A., Awais, M. M., Watkins, A. P., and Lockwood, F. C., 1999, “CFD and Neural Network Modeling of Dense Propane Spray,” Atomization Conference, ILASS-Europe’99, Toulouse, France, July 5–7.
Schulte, G., Guardani, R., and Oller do Nascimento, C. A., 1999, “Study of the Spray Structure of a Fan Atomizer by Means of a Neural Network-Based Mathematical Model,” Atomization Conference, ILASS-Europe’99, Toulouse, France, July 5–7.
Pruvost,  J., Legrand,  J., and Legentilhomme,  P., 2001, “Three-Dimensional Swirl Flow Velocity-Field Reconstruction Using a Neural Network With Radial Basis Function,” J. Fluids Eng., 123, pp. 920–927.
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Lee,  S. Y., and Tankin,  R. S., 1984, “Study of Liquid Spray (Water) in a Condensable Environment (Steam),” Int. J. Heat Mass Transfer, 27, No. 3, pp. 363–374.
Adzic,  M., Carvalho,  I. S., and Heitor,  M. V., 2001, “Visualization of the Disintegration of an Annular Liquid Sheet in a Coaxial Airblast Injector at Low Atomizing Air Velocities,” Opt. Diagnostics Eng.,5, No. 1, pp. 27–38.
Ruff,  G. A., Sagar,  A. D., and Faeth,  G. M., 1989, “Structure and Mixing Properties of Pressure-Atomized Sprays,” AIAA J., 27, No. 7, pp. 901–908.
Yule,  A. J., Sharief,  R. A., Jeong,  J. R., Nasr,  G. G., and James,  D. D., 2000, “The Performance Characteristics of Solid-Cone- Spray Pressure Swirl Atomizers,” Atomization Sprays, 10, pp. 627–646.
Dorfner,  V., Domnick,  J., Durst,  F., and Kohler,  R., 1996, “Viscosity and Surface Tension Effects in Pressure Swirl Atomization,” Atomization Sprays, 5, pp. 261–285.
Ghorbanian, K., Ashjaee, M., Soltani, M. R., Mesbahi, M. H., and Morad, M. R., 2003, “Experimental Flow Visualization of Single Swirl Spray Pattern at Various Pressure Drops,” AIAA-2003-4758, AIAA 39th Joint Propulsion Conference and Exhibit, Huntsville, Alabama, USA, 20–23 July.
Ghorbanian, K., Ashjaee, M., Soltani, M. R., Mesbahi, M. H., and Morad, M. R., 2003, “Experimental Study of the Spray of a Liquid-Liquid Coaxial Swirl Injector for Different Injection Pressures,” 9th International Conference on Liquid Atomization and Spray Systems, ICLASS 2003, Sorrento, Italy.
Ghorbanian, K., Ashjaee, M., Soltani, M. R., Mesbahi, M. H., and Morad, M. R., 2002, “PDA Droplet Size and Velocity Measurement of a Swirl Atomized Spray,” 9th Asian Congress of Fluid Mechanics, Isfahan, Iran.
Ashjaee, M., Soltani, M. R., Ghorbanian, K., and Morad, M. R., 2002, “PDA Study of Two Phase Flow in a Spray Field of a Jet-Swirl Type Injector,” 3rd Australian Conference on Laser Diagnostics in Fluid Mechanics and Combustion, Australia.
Ashjaee, M., Ghorbanian, K., Soltani, M. R., Mesbahi, M. H., and Morad, M. R., 2002, “PDA Measurements of Droplet Size and Velocity In Mixing Region of Two Sprays,” 9th Conference of Iranian Society of Mechanical Engineers, Tehran, Iran.
Soltani, M. R., Ghorbanian, K., Ashjaee, M., and Morad, M. R., 2003, “Neural Network Analysis of Single Swirl Spray Pattern at Various Pressure Drops,” AIAA-2003-4757, AIAA 39th Joint Propulsion Conference and Exhibit, Huntsville, Alabama, USA, 20–23 July.
Soltani, M. R., Ghorbanian, K., Ashjaee, M., Mesbahi, M. H., and Morad, M. R., 2003, “Prediction of Velocity Distribution in the Mixing Region of Swirl Sprays Using Neural Network Implementation,” AIAA-2003-4270, AIAA 33rd Fluid Dynamics Conference, Orlando, Florida, USA, 23–26 June.
Morad, M. R., 2005, “Determination of the Spray Characteristics of a Liquid–Liquid Coaxial Injector Utilizing PDA and Neural Network Analysis,” Sharif University of Technology, Tehran, Iran, January.

Figures

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Trajectory mode. Measurements are used for GRNN training.
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Planar mode. Measurements are used for evaluation of the GRNN predictions.
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Effect of σ on the velocity prediction at Z=26 mm: (a) Axial velocity; (b) Radial velocity
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Variation of σopt. for data lines at different Z
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Mean velocity error for the planar mode
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Geometrical setup and the corresponding parameters
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Measurement region for the side-by-side injector setup
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Axial velocity distribution for different injector spacing
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Radial velocity distribution for different injector spacing
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Axial velocity reconstruction
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Radial velocity reconstruction
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Mean prediction error over the domain for different injector spacing
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Mean prediction error for different number of training samples: (a) Axial velocity, di=18 mm; (b) Radial velocity, di=18 mm

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