Commenced in January 2007
Paper Count: 30184
A Numerical Framework to Investigate Intake Aerodynamics Behavior in Icing Conditions
Abstract:One of the major parts of a jet engine is air intake, which provides proper and required amount of air for the engine to operate. There are several aerodynamic parameters which should be considered in design, such as distortion, pressure recovery, etc. In this research, the effects of lip ice accretion on pitot intake performance are investigated. For ice accretion phenomenon, two supervised multilayer neural networks (ANN) are designed, one for ice shape prediction and another one for ice roughness estimation based on experimental data. The Fourier coefficients of transformed ice shape and parameters include velocity, liquid water content (LWC), median volumetric diameter (MVD), spray time and temperature are used in neural network training. Then, the subsonic intake flow field is simulated numerically using 2D Navier-Stokes equations and Finite Volume approach with Hybrid mesh includes structured and unstructured meshes. The results are obtained in different angles of attack and the variations of intake aerodynamic parameters due to icing phenomenon are discussed. The results show noticeable effects of ice accretion phenomenon on intake behavior.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084598Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1875
 W.B. Wright, "User manual for the NASA Glenn ice accretion code LEWICE version 2.0," NASA CR-1999-209409, 1999.
 E. Ogretim, W. Huebsch, and A. Shinn, "Aircraft ice accretion prediction based on neural networks," Journal of Aircraft, Vol. 43, No.1, pp. 233-240, 2006.
 M. Taeibi-Rahni, M.R Soltani, and A. Taheri, An introduction to intake aerodynamics, Iranian aerospace research center publication, ministry of science, research and technology, Tehran, First edition, 2004.
 E.L. Goldsmith, J. Seddon, Practical intake aerodynamic design, Oxford: Blackwell Scientific Publications, 1993.
 B.L. Messinger, "Equilibrium temperature of an unheated icing surface as a function of airspeed," Journal of the Aeronautical Sciences, Vol.20, No.1, pp. 29-42, 1953.
 I. Paraschivoiu, S. Gouttebroze, and F. Saeed, "CANICEÔÇöCapabilities and current status," NATO/RTO Workshop, Assessment of icing code prediction capabilities, at CIRA in Capua, Italy, Dec. 6-7, 2000.
 D.N. Anderson, D.B. Hentschel, and G.A. Ruff, "Measurment and correlation of ice accretion roughness," NASACR-2003-211823 and AIAA-98-0486, June 2003.
 D.N. Anderson, and J. Shin, "Characterization of ice roughness from simulated icing encounters," NASA TM-107400AIAA-97-0052, 1997.
 J. Chung, Y. Choo, A. Reehorst, M. Potapczuk, and J. Slater, "Navier stokes analysis of the flowfield characteristics of an ice contaminated aircraft wing," AIAA Paper 99-0375, 1999.
 M.B. Bragg, "Experimental aerodynamic characteristics of an NACA 0012 airfoil with simulated glaze ice," AIAA Journal of Aircraft, Vol. 25, No. 9, pp. 849-854,1988.
 S.C. Caruso, "NEARICE: An unstructured mesh Navier-Stokes based ice accretion prediction method," AIAA Paper 94-0606, Jan. 1994.
 M. Vickerman, Y. Choo, D. Braun, M. Baez, and S. Gnepp, "SmaggIce: surface modeling and grid generation for iced airfoils -phase 1 results," AIAA Paper 2000-0235, 2000.
 M.B. Menhaj, Computational intelligence: Fundamental of neural networks, Tehran: Amirkabir university of technology publication, Second Edition, 2005.