GU Wenting, ZHAO Zhenshan, ZHOU Hanwei, FENG Jian, TAN Zhaoguang, LI Dong. ZHANG Minghui, CHEN Zhenli, MAO Jun, WANG Gang, TAN Zhaoguang, WANG Long, ZHANG Binqian.ĭesign of Krueger flap for civil aircraft with blended-wing-body
Xi'an: School of Aeronautics, Northwestern Polytechnical University, 2012.(in Chinese) 焦子涵. Aerodynamic and stealth optimization design investigation on foil. Investigation on the effects of geometric parameters on airfoils' stealth characteristics. Frequency response scattering characteristic of aircraft. Convergence properties of radial basis function. Journal of Statistical Planning and Inference, 1990, 26: 131-148. Notes on Numerical Fluid Mechanics, 1999(65): 71-78. IEEE Antennas and Propagation Magazine, 1993, 35(1): 84-89. Benchmark radar targets for the validation of computational electromagnetics programs. Xi'an: School of Aeronautics, Northwestern Polytechnical University, 2005.(in Chinese) 王明亮. Aerodynamic and stealth optimization design for aircraft.
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Aerodynamic considerations of blended wing body aircraft. Key words: flying wing configuration, stealth airfoil, method of moment, integrated aerodynamic and stealth design, Pareto genetic algorithm, optimization design The Pareto front can provide multiple choices for 3D design. Some airfoil parameters show opposite effect on aerodynamic performance and stealth characteristics, and they should be chosen as the main design variables for integrated optimization. The upper surface of the outer wing affects transonic aerodynamic performance seriously, which should be designed carefully to improve aerodynamic efficiency, while more attention should be paid to the stealth performance in the lower surface. The results show that for a flying wing with both good aerodynamic and stealth performance,the pitching moment and radar cross section (RCS) in the key azimuth of the inner wing can be reduced by camber, leading-edge radius, trailing-edge angle and thickness design. An aerodynamic and stealth integrated airfoil optimization design investigation is carried out. Diverse optimal objectives and constraints are raised on the capability and features of the inner and outer wing. To deal with the diametrically different requirements between the aerodynamic and stealth design of a flying wing configuration, high fidelity methods are used to evaluate the aerodynamic performance and stealth characteristics of the foil, and a multi-objective optimization platform is established based on the Parsec method, radial basis function (RBF) neural network, Pareto genetic algorithm and the loose surrogate model management method.
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