Evolutionary-Based Multidisciplinary Design Exploration for Silent Supersonic Technology Demonstrator Wing

Multidisciplinary design exploration with multiple objectives was performed for the wing shape of a silent supersonic technology demonstrator, considering aerodynamics, structures, and boom noise. Aerodynamic evaluation was carried out by solving Euler equations with computational fluid dynamics, an...

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Bibliographic Details
Published in:Journal of aircraft 2008-09, Vol.45 (5), p.1481-1494
Main Authors: Chiba, Kazuhisa, Makino, Yoshikazu, Takatoya, Takeshi
Format: Article
Language:English
Subjects:
Aerodynamics
Aerospace engineering
Eulers equations
Fluid dynamics
Genetic algorithms
SST
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Summary:Multidisciplinary design exploration with multiple objectives was performed for the wing shape of a silent supersonic technology demonstrator, considering aerodynamics, structures, and boom noise. Aerodynamic evaluation was carried out by solving Euler equations with computational fluid dynamics, and composite structural evaluation was performed by using Nastran for strength and vibration requirements with computational structural dynamics. The intensity of the sonic boom was evaluated by a modified linear theory. The optimization problem had five objective functions: minimization of the pressure and friction drags, boom intensity at the supersonic condition, and composite structural weight and maximization of the lift at the subsonic low-speed condition. The three-dimensional wing shape defined by 58 design variables was optimized with multi-objective particle swarm optimization and an adaptive-range multi-objective hybrid genetic algorithm method. In the structural evaluation, the combination optimization of stacking sequences of laminated composites was performed for inboard and outboard wings with strength and vibration requirements. Consequently, 75 nondominated solutions were efficiently obtained through 12 generations. Moreover, data mining was performed to obtain the design knowledge for deciding a compromise solution. The data mining revealed useful knowledge in the design space, such as the tradeoff information among the objective functions and the correlations between the objective functions and design variables. A compromise solution was successfully determined by using the obtained physical design knowledge. [PUBLICATION ABSTRACT]
ISSN:0021-8669
1533-3868
DOI:10.2514/1.33272