Multi-disciplinary Design Optimization of Air-Breathing Hypersonic Vehicle Using Pareto Games and Evolutionary Algorithms

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Abstract

The design integration of a supersonic combustion ramjet engine (SCRAMJET) with an airframe remains a critical task for guarantying a successful mission of trans atmospheric or hypersonic cruise vehicles. For this purpose, the operational efficiency has to be established by the effective specific impulse and the thrust to weight ratio of the accelerating vehicle. In order to analyze the foregoing problems, a design methodology based on Evolutionary Algorithms (EAs) and Game Strategies (GS) is developed. In this study, Evolutionary Algorithms (EAs) are used to solve MDO problems. The proposed methodology is tested and its performances and quality design evaluated for optimizing a 2-D air-breathing hypersonic vehicle shape at cruise flight conditions: Euler flow, Mach number = 8; angle of attack = 0°; flight altitude = 30 km, involving aerodynamics, thermodynamics and propulsion disciplines. The set up of an operational flight corridor requires a compromise among air-breathing engine performance, vehicle aerodynamic performance, and structural thermal load limit resulting from aero-heating. For this purpose, the operational efficiency is established by the effective specific impulse and thrust to weight ratio of the accelerating vehicle. In order to analyze the foregoing problems, a methodology is developed, which permits a quick performance evaluation of an idealized, integrated SCRAMJET vehicle for preliminary design analysis. A Pareto-EAs methodology is used to find design and off design solutions of an integrated vehicle consisting of the fore body inlet, the supersonic flow combustor and the after body expansion nozzle. From preliminary numerical experiments on a generic test case 2-D air breathing vehicle and analysis of results, the Pareto-EAs numerical approach is a promising methodology with game coalition for its use in industrial aeronautical design and well suited for its implementation on HPCs for increasing its efficiency.

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APA

Wu, P., Tang, Z., & Periaux, J. (2019). Multi-disciplinary Design Optimization of Air-Breathing Hypersonic Vehicle Using Pareto Games and Evolutionary Algorithms. In Computational Methods in Applied Sciences (Vol. 48, pp. 317–331). Springer Netherland. https://doi.org/10.1007/978-3-319-89988-6_19

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