Evolutionary multi-objective multi-architecture design space exploration methodology

被引:11
作者
Frank, Christopher P. [1 ]
Marlier, Renaud A. [2 ]
Pinon-Fischer, Olivia J. [2 ]
Mavris, Dimitri N. [2 ]
机构
[1] Georgia Inst Technol, Sch Aerosp Engn, 270 Ferst Dr NW, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Ferst Dr NW, Atlanta, GA 30332 USA
关键词
Multi-objective optimization; Design space exploration; Evolutionary algorithm; Pareto frontier; Suborbital vehicles; SYSTEMS;
D O I
10.1007/s11081-018-9373-x
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The design of revolutionary aerospace vehicles is characterized by large design spaces, a lack of established baselines, and some uncertainty in the design and regulatory requirements that such vehicles will need to meet. A new evolutionary multi-architecture multi-objective optimization algorithm is presented to support design concept selection when faced with such challenges. The proposed approach allows designers to efficiently and exhaustively generate variable-oriented architectures that can be further optimized and compared. It provides a dynamic decision-making environment able to identify trends and trade-offs, and prioritize designs. The application of the proposed methodology to suborbital vehicles highlights key promising technological enablers, which can be leveraged to design high-performance and robust concepts.
引用
收藏
页码:359 / 381
页数:23
相关论文
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