Investigation on Effective Sampling Strategy for Multi-objective Design Optimization of RBCC Propulsion Systems via Surrogate-assisted Evolutionary Algorithms

Tuan Quang Ho, Hideaki Ogawa, Cees Bil

研究成果: ジャーナルへの寄稿学術誌査読

1 被引用数 (Scopus)

抄録

Rocket-based combined cycle (RBCC) engines are an airbreathing propulsion technology that offers considerable potential for efficient access-to-space. Successful design of RBCC-powered space transport systems requires reliable databases for both vehicle and engine performance, calling for an effective sampling method to accurately resolve non-linear characteristics in vast design space. This paper presents an optimal sampling strategy based on the function gradients to realize efficient database construction based on evolutionary algorithms and assesses its effectiveness by applying the methodology to various test functions with multiple objectives as well as surrogate models representing scramjet intake characteristics for validation.

本文言語英語
ページ(範囲)1252-1262
ページ数11
ジャーナルProcedia Engineering
99
DOI
出版ステータス出版済み - 2015
外部発表はい
イベントAsia-Pacific International Symposium on Aerospace Technology, APISAT 2014 - Shanghai, 中国
継続期間: 9月 24 20149月 26 2014

!!!All Science Journal Classification (ASJC) codes

  • 工学一般

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