Multidisciplinary Design Optimization Processes for Efficiency Improvement of Aircraft: State-of-the-Art Review

被引：0

作者：

Leng, Jun-xue ^{[1
]}

Wang, Zhen-guo ^{[1
]}

Huang, Wei ^{[1
]}

Shen, Yang ^{[1
]}

An, Kai ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Aerosp Sci & Engn, Changsha 410073, Hunan, Peoples R China

来源：

INTERNATIONAL JOURNAL OF AERONAUTICAL AND SPACE SCIENCES | 2024年

基金：

国家重点研发计划;

关键词：

Multidisciplinary design optimization; Data dimensionality reduction; Machine learning; MDO strategy; Optimization algorithms; Data mining; AERODYNAMIC OPTIMIZATION; DIMENSIONALITY REDUCTION; GLOBAL OPTIMIZATION; MODEL; PERFORMANCE; CONCURRENT; ALGORITHM; DYNAMICS; JET;

D O I：

10.1007/s42405-024-00811-8

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

During actual flight processes, aircraft face various complex operating conditions and must consider the requirements of different disciplines to achieve good overall performance. Multidisciplinary design optimization (MDO) for aircraft is a complex and time-consuming task, making efficiency crucial in aircraft design. This paper starts from the conventional MDO process, covering five aspects including design variables, performance evaluation methods, MDO strategies, optimization algorithms, and knowledge extraction for enhancing MDO efficiency. It introduces multiple techniques and current research status aimed at improving MDO efficiency, and, combined with artificial intelligence, outlines future directions for MDO development. This paper aims to help MDO researchers clarify their thoughts and provide references for advancing current MDO methods.

引用

页数：23

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