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Supervised by Ministry of Industry and Information Technology of The People's Republic of China Sponsored by Harbin Institute of Technology Editor-in-chief Yu Zhou ISSNISSN 1005-9113 CNCN 23-1378/T

Related citation:Lei Wang,Guanhua Liu,Zhiping Qiu.Review:Recent Developments in the Uncertainty-Based Aero-Structural Design Optimization for Aerospace Vehicles[J].Journal of Harbin Institute Of Technology(New Series),2018,25(3):1-15.DOI:10.11916/j.issn.1005-9113.17110.
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Review:Recent Developments in the Uncertainty-Based Aero-Structural Design Optimization for Aerospace Vehicles
Lei Wang, Guanhua Liu,Zhiping Qiu
(Institute of Solid Mechanics, School of Aeronautic Science and Engineering, Beihang University,Beijing 100083,China)
Abstract:
With the increasing demands of aircraft design, the traditional deterministic design can hardly meet the requirements of fine design optimization because uncertainties may exist throughout the whole lifecycle of the aircraft. To enhance the robustness and reliability of the aircraft design, Uncertainty Multidisciplinary Design Optimization (UMDO) has been developing for a long time. This paper presents a comprehensive review of UMDO methods for aerospace vehicles, including basic UMDO theory and research progress of its application in aerospace vehicle design. Firstly, the UMDO theory is preliminarily introduced, with giving the definition and classification of uncertainty as well as its sources corresponding to the aircraft design. Then following the UMDO solving process, the application in different coupled disciplines is separately discussed during the aircraft design process, specifically clarifying the UMDO methods for aero-structural optimization. Finally, the main challenges of UMDO and the future research trends are given.
关键词:  uncertainty-based multidisciplinary design optimization  UMDO procedure  uncertainty analysis  aero-structural optimization
DOI:10.11916/j.issn.1005-9113.17110
分类号:V214.1
Fund:
Descriptions in Chinese:
  

综述:飞行器不确定性气动/结构多学科优化设计进展

王磊,刘冠华,邱志平

(北京航空航天大学 航空科学与工程学院 固体力学研究所,北京 100083)

创新点说明:

目前对于贫信息条件下的不确定性飞行器多学科优化还主要依赖于非概率方法,结合贝叶斯推理和蒙特卡洛马尔科夫链的一种概率不确定性方法可以处理不确定性先验信息较少的情况,将其与飞行器多学科优化方法结合可以扩展不确定性飞行器多学科优化方法的适用情况。

研究目的:

研究不确定性飞行器多学科优化设计的最新进展,总结现有不确定性飞行器多学科优化方法面临的挑战和日后可能发展的研究方向。

研究方法:

首先结合飞行器设计领域的不确定性来源,对于不确定性基本概念进行了综述;然后重点阐述了气动弹性领域的不确定性优化设计的流程,按照可靠性气动弹性优化和鲁棒性气动弹性优化分别进行了探索,总结其目前存在的不足;然后研究领域拓展到气动、声、热、结构领域,分析不确定性优化方法在这些学科耦合领域的最新进展。在此基础上,总结了现存不确定性飞行器多学科优化方法面临的问题,指出了未来可能的发展方向。

结果:

通过对气动弹性领域概率优化方法和非概率优化方法(如区间方法、凸模型方法)的综述,得出了可以发展适用于不确定性先验信息较少的概率不确定性多学科优化方法的分析结果。

结论:

目前结合贝叶斯理论和蒙特卡洛马尔科夫链的不确定性分析方法可以处理贫信息条件下的可靠性量化,体现了适用于不确定性信息匮乏的概率不确定性多学科优化方法的发展潜力,可以以此为基础在未来进行更深入的研究和探索。

关键词:不确定性多学科优化设计;不确定性优化流程;不确定性分析;气动弹性优化设计

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