Gradient-based multidisciplinary design optimization of an autonomous underwater vehicle

被引:16
作者
Chen, Xu [1 ]
Wang, Peng [1 ]
Zhang, Daiyu [2 ]
Dong, Huachao [1 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian, Shaanxi, Peoples R China
[2] Jiangsu Univ Sci & Technol, Sch Naval Architecture & Ocean Engn, Zhenjiang 212003, Peoples R China
基金
中国国家自然科学基金;
关键词
Autonomous underwater vehicle; Multidisciplinary feasible; Gradient calculation; Analytic methods; SYSTEM;
D O I
10.1016/j.apor.2018.08.006
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
In this paper, multidisciplinary design optimization (MDO) is introduced for the conceptual design of an autonomous underwater vehicle (AUV). The purpose is to minimize the energy consumption with predefined sailing distance. AUV is decomposed into three disciplines and the coupling relationship is analyzed to build the optimization model. Since drag plays a major role in energy consumption, a hydrodynamic analysis framework is established for drag calculation, consisting of parametric modeling, mesh auto-generation and numerical simulation. In order to complete the optimization effectively, multidisciplinary feasible (MDF) architecture is used and gradient-based optimization algorithm is adopted. Moreover, analytic methods are incorporated into the MDF architecture via gradient to further improve the efficiency of gradient calculation. The optimization result shows that the optimized AUV is much more energy-saving than the initial design and the MDF architecture via coupled analytic methods is quite efficient.
引用
收藏
页码:101 / 111
页数:11
相关论文
共 43 条
[1]  
[Anonymous], 2016, STRUCT MULTIDISCIP O
[2]  
[Anonymous], 2015, SCIPY OPEN SOURCE SC
[3]  
[Anonymous], 2012, INNOVATION POWER CON
[4]  
[Anonymous], 2012, METAHEURISTICS OPTIM
[5]  
[Anonymous], 1996, DOCTORAL DISSERTATIO
[6]  
Belegundu A., 2013, S MULT AN OPT
[7]  
Bloebaum C.L., 1992, Engineering Optimization, V19, P171
[8]   Penalty function approaches for ship multidisciplinary design optimisation (MDO) [J].
Campana, Emilio Fortunato ;
Fasano, Giovanni ;
Peri, Daniele .
EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING, 2012, 6 (06) :765-784
[9]   An asymmetric suboptimization approach to aerostructural optimization [J].
Chittick, Ian R. ;
Martins, Joaquim R. R. A. .
OPTIMIZATION AND ENGINEERING, 2009, 10 (01) :133-152
[10]  
Cramer E. J., 1994, SIAM J OPTIMIZ, V4, P754, DOI DOI 10.1137/0804044