Parametric Geometric Model and Hydrodynamic Shape Optimization of A Flying-Wing Structure Underwater Glider

• Published in: China ocean engineering Vol. 31; no. 6; pp. 709 - 715
• Main Authors: Wang, Zhen-yu, Yu, Jian-cheng, Zhang, Ai-qun, Wang, Ya-xing, Zhao, Wen-tao
• Format: Journal Article
• Language: English
• Published: Nanjing Chinese Ocean Engineering Society 01.12.2017; Springer Nature B.V; State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016,China; University of Chinese Academy of Sciences, Beijing 100049, China%State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016,China
• Subjects: Algorithms; Coastal Sciences; Computation; Computational fluid dynamics; Design; Design of experiments; Design optimization; Dynamics; Engineering; Finite element method; Flight; Fluid dynamics; Fluid- and Aerodynamics; Hydrodynamics; Kernel functions; Marine & Freshwater Sciences; Mathematical models; Mesh generation; Modelling; Numerical analysis; Numerical and Computational Physics; Numerical methods; Oceanography; Offshore Engineering; Particle swarm optimization; Shape optimization; Simulation; Underwater; Underwater construction; Underwater exploration; Underwater gliders; Underwater structures; surrogate model; blended-wing-body; design optimization; underwater glider
• ISSN: 0890-5487; 2191-8945
• DOI: 10.1007/s13344-017-0081-7

Combining high precision numerical analysis methods with optimization algorithms to make a systematic exploration of a design space has become an important topic in the modern design methods. During the design process of an underwater glider＇s flying-wing structure, a surrogate model is introduced to decrease the computation time for a high precision analysis. By these means, the contradiction between precision and efficiency is solved effectively. Based on the parametric geometry modeling, mesh generation and computational fluid dynamics analysis, a surrogate model is constructed by adopting the design of experiment （DOE） theory to solve the multi-objects design optimization problem of the underwater glider. The procedure of a surrogate model construction is presented, and the Gaussian kernel function is specifically discussed. The Particle Swarm Optimization （PSO） algorithm is applied to hydrodynamic design optimization. The hydrodynamic performance of the optimized flying-wing structure underwater glider increases by 9.1%.