流体仿真软件在船舶与海洋结构物概念设计阶段应用广泛。针对潜器外形设计过程中，仿真分析往往需要耗费大量的时间成本，无法直接与优化器结合的问题，本文研究基于支持向量回归机（Support Vector Regression，SVR）的潜器外形优化方法，包括拉丁超立方试验设计选取样本点、基于ICEM的潜器参数化建模和网格自动划分、基于Fluent的阻力计算及SVR模型的构造。采用改进的粒子群算法求解潜器外形优化设计问题，得到了阻力性能优良的潜器外形。
CFD simulation software greatly improves the efficiency and accuracy of optimization design of submersible shape. However, during the optimization, optimization results usually requires a lot of iterations to be achieved. Fluid simulation software, such as fluent will take enormous time and cost during the optimization process. Therefore, this paper proposes a Support Vector Regression (SVR) to study the optimization of submersible shape. The process of building matamodel include:Latin Hypercube experimental design selected sample points, automatic division based ICEM submersible parametric modeling and grid-based computing. Particle Swarm Optimization (PSO) algorithm is adopted to obtain the optimum with a minimum resistance.
2016,38(12): 127-130 收稿日期：2016-07-17
DOI：10.3404/j.issn.1672-7619.2016.12.025
分类号：U661
基金项目：国家自然科学基金资助项目（11202078）
作者简介：谢云飞(1981-),男,硕士,讲师,研究方向为船舶与海洋工程结构物设计制造。
参考文献：
[1] 李冬琴, WILSON P A, 蒋志勇. 船舶操纵性能及其代理模型构建(英文)[J]. 船舶力学, 2015, 19(12):1463-1474.
[2] 孙丽娜, 詹成胜, 冯佰威, 等. 三体船侧体布局及型线优化设计研究[J]. 船舶工程, 2015, 37(5):7-10, 26.
[3] 孙丽娜, 詹成胜, 冯佰威, 等. 三体船侧体布局及型线优化设计研究[J]. 船舶工程, 2015, 37(5):7-10, 26.
[4] 常海超, 冯佰威, 刘祖源, 等. 船型优化中样本点选取方法对近似模型精度的影响研究[J]. 中国造船, 2013, 54(4):84-93.
[5] 程妍雪, 庞永杰, 杨卓懿, 等. 基于径向基神经网络模型的耐压壳6σ设计[J]. 上海交通大学学报, 2014, 48(4):493-497.
[6] AWAD M, KHANNA R. Support vector regression[M]//AWAD M, KHANNA R. Efficient learning machines:Theories, concepts, and applications for engineers and system designers. New York:Apress, 2015:67-80.
[7] KAZEM A, SHARIFI E, HUSSAIN F K, et al. Support vector regression with chaos-based firefly algorithm for stock market price forecasting[J]. Applied Soft Computing, 2013, 13(2):947-958.
[8] WEI Z, TAO T, DING Z S, et al. A dynamic particle filter-support vector regression method for reliability prediction[J]. Reliability Engineering & System Safety, 2013, 119:109-116.
[9] DONG H C, SONG B W, WANG P, et al. A kind of balance between exploitation and exploration on kriging for global optimization of expensive functions[J]. Journal of Mechanical Science and Technology, 2015, 29(5):2121-2133.
[10] DONG H C, SONG B W, DONG Z M, et al. Multi-start Space Reduction (MSSR) surrogate-based global optimization method[J]. Structural and Multidisciplinary Optimization, 2016, 54(4):907-926.
[11] 蔡厚平, 李明霞. 基于改进粒子群算法的大开口甲板板架轻量化设计[J]. 舰船科学技术, 2015, 37(5):109-113.
