张干锋,王德禹.基于分区间泛化Kriging近似模型的船舶局部结构形状优化[J].海洋工程,2018,36(6):46~57
基于分区间泛化Kriging近似模型的船舶局部结构形状优化
Shape optimization of ships′ local structure with the partition and generalization Kriging approximation model
  
DOI:10.16483/j.issn.1005-9865.2018.06.006
中文关键词:  分区间泛化  Kriging近似模型  形状优化  分阶段优化  船舶结构  多岛遗传算法
英文关键词:partition and generalization  Kriging approximation  shape optimization  phased optimization  ship structure  multi island genetic algorithm
基金项目:工信部高技术船舶科研项目([2016]548);教育部财政部重大专项船舶数字化智能设计系统(201335)
作者单位E-mail
张干锋 上海交通大学 海洋工程国家重点实验室上海 200240
高新船舶与深海开发装备协同创新中心上海 200240 
290899701@qq.com 
王德禹 上海交通大学 海洋工程国家重点实验室上海 200240
高新船舶与深海开发装备协同创新中心上海 200240 
dywang@sjtu.edu.cn 
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中文摘要:
      为提高Kriging近似模型在船舶结构性能多维度响应预测方面的适用性,对常规Kriging近似模型进行分区间泛化改进:一是对设计样本点的各个维度(分量)进行划区,并在每一个分区间内采用最优拉丁超立方(OLhd)取样;二是引入比例系数w1组合高斯与指数型相关函数提高模型对数据的泛化能力,从而在每个划分的区间内建立泛化的Kriging近似模型。通过SCH测试函数,验证了构造的分区间泛化Kriging模型有效性。结合参数化建模和改进Kriging近似模型对某过渡肘板和舱口角隅边界进行形状优化,优化第一阶段由改进的近似模型通过多岛遗传算法得到全局初步的最优解,第二阶段在初步解的基础上缩小优化变量范围,由少量的FEM计算即可在小范围内搜寻到精确的最优设计变量。结果表明:分区间泛化Kriging近似模型在预测多维度响应时较常规Kriging模型预测精度更高;分阶段的形状优化流程在保证极小误差和缩小计算成本的情况下能够得到理想的应力分布和重量优化结果,有助于船舶结构的轻量化研究。
英文摘要:
      Some improvements with regard to partition and generalization have been proposed for Kriging approximation model. The change makes the Kriging approximation model more suitable for the prediction of multi dimensional responses in ship structure engineering. One of the improvements about partition is to divide each dimension of sampling point’s data in the design space into two or four equal parts. The Optimal Latin Hypercube Design sampling is applied in each partition. Then different Kriging approximation models are established among different partitions. The other improvement is combining Gauss and exponential correlation function by introducing of proportional coefficient w1, which increases the type of correlation function and thereby improves the generalization performance of approximation model. The coefficient w1 is defined as the maximum likelihood estimator, which is similar to the definition of parameter in the correlation function. According to the improvement measures, the partition and generalization Kriging approximation model (PGKAM) is established in each interval. With testing the Schaffer function N.1, the partition and generalization Kriging approximation modeling has been proved effective. By integrating with parametric modeling and PGKAM, certain optimization of problems of bracket and hatch corner’s boundary shape is carried out. In the process of shape optimization, firstly, the global initial optimal solution is obtained from the improved approximate model with the Multi Island Genetic Algorithm. Then the scope of the optimization variables is trimmed based on the initial solution. With costing few FEM calculations, the exact optimal design variables are able to be found efficiently in a small scale. The results illustrate that the partition and generalization Kriging approximation model has higher prediction accuracy than the conventional Kriging model in the prediction of multi dimensional responses. Phased shape optimization methodology ensures the ideal stress distribution and weight optimization results to be capable of obtaining when error is minimum and the calculation burden is lessened, which is helpful to the lightweight analysis of ship structure.
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