Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method

Weight reduction has attracted much attention among ship designers and ship owners. In the present work, based on an improved bi-directional evolutionary structural optimization (BESO) method and surrogate model method, we propose a hybrid optimization method for the structural design optimization of beam-plate structures, which covers three optimization levels: dimension optimization, topology optimization and section optimization. The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints. The kernel optimization procedure (KOP) uses BESO to obtain the optimal topology from a ground structure. To deal with beam-plate structures, the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure. In the first optimization level, a series of ground structures are generated based on different dimensional parameter combinations, the KOP is performed to all the ground structures, the response surface model of optimal objective values and dimension parameters is created, and then the optimal dimension parameters can be obtained. In the second optimization level, the optimal topology is obtained by using the KOP according to the optimal dimension parameters. In the third optimization level, response surface method (RSM) is used to determine the section parameters. The proposed method is applied to a hatch cover structure design. The locations and shapes of all the structural members are determined from an oversized ground structure. The results show that the proposed method leads to a greater weight saving, compared with the original design and genetic algorithm (GA) based optimization results.     

基于RANS法的船舶阻力及自由运动预报

文章介绍了基于RANS法求解船舶自由运动水动力性能的方法。通过对流域设计、网格划分方法、运动求解法及湍流模型的选择等进行完整的讨论与分析,提出了一套求解船舶自由运动的RANS方法。以低速船(KCS型船模)及高速船(Fridsma滑行艇)为计算对象,计算结果验证了RANS法在预报船舶自由航行时水动力性能的实用性。     

基于支持向量机的高速滑行艇航态优化

引入支持向量机(SVM)分类算法研究滑行艇纵向稳定滑行与纵向运动失稳之间的分界线,验证重叠网格法与Realizable k-ε湍流模型在计算滑行艇阻力及自由升沉纵倾时的准确性,使用该方法对一组以体积弗劳德数Fr_?及重心纵向位置l_(cg)为设计变量的样本点进行数值计算,并使用SVM法对计算结果进行分类,提出基于"偏离度约束"的SVM,使用该改进算法拟合分界线,使用修正后的分界线对重心进行优化,减阻效果可达5.15%,同时可求得在原设计方案的重心下,航速提升至Fr_?=7.16。