点击次数：

论文类型：期刊论文

发表时间：2018-08-01

发表刊物：JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN

收录刊物：SCIE

卷号：26

期号：4

页面范围：562-574

ISSN号：1023-2796

关键字：Ship chamber; Ship lift; Structure optimization; Multilevel optimization; Beam-plate structure; BESO; RSM

摘要：Weight reduction of ship chamber is a main concern of ship lift design for improving the load capacity. The structure of ship chamber is typical of beam-plate structure. To deal with structural optimization problem of beam-plate structure, a multilevel structural optimization method was developed based on combining an improved bi-directional evolutionary structural optimization (BESO) method and surrogate model method, which covers three optimization levels, as dimension optimization, topology optimization and section optimization. The aim of the proposed optimization method is to determine global design parameters, integral structural topology, and locations and sectional parameters of structural members from an oversized ground structure. The kernel optimization procedure (KOP) is using BESO to obtain the optimal topology from a ground structure. In order to deal with beam-plate structures, cubic box is adopted as the unit cell to construct ground structure for BESO. In the first optimization level, based on different dimensional parameter combinations, a series of ground structures are generated and used to perform KOP. Response surface (RS) model is used to simulate the nonlinear relationship between the optimal objective values and dimension parameters, then the optimal dimensional parameters can be obtained. In the second optimization level, the optimal dimension parameters are used to generate the ground structure, and the optimal topology could be obtained by using KOP. In the third optimization level, RS model is also used to determine the section parameters. The proposed method is applied to structural design of ship chamber of a 500-ton class ship lift. The results show that the pro-posed method leads to a greater weight saving, compared with the original design and generic algorithm (GA)-based optimization results.