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一种有效近似建模方法及船舶耐波性代理模型构建
引用本文:李冬琴,Philip A.WILSON,蒋志勇,赵欣.一种有效近似建模方法及船舶耐波性代理模型构建[J].船舶力学,2016,20(3):243-257.
作者姓名:李冬琴  Philip A.WILSON  蒋志勇  赵欣
作者单位:江苏科技大学 船舶与海洋工程学院,江苏镇江,212003;南安普顿大学 工程与环境学院,流体结构耦合研究组,英国南安普顿 SO17 1BJ
摘    要:船舶耐波性能预报计算过程复杂,会受到诸多设计变量的影响;且采用高精度商业软件如CFD预报船舶性能的计算代价非常高。文章采用拉丁超立方方法进行了设计空间抽样。定义了一个新的综合衡准指标来表达船舶耐波性能,即短期和长期作用下船舶非工作时间百分数。考虑了船舶耐波性能中的五个运动方向:横摇、纵摇、转艏、横荡和升沉。为提高船舶耐波性能计算效率,一种有效的近似建模方法—单参数Lagrangian 支持向量回归算法被用于训练并构建代理模型以预报船舶耐波性能,且该算法是由作者在过去的研究工作中首次提出。以海洋平台支援船(OSV)为例,采用SPL-SVR算法预报船舶耐波性能,并与基于NAPA计算仿真结果、人工神经网络和经典支持向量回归算法进行对比。该文考虑OSV的两种速度,建立了海洋平台支援船短期作用下非工作时间百分数的耐波性能响应面模型,结果显示采用SPL-SVR算法建立的船舶耐波性能响应面模型比较适合船型初步设计的工程实际应用,并具有较高的计算效率。

关 键 词:代理模型  支持向量机  实验设计  船舶耐波性

Establishment of Metamodels for Ship Seakeeping Performance Using an Effective Approximation Modeling Method
LI Dong-qin,Philip A WILSON,JIANG Zhi-yong,ZHAO Xin.Establishment of Metamodels for Ship Seakeeping Performance Using an Effective Approximation Modeling Method[J].Journal of Ship Mechanics,2016,20(3):243-257.
Authors:LI Dong-qin  Philip A WILSON  JIANG Zhi-yong  ZHAO Xin
Abstract:The prediction of seakeeping performance for ships is a complex calculation process because of the large number of possible ship configuration variables that will affect the seakeeping motion;high fidelity commercial software is used to forecast the ship performance such as Computational Fluid Dynamics (CFD) then there is a large overhead in both time and money to use such software. In this paper, the Latin Hypercube Design methodology is employed to explore the design space and to sample data to cover the design space. An index is introduced, namely the percentage of down-time which illustrates the short-term and long-term ship seakeeping motion, defined as the compre-hensive evaluation index for ship seakeeping performance, which is to be used in the comparison pro-cess of ship design. The five motions of ship seakeeping performance were considered as roll, pitch, yaw, sway and heave. To improve the efficiency of seakeeping calculation, an effective approxima-tion modeling method - the Single-parameter Lagrangian Support Vector Regression (SPL-SVR) was adopted and trained to establish the metamodels and predict the seakeeping performance and this algorithm was first proposed by authors in their past studies. For the Offshore Supply Vessel (OSV), the seakeeping criteria were predicted with the SPL-SVR and compared with the NAPA-based cal-culation results with the seakeeping manager, the Artificial Neural Network results and classical SVR results. Using two ship speeds for an Offshore Supply Vessel, the metamodels of ship seakeeping per-formance of short-term percentage of downtime were established;these metamodels were suitable for the practical application in ship preliminary design stage and all the numerical results show the ef-fectiveness of the new approximation algorithms.
Keywords:metamodel  Support Vector Machine  design of experiment  seakeeping
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