基于PMA的船舶多学科协同可靠性分析  

Multidisciplinary collaborative reliability analysis of the conceptual design of ship based on PMA

作　　者：蔡厚平[1] 李明霞[1] 

机构地区：[1]南通航运职业技术学院,江苏南通226010

出　　处：《舰船科学技术》2015年第9期127-131,136,共6页Ship Science and Technology

摘　　要：针对现有的多学科可靠性分析方法只进行系统级优化,使系统级优化器的工作负担过重、求解效率低下的问题,提出一种基于性能策略法(Performance Measure Approach,PMA)的多学科遗传协同(Collaborative Optimization Based On Genetic Algorithm,GA-CO)可靠性分析方法(PMA-GA-CO)。该方法将PMA方法与多学科协同优化算法结合进行复杂系统工程可靠性分析。同时,采用遗传算法求解系统级可靠性优化问题,克服多学科协同优化算法中拉格朗日乘子不存在的缺陷。在PMA-GA-CO方法中所有的学科能够独立的进行优化,这样不仅解除了所有学科之间的耦合,提高了搜索最大可能点(Most Probable Point,MPP)的效率,而且学科级能进行优化,系统级优化器的负担可显著地降低。通过散货船概念设计多学科可靠性分析的工程例子证明了文中提出方法的效率和精度,这个优点在大规模的复杂工程系统的设计中能够更好地体现出来。To overcome the high computational cost of reliability analysis,This article introduces a method which combines the genetic algorithms-based collaborative optimization framework and the performance measure approach to assess the uncertainty encountered in the multidisciplinary design process.that is,PMA – GA – CO. genetic algorithms-based collaborative optimization（ GA – CO） is one of the improved forms of CO that overcomes the difficulty of convergence given the existing of highly nonlinear consistency constraints. PMA- GA- CO,which not only lifted the coupling between all disciplines to improve the search most probable point,the burden of system-level optimizer also can be significantly reduced. Examples of conceptual design of bulk carriers through multidisciplinary reliability analysis method proposed in this paper proves the efficiency and precision. What is more,this advantage in the design of large-scale complex engineering systems will be better reflected.

关 键 词：多学科协同优化算法 性能测量法 可靠性分析 遗传算法 船舶概念设计 

分 类 号：U661[交通运输工程—船舶及航道工程]