程耿东

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:丹麦技术大学

学位:博士

所在单位:力学与航空航天学院

电子邮箱:chenggd@dlut.edu.cn

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A sequential approximate programming strategy for reliability-based structural optimization

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论文类型:期刊论文

发表时间:2006-08-01

发表刊物:COMPUTERS & STRUCTURES

收录刊物:SCIE、EI、Scopus

卷号:84

期号:21

页面范围:1353-1367

ISSN号:0045-7949

关键字:reliability-based structural optimization; sequential approximate programming; approximate reliability index; accurate reliability index; concurrent convergence; computational efficiency

摘要:Although reliability-based structural optimization (RBSO) is recognized as it rational structural design philosophy that is more advantageous to deterministic optimization, most common RBSO is based on straight-forward two-level approach connecting algorithms of reliability calculation and that of design optimization. This is achieved usually with an outer loop for optimization of design variables and an inner loop for reliability analysis. A number of algorithms have been proposed to reduce the computational cost of such optimizations, such as performance measure approach, semi-infinite programming. and mono-level approach. Herein the sequential approximate programming approach, which is well known in structural optimization, is extended as an efficient methodology to solve RBSO problems. In this approach, the optimum design is obtained by solving a sequence of sub-programming problems that usually consist of an approximate objective function subjected to a set of approximate constraint functions. In each sub-programming. rather than direct Taylor expansion of reliability constraints. a new formulation is introduced for approximate reliability constraints at the current design point and its linearization. The approximate reliability index and its sensitivity are obtained from a recurrence formula based oil the optimality conditions for the most probable failure point (MPP). It is shown that the approximate NIPP. a key component of RBSO problems. is concurrently improved during each sub-programming solution step. Through analytical models and comparative Studies over complex examples, it is illustrated that our approach is efficient and that a linearized reliability index is a good approximation of the accurate reliability index. These unique features and the concurrent convergence of design optimization and reliability calculation are demonstrated with several numerical examples. (c) 2006 Elsevier Ltd. All rights reserved.