精密及缺陷信息条件下的结构可靠性设计

STRUCTURAL RELIABILITY DESIGN UNDER INCOMPLETE INFORMATION

概率方法一直以来被认为是处理不确定现象的最有效的方法.传统的概率可靠性模型建立在随机变量的分布函数基础上,需要较完整的数据信息.在结构设计问题中,有关载荷、抗力等影响因素的统计数据一般是稀少的或缺乏的,信息往往以非完整的形式出现.此外,结构的安全设计还需考虑结构和环境的相互作用,结构设计、分析、评价以及制作过程中可能存在的误差等,有些不确定因素不能归于随机性.因此,需要发展新的结构可靠性设计模型和方法,以克服传统的概率可靠性方法的局限和不足.本文对精密及缺陷信息条件下的可靠性设计模型和方法进行综述,内容包括随机可靠性设计模型与方法、非完整信息下的可靠性分析和设计、模型误差和主观不确定的影响、复杂系统优化求解镱略、以及今后的研究展望.

Conventional reliability analysis is based on the probabilistic distribution of random variables. In structural design problems, however, statistical data regarding load or resistance are usually incomplete. In addition, a robust structural design must consider the interaction of the structures with the environment, errors in the stage of the structure design, the structure analysis, the evaluation, and the fabrication, some of which may not be categorized as to randomness. Therefore, a new theoretical framework for the structural reliability and the optimal design which incorporates the different uncertainty sources becomes necessary to achieve a suitable practical solution different from the traditional probabilistic method. This paper provides an overview on structural reliability and optimal design under circumstances of incomplete information. Several topics such as probability-based design, possibility theory for dealing with incomplete information, the influence of model errors and subjective uncertainties, and applications of evolutionary algorithms to reliability design are discussed. The paper concludes with a brief perspective for further research.