摘要
针对同时包含概率变量和证据变量的混合不确定性问题,提出了一种高效的结构可靠性分析方法,在保证精度的前提下大幅提高了计算效率。借助证据变量均匀化手段,将传统概率可靠性分析中的最可能失效点(MPP)概念引入概率-证据混合模型,基于MPP建立线性近似功能函数,并进行高效可靠性分析。最后通过三个工程算例验证了该方法的有效性。
An efficient reliability analysis method for structure has been proposed, whose inputs consist of both probable variables and evidence variables. The method greatly reduces the computation cost of relia- bility analysis with mixture of aleatory and epistemic uncertainty, at the same time its result has high accuracy. In the method,a uniformity approach is used to deal with evidence variables,and then the con- cept of most probable point （MPP） in probability theory is introduced to reliability analysis for hybrid model,which has both aleatory and epistemic uncertainty. A first order Taylor expansion is expanded at MPP,which is used for reliability analysis as approximation model instead of the original performance function. Finally,three numerical examples are analyzed to demonstrate the effectiveness of the present method.
出处
《计算力学学报》
CAS
CSCD
北大核心
2016年第2期135-143,共9页
Chinese Journal of Computational Mechanics
基金
国家自然科学基金(11172096)
国家自然科学基金优秀青年科学基金(51222502)
湖南省杰出青年基金(14JJ1016)资助项目
关键词
混合可靠性分析
概率模型
证据理论
可靠性区间
hybrid reliability
probability model
evidence theory
reliability interval
