High‐dimensional model representation for structural reliability analysis
High‐dimensional model representation for structural reliability analysis
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DOI：
10.1002/cnm.1118
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发表时间：
2009-04
影响因子：
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通讯作者：
R. Chowdhury;B. N. Rao;A. Prasad
中科院分区：
文献类型：
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作者：
R. Chowdhury;B. N. Rao;A. Prasad
本文提出了一种新的计算工具，预测失效概率的结构/机械系统受到随机载荷，材料性能和几何形状。该方法涉及高维模型表示（HDMR），有利于低维近似的原始高维隐式极限状态/性能函数，响应面生成的HDMR组件功能，和蒙特卡洛模拟。HDMR是一套通用的定量模型评估和分析工具，用于捕获输入和输出模型变量集之间的高维关系。如果高阶变量的相关性很弱，这是一种非常有效的系统响应公式，允许物理模型被前几个低阶项捕获。一旦定义了原始隐式极限状态/功能函数的近似形式，就可以通过统计模拟来获得失效概率。九个涉及数学函数和结构力学问题的数值例子的结果表明，所提出的方法提供了准确和计算效率高的估计故障的概率。版权所有© 2008约翰威利父子有限公司.
This paper presents a new computational tool for predicting failure probability of structural/mechanical systems subject to random loads, material properties, and geometry. The method involves high-dimensional model representation (HDMR) that facilitates lower-dimensional approximation of the original high-dimensional implicit limit state/performance function, response surface generation of HDMR component functions, and Monte Carlo simulation. HDMR is a general set of quantitative model assessment and analysis tools for capturing the high-dimensional relationships between sets of input and output model variables. It is a very efficient formulation of the system response, if higher-order variable correlations are weak, allowing the physical model to be captured by the first few lower-order terms. Once the approximate form of the original implicit limit state/performance function is defined, the failure probability can be obtained by statistical simulation. Results of nine numerical examples involving mathematical functions and structural mechanics problems indicate that the proposed method provides accurate and computationally efficient estimates of the probability of failure. Copyright © 2008 John Wiley & Sons, Ltd.