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The stepwise accuracy-improvement strategy based on the Kriging model for structural reliability analysis

机译:基于结构可靠性分析的Kriging模型的逐步精度改进策略

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摘要

For structural reliability analysis with time-consuming performance functions, an innovative design of experiment (DoE) strategy of the Kriging model is proposed, which is named as the stepwise accuracy-improvement strategy. The epistemic randomness of the performance value at any point provided by the Kriging model is used to derive an accuracy measure of the Kriging model. The basic idea of the proposed strategy is to enhance the accuracy of the Kriging model with the best next point that has the largest improvement with regard to the accuracy measure. An optimization problem is developed to define the best next point. The objective function is the expectation that quantifies how much an untried point could enhance the accuracy of the Kriging model. Markov chain Monte Carlo sampling and Gauss-Hermite quadrature are employed to make several approximations to solve the optimization problem and get the best next point. A structural reliability analysis method is also constructed based on the proposed strategy and the accuracy measure employed. Several examples are studied. The results validate the advantages of the proposed DoE strategy.
机译:对于具有耗时的性能功能的结构可靠性分析,提出了一种克里格模型的实验(DOE)策略的创新设计,被命名为逐步精度改善策略。通过Kriging模型提供的任何点的性能值的认知随机性用于得出Kriging模型的精度测量。拟议策略的基本思想是提高Kriging模型的准确性,其最佳下一点具有最大的准确度措施的改进。开发了优化问题以定义最佳下一点。目标函数是期望量化未经定位点可以提高克里格化模型的准确性的预期。马尔可夫链Monte Carlo采样和高斯 - Hermite正交用来解决解决优化问题的几个近似,并获得最佳下一点。基于所提出的策略和所采用的准确度,还构建了结构可靠性分析方法。研究了几个例子。结果验证了拟议的DOE策略的优势。

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