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Structural Reliability Assessment by a Modified Spectral Stochastic Meshless Local Petrov-Galerkin Method

机译:由改进的光谱随机无线局部Petrov-Galerkin方法进行结构可靠性评估

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摘要

This study presents a new tool for solving stochastic boundary-value problems. This tool is created by modify the previous spectral stochastic meshless local Petrov-Galerkin method using the MLPG5 scheme. This modified spectral stochastic meshless local Petrov-Galerkin method is selectively applied to predict the structural failure probability with the uncertainty in the spatial variability of mechanical properties. Except for the MLPG5 scheme, deriving the proposed spectral stochastic meshless local Petrov-Galerkin formulation adopts generalized polynomial chaos expansions of random mechanical properties. Predicting the structural failure probability is based on the first-order reliability method. Further comparing the spectral stochastic finite element-based and meshless local Petrov-Galerkin-based predicted structural failure probabilities indicates that the proposed spectral stochastic meshless local Petrov-Galerkin method predicts the more accurate structural failure probability than the spectral stochastic finite element method does. In addition, generating spectral stochastic meshless local Petrov-Galerkin results are considerably time-saving than generating Monte-Carlo simulation results does. In conclusion, the spectral stochastic meshless local Petrov-Galerkin method serves as a time-saving tool for solving stochastic boundary-value problems sufficiently accurately.
机译:本研究提出了一种解决随机边值问题的新工具。使用MLPG5方案修改先前的光谱随机无线局部PETROV-GALERKIN方法来创建此工具。这种改进的光谱随机网状无源Petrov-Galerkin方法被选择性地应用于预测机械性能的空间变异性的不确定性的结构故障概率。除了MLPG5方案外,推导出所提出的光谱随机无线局部Petrov-Galerkin配方采用随机力学性能的广义多项式混沌扩展。预测结构故障概率基于一阶可靠性方法。进一步比较基于光谱随机有限元和无丝毫的本地Petrov-Galerkin的预测结构失败概率,表明所提出的光谱随机无线局部Petrov-Galerkin方法预测比光谱随机有限元方法更精确的结构失效概率。此外,产生光谱随机无线无线局部Petrov-Galerkin结果比生成Monte-Carlo仿真结果相当节省时间。总之,光谱随机丝毫本地Petrov-Galerkin方法用作充分精确地解决随机边界值问题的节省时间。

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