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Fast variable stiffness composite cylinder uncertainty analysis by using reanalysis assisted Copula function

机译:快速变量刚度复合圆筒通过使用Reanalysis辅助Copula功能进行不确定性分析

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There are lots of uncertainties in variable-stiffness composite materials such as material properties, fibre volume fraction, geometries at various scale and matrix porosity. Commonly, these uncertainties are not always mutually independent and there exist correlations among these random input variables. These correlations may affect the output of composite significantly. To address these correlations, a novel approach for uncertainty analysis based on copula function assisted by reanalysis method is suggested. The Copula function is utilized to address the correlations of random input variables. Monte Carlo simulation (MCS) is employed to obtain the uncertainty analysis. Therefore, a large number of samples should be generated and the expensive computational cost is not feasible when the popular finite element (FE) model is utilized. To save the computational cost and make the uncertainty analysis feasible in practice, an efficient fast computation method, reanalysis method is integrated in the frame. The numerical test demonstrates that the proposed approach is an efficient uncertainty analysis tool for the practical engineering problems.
机译:可变刚度复合材料中存在许多不确定性,例如材料性质,纤维体积分数,各种规模的几何形状和基质孔隙率。通常,这些不确定性并不总是相互独立的,并且这些随机输入变量之间存在相关性。这些相关性可能显着影响复合材料的输出。为了解决这些相关性,提出了一种基于Reanalysis方法辅助的Copula功能的不确定分析方法。 Copula功能用于解决随机输入变量的相关性。 Monte Carlo仿真(MCS)用于获得不确定性分析。因此,当使用流行的有限元(FE)模型时,应产生大量样本,并且在使用流行的有限元(FE)模型时,昂贵的计算成本是不可行的。为了节省计算成本并使实际上可行的不确定性分析,高效的快速计算方法,重新分析方法集成在框架中。数值测试表明,该方法是实际工程问题的有效的不确定性分析工具。

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