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Non-probabilistic uncertainty quantification and response analysis of structures with a bounded field model

机译:具有边界场模型的结构的非概率不确定性量化和响应分析

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A general framework for quantifying bounded field uncertainties in loading conditions, material properties and geometrical dimensions is developed in this study. By using a non-probabilistic series expansion (NPSE) method similar as the Expansion Optimal Linear Estimator (EOLE), the bounded field uncertainties with certain spatial correlation characteristic are modeled with a reduced set of uncertain-but-bounded coefficients. Further, it is shown that these coefficients are bounded by a multi-ellipsoid convex model. The gradient-based mathematical programming algorithm combined with an efficient adjoint variable sensitivity scheme is then employed to evaluate the upper and lower bounds of structural performance. The proposed method allows spatially varying uncertainties as well as their dependencies to be described in a non-probabilistic framework, which ensures the objectivity and accuracy of representations of bounded field uncertainties. Moreover, it provides an efficient way to evaluate the variation range of structural performance with a significant reduction of computational cost compared to direct treatments. Numerical examples regarding the performance bound evaluation of structures with bounded field uncertainties are presented to illustrate the validity and applicability of this method. (C) 2019 Elsevier B.V. All rights reserved.
机译:在这项研究中,开发了用于量化载荷条件,材料特性和几何尺寸中的边界场不确定性的通用框架。通过使用类似于扩展最优线性估计器(EOLE)的非概率级数扩展(NPSE)方法,使用减少的一组不确定但有界的系数对具有某些空间相关特性的有界场不确定性进行建模。此外,示出了这些系数由多椭球凸模型限制。然后,将基于梯度的数学规划算法与有效的伴随变量敏感度方案相结合,用于评估结构性能的上限和下限。所提出的方法允许在非概率框架中描述空间变化的不确定性及其依赖性,这确保了界场不确定性表示的客观性和准确性。而且,与直接处理相比,它提供了一种有效的方法来评估结构性能的变化范围,同时显着降低了计算成本。给出了关于具有有限场不确定性的结构的性能边界评估的数值例子,以说明该方法的有效性和适用性。 (C)2019 Elsevier B.V.保留所有权利。

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