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Coupled fuzzy-interval model and method for structural response analysis with non-probabilistic hybrid uncertainties

机译:具有非概率混合不确定性的结构响应分析的耦合模糊状态和方法

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In many engineering practices with uncertainty, the non-probabilistic methods play an increasing important role. To overcome the limitation of traditional single-uncertainty modeling methods in handling coupled uncertain problems, this paper develops a more general hybrid uncertainty analysis framework. The non-probabilistic hybrid uncertainties are expressed as coupled fuzzy-interval variables, where the bounds of interval are interpreted as fuzzy sets instead of deterministic values. By means of the cut-set strategy and decomposition theorem in fuzzy set theory, the hybrid uncertain problem is transformed into a series of dual-interval problems. The conservative and radical extreme-value predictions in different variable subspaces are adopted to characterize the coupled uncertainty in output response. To further improve the computational efficiency of extreme-value prediction, an adaptive response surface model using radial basis function is proposed, where the potential global optimum points are introduced as the new sample points in the sequential sampling process. Finally, the effectiveness of the proposed method on dealing with non-probabilistic hybrid uncertainties is validated by two examples. (c) 2020 Elsevier B.V. All rights reserved.
机译:在许多具有不确定性的工程实践中,非概率方法起着越来越重要的作用。为了克服传统单不确定性建模方法在处理耦合不确定问题方面的局限性,开发了更通用的混合不确定性分析框架。非概率的混合不确定性表示为耦合模糊间变量,其中间隔的边界被解释为模糊集而不是确定性值。通过模糊集理论中的切割策略和分解定理,混合不确定问题转变为一系列双间隔问题。采用不同可变子空间中的保守和自由基极值预测来表征输出响应中的耦合不确定性。为了进一步提高极值预测的计算效率,提出了一种使用径向基函数的自适应响应表面模型,其中潜在的全球最佳点被引入顺序采样过程中的新采样点。最后,通过两个例子验证了拟议方法关于处理非概率混合不确定性的方法的有效性。 (c)2020 Elsevier B.V.保留所有权利。

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