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A novel structural reliability analysis method via improved maximum entropy method based on nonlinear mapping and sparse grid numerical integration

机译:一种新颖的结构可靠性分析方法,通过改进基于非线性映射和稀疏网格数值集成的最大熵方法

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摘要

This paper proposes an improved maximum entropy method for reliability analysis (i-MEM), in which the limit state function is transformed by a nonlinear mapping to predict the failure probability accurately. Through the nonlinear mapping, more statistical information can be obtained by the first-four statistical moments, and the truncation error originating from numerical integration is solved by the bounded limit state function after the nonlinear mapping, therefore the i-MEM can capture the tail information of the real probability distribution. In order to calculate the statistical moments in i-MEM with accuracy and efficiency, an improved sparse grid numerical integration method (i-SGNI) is developed on the basis of the normalized moment-based quadrature rule. Combining the i-MEM and i-SGNl, a novel reliability analysis method is proposed. To illustrate the accuracy, efficiency and numerical stability of the proposed method, six numerical examples and one engineering example are presented, compared with some common reliability analysis methods. The results show that the proposed method, with the combination of i-MEM and i-SGNI, can achieve a good balance between accuracy and efficiency for structural reliability analysis.
机译:本文提出了一种改进的可靠性分析(I-MEM)的最大熵方法,其中通过非线性映射改变极限状态功能,以准确地预测失效概率。通过非线性映射,可以通过前四个统计矩获得更多统计信息,并且在非线性映射之后,通过界限的限制状态函数来解决源自数值积分的截断误差,因此I-MEM可以捕获尾信息实际概率分布。为了以准确性和效率计算I-MEM中的统计瞬间,基于标准化的力矩基正规规则开发了一种改进的稀疏网格数值积分方法(I-SGNI)。组合I-MEM和I-SGNL,提出了一种新颖的可靠性分析方法。为了说明所提出的方法的准确性,效率和数值稳定性,与一些常见可靠性分析方法相比,提出了六个数值示例和一个工程例。结果表明,该方法具有I-MEM和I-SGNI的组合,可以在结构可靠性分析的准确性和效率之间实现良好的平衡。

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