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Safety analysis of structures with probability and evidence theory

机译:基于概率和证据理论的结构安全性分析

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摘要

In safety analysis of structures, classical probabilistic analysis has been a popular approach in engineering. However, it is not always to obtain sufficient information to model all uncertain parameters of structures system by probability theory, especially at early stage of design. Under this circumstance, probability theory (used to model random uncertainty) combined with evidence theory (used to model epistemic uncertainty) may be utilized in safety analysis of structures. This paper proposed a novel method for safety analysis of structures based on probability and evidence theory. Firstly, Bayes conversion method is used as the way for precision of evidence body, and the mean and variance of epistemic uncertain variables is defined. Then epistemic uncertainty variables is transformed to normal random variables by reflection transformation method, and the checking point method (J-C method) is used to solve most probability point and reliability. A numerical example and two engineering examples are given to demonstrate the performance of the proposed method. The results show both precision and computational efficiency of the method is high. Moreover, the proposed method provides basis for reliability-based optimization with the hybrid uncertainties.
机译:在结构安全性分析中,经典概率分析已成为工程学中的一种流行方法。但是,并非总是能获得足够的信息来通过概率论对结构系统的所有不确定参数进行建模,尤其是在设计初期。在这种情况下,概率论(用于模拟随机不确定性)和证据理论(用于模拟认知不确定性)可以用于结构安全性分析。提出了一种基于概率和证据理论的结构安全性分析新方法。首先,以贝叶斯转换法作为证据体精度的方法,定义了认知不确定变量的均值和方差。然后通过反射变换法将认知不确定性变量转换为正态随机变量,并采用检验点法(J-C方法)求解大多数概率点和可靠性。数值算例和两个工程算例说明了所提方法的性能。结果表明,该方法精度高,计算效率高。此外,所提出的方法为基于混合不确定性的可靠性优化提供了基础。

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