秦琪, 张玄一, 卢朝辉, 赵衍刚. 简化三阶矩拟正态变换及其在结构可靠度分析中的应用[J]. 工程力学, 2020, 37(12): 78-86, 113. DOI: 10.6052/j.issn.1000-4750.2020.01.0015
引用本文: 秦琪, 张玄一, 卢朝辉, 赵衍刚. 简化三阶矩拟正态变换及其在结构可靠度分析中的应用[J]. 工程力学, 2020, 37(12): 78-86, 113. DOI: 10.6052/j.issn.1000-4750.2020.01.0015
QIN Qi, ZHANG Xuan-yi, LU Zhao-hui, ZHAO Yan-gang. SIMPLIFIED THIRD-ORDER NORMAL TRANSFORMATION AND ITS APPLICATION IN STRUCTURAL RELIABILITY ANALYSIS[J]. Engineering Mechanics, 2020, 37(12): 78-86, 113. DOI: 10.6052/j.issn.1000-4750.2020.01.0015
Citation: QIN Qi, ZHANG Xuan-yi, LU Zhao-hui, ZHAO Yan-gang. SIMPLIFIED THIRD-ORDER NORMAL TRANSFORMATION AND ITS APPLICATION IN STRUCTURAL RELIABILITY ANALYSIS[J]. Engineering Mechanics, 2020, 37(12): 78-86, 113. DOI: 10.6052/j.issn.1000-4750.2020.01.0015

简化三阶矩拟正态变换及其在结构可靠度分析中的应用

SIMPLIFIED THIRD-ORDER NORMAL TRANSFORMATION AND ITS APPLICATION IN STRUCTURAL RELIABILITY ANALYSIS

  • 摘要: 针对三阶矩拟正态变换理论公式系数形式复杂及现有相关系数的转换公式适用范围未明确的问题,通过对公式系数进行简化和对相关系数的讨论,提出了独立随机变量和相关随机变量的简化三阶矩拟正态变换模型,并给出了相关系数转换公式的简明适用范围。通过将提出的简化三阶矩拟正态变换模型与一阶可靠度分析方法(FORM)结合,发展了随机变量分布未知条件下的可靠度分析方法,并采用数值算例验证了该方法的准确性和适用性。研究结果表明,所提出的简化三阶矩拟正态变换模型具有较高的准确性和适用性,能够与FORM分析方法结合,实现随机变量分布未知条件下的结构可靠度分析。

     

    Abstract: Existing third moment normal transformation (TMNT) model formula coefficients are relatively complex and the applicability range of correlation coefficients translation formula has not been clearly defined. A simplified TMNT model is proposed by simplifying the formula coefficients and by discussing the correlation coefficients. The proposed model is applicable for independent and related random variables. The explicit applicable range of a correlation coefficients translation formula is also proposed, which can be used to determine whether the proposed model can be applied for a particular engineering problem. Combined with first order reliability method (FORM), the proposed model is adopted to reliability analysis including random variables with unknown distributions. Numerical examples show that the proposed model has enough accuracy and efficiency and can be applied to conduct the reliability analysis including random variables with unknown distributions.

     

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