Algorithm for generation correlative variables and Monte Carlo simulation of slope reliability

CHEN Jiang-hong; LI Jian-lin; XU Xiao-liang; WAN Liang-peng; HUANG Yi-sheng; DENG Hua-feng

doi:10.16285/j.rsm.2017.11.033

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Algorithm for generation correlative variables and Monte Carlo simulation of slope reliability

更新时间：2026-06-25

- Algorithm for generation correlative variables and Monte Carlo simulation of slope reliability
- Vol. 38, Issue 11, Pages: 3341-3346(2017)
- 作者机构：
  
  1. 三峡大学三峡库区地质灾害教育部重点实验室,湖北,宜昌,443002
  2. 三峡大学理学院,湖北,宜昌,443002
  3. 中国三峡建设管理有限公司,四川,成都,610000
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2017.11.033
  CLC： TU457
- Online First：05 June 2018，
  
  Published：2017
- 稿件说明：
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CHEN Jiang-hong, LI Jian-lin, XU Xiao-liang, et al. Algorithm for generation correlative variables and Monte Carlo simulation of slope reliability[J]. 2017, 38(11): 3341-3346.
DOI：

CHEN Jiang-hong, LI Jian-lin, XU Xiao-liang, et al. Algorithm for generation correlative variables and Monte Carlo simulation of slope reliability[J]. 2017, 38(11): 3341-3346. DOI： 10.16285/j.rsm.2017.11.033.

摘要

描述变量相关性的多元分布模型有着广泛的工程应用。利用多元线性自回归模型和排序算法，研究了具有指定边缘分布和指定相关结构的多维随机变量的生成算法。基于MATLAB语言编程实现了该算法。将该算法应用于结构可靠度和边坡可靠度直接抽样Monte Carlo模拟计算问题中，解决了传统Monte Carlo模拟难以考虑变量互相关性的难题。数值实验表明，该方法计算结果精确，可以放松理论模型的理想化要求，能更真实的反映问题实际。将该方法与一次二阶矩方法计算结果对比发现，一次二阶矩方法往往对可靠度有过高的估计。此外失效概率对变量分布类型比较敏感，相同的安全系数可能对应不同的失效概率。提出的方法可以应用于复杂结构系统的可靠度计算问题，并可推广应用于其他领域的相依变量的仿真问题。

Abstract

A multivariate distribution model that describes the relevance of variables has a wide range of engineering applications. Based on the multiple linear autoregressive model and the sorting algorithm

a generation algorithm of multidimensional random variable with the specified edge distribution and the specified structure is studied. The algorithm was implemented using MATLAB. The proposed approach

a direct sampling Monte Carlo simulation method

is applied to determine the structural reliability and slope reliability. The problem related to correlative variables

difficult to solve by traditional Carlo Monte simulation

is solved by the proposed method. The numerical analysis shows that this method is reliable in calculation. The method can loosen the idealized restrains of theory model

and realistically reflect the practical problem. Compared the results from first-order second-moment method

it is found that the first-order second-moment method usually gives a high estimation in reliability. Failure probability is sensitive to the distribution type of the variable. Same safety factor maybe correspond to different failure probabilities. The proposed approach can be applied to calculation of complex structural system reliability and to simulation with dependent random variables in other fields.

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