基于蒙特卡罗模拟的高效边坡可靠度修正方法

传统的蒙特卡罗模拟方法在分析由于参数不确定性修正而引起的可靠度修正问题时效率较低。为此,提出了一种基于蒙特卡罗模拟的高效边坡可靠度修正方法,该方法主要包括2个关键步骤:1)根据参数初始分布利用蒙特卡罗模拟方法计算边坡的失效概率,并输出蒙特卡罗模拟的失效样本;2)利用参数统计特征值修正后的联合概率密度函数和蒙特卡罗模拟失效样本计算修正后边坡的失效概率。以两个边坡问题为例说明了所提方法的有效性。结果表明:所提出的方法在计算修正的失效概率过程中无需重新执行蒙特卡罗模拟,计算过程简单、计算效率高。此外,所提方法能够适用于隐式表达功能函数的边坡可靠度修正问题,并能够有效地解决单变量和多变量修正的边坡可靠度修正问题。

EFFICIENT SLOPE RELIABILITY UPDATING METHOD BASED ON MONTE CARLO SIMULATION

The traditional Monte Carlo simulation (MCS) could be prohibitively expensive in relatively low-probability slope reliability updating problems caused by the updating of the uncertainty of the uncertain parameters. This paper aims to propose an efficient slope reliability updating method based on MCS. The slope failure probability for the original probability distribution of input uncertain parameters is first calculated using the MCS and the corresponding failure samples are extracted. Then, the slope failure probabilities for any other probability distributions of input uncertain parameters are directly obtained based on the failure samples. Two slope examples are investigated to demonstrate the validity of the proposed method. The results show that the new efficient slope reliability updating method based on MCS proposed in this paper is simple and efficient in calculating the new updated slope failure probability, as it does not need to re-run the MCS. It not only can deal with the reliability problems with implicit performance functions, but also can solve the slope reliability problems involving single and multiple variables.