提出分析相关非正态变量可靠度计算问题的随机响应面法,采用Nataf变换成功地解决输入变量相关时随机响应面法的配点问题及可靠度计算问题。推导4~6阶Hermite随机多项式展开的解析表达式,并编写基于C#语言的随机响应面法计算程序。以岩质边坡平面滑动破坏模式为例证明随机响应面法在边坡可靠度分析中的有效性。研究结果表明,基于Nataf变换的随机响应面法能够有效分析含有相关非正态变量的边坡可靠度问题。随机响应面法的计算精度优于传统的FORM方法,其计算效率高于传统的蒙特卡罗模拟方法,其收敛性在数学意义上是有保证的。随机多项式展开的阶数几乎对边坡安全系数均值的估计没有影响,但是在边坡失效概率的计算中要选择适当的随机多项式展开的阶数。在基于随机响应面法的可靠度分析框架内,边坡安全系数计算和可靠度分析2个过程分开独立进行,同时计算安全系数和失效概率能够更加系统地进行边坡稳定性分析。研究成果为拓展随机响应面法在边坡可靠度分析中的应用奠定了一定的基础。
This paper aims at proposing a stochastic response surface method(SRSM) for reliability analysis involving correlated random variables.The Nataf transformation is adopted to effectively transform the correlated nonnormal random variables into the independent standard normal variables,which facilitates the collocation points associated with the correlated random variables and reliability computation using the SRSM.Explicit polynomials are derived for fourth-order to sixth-order Hermite polynomial chaos expansions of any number of random variables.A C#-language based computer program WHUSRSM(Wuhan University SRSM) is developed.An example of reliability analysis of rock slope stability with plane failure is presented to demonstrate the validity and capability of the proposed SRSM.The results indicate that the proposed SRSM can evaluate the reliability of rock slope stability involving correlated random variables efficiently.The proposed SRSM has a higher accuracy than the conventional first-order reliability method;and its efficiency is higher than Monte Carlo simulations.Moreover,the convergence in Hilbert space of the SRSM can be ensured in any case.The mean of factor of safety for slope stability can be accurately estimated by the proposed SRSM with different orders.However,the orders of the SRSM should be selected carefully to accurately estimate the probability of rock slope failure.The calculation of factor of safety and the reliability analysis can be conducted separately within the framework of the SRSM based on reliability analysis.Slope stability analysis would be investigated systematically with the results associated with factor of safety as well as probability of failure.These results can provide a basis for extending the application of the SRSM to reliability analysis of rock slope stability.