边坡稳定可靠度分析的新型四阶矩法

提出了一种边坡稳定可靠度分析的新型四阶矩计算方法.该方法将均匀设计法、径向基神经网络技术和最大熵原理相结合对边坡进行可靠性分析.采用均匀设计法确定粘聚力和内摩擦角的网络训练样本空间,并采用基于有限元的强度折减法计算样本空间中样本所对应的边坡安全系数.利用这些样本及对应的安全系数训练径向基神经网络.利用训练好的神经网络获得满足统计数量要求的边坡安全系数,并计算边坡安全系数前四阶矩.利用最大熵原理得到边坡安全系数的概率密度函数近似表达式、边坡失效概率以及相应的可靠指标.该方法的计算结果与蒙特卡罗法的计算结果对比表明该方法具有较高的精度.

A New Method of Four Order Moments for Reliability Analysis on Slope Stability

In this study, a new four-order moment method for reliability analysis of slope stability was proposed. The reliability analysis of slope stability was conducted by the combination of the uniform design method, the RBF neural network technique, and the maximum entropy principle. The network training sample space of cohesion and internal friction angle was firstly determined by the uniform design method, and the slope safety factor related to the samples was obtained by the strength reduction method using the finite element analysis. The RBF neural network was trained by the samples and their corresponding safety factors. The safety factors of the slope satisfying the statistical requirement were obtained by the well-trained neural network, and the first four-order moments of the slope safety factor were calculated. Furthermore, the approximate expression of probability density function of the slope safety factor, the slope failure probability, and the corresponding reliability index were investigated by the maximum entropy principle. Compared with the results from Monte Carlo method, the proposed method shows high precision.