关键词: 堤防边坡, 抗滑稳定, 可靠度分析, 正交试验, BP神经网络, 蒙特卡洛法, 失效概率

Abstract: It is not convenient to calculate failure probability using traditional reliability theory for complex structures such as levee slope whose performance function cannot be explicitly expressed. In this paper, neural network model is used to replace the performance function of slope and the Monte-Carlo method is used to calculate the failure probability. The samples for training network are generated through orthogonal trial, and the safety factors of the samples are calculated by the strength reduction method of finite element method (FEM). The failure probability is calculated by constructing performance function by using the strong non-linear fitting ability of neural network. Through an example calculation, the failure probability of levee slope is studied with internal friction angle, cohesion force and elastic modulus as random variables. This method is proved to be simple and reasonable.

Key words: levee slope, anti-sliding stability, reliability analysis, orthogonal trial, BP neural network, Monte-Carlo method, failure probability