基于RBF神经网络的露天采石场边坡稳定性数值模拟  

Numerical Simulation on Slope Stability of Open-pit Quarry Based on RBF Neural Network

作　　者：屈晓明 QU Xiaoming(Hubei Coal Geological 125 Team,Yichang 443000,Hubei,China)

机构地区：[1]湖北煤炭地质一二五队,湖北宜昌443000

出　　处：《水力发电》2023年第6期34-38,共5页Water Power

基　　金：湖北煤炭地质局科技创新2022年项目。

摘　　要：根据露天采石场的实际环境,采用FLAC建立边坡的三维模型,选取边坡的力学指标,将其输入至RBF神经网络中,对该边坡的稳定性进行数值模拟。结果表明,在开挖过程中,边坡岩土体的压应力逐渐减小,拉应力区出现在边坡的中部,容易导致边坡坍塌;边坡内各岩层会出现不同程度的膨胀变形,边坡坡脚处的应力演化条件较为复杂,会出现最大的膨胀变形。According to the actual environment of a open-pit quarry,the three-dimensional model of slope is established with FLAC,and the mechanical indexes of the slope are selected and input into the RBF neural network to simulate the stability of the slope.The results show that,(a)during the excavation,the compressive stress of slope rock mass decreases gradually,and the tensile stress zone appears in the middle of slope,which is easy to cause slope collapse;and(b)each rock stratum in the slope will have different degrees of expansion deformation,the stress evolution conditions at slope toe are relatively complex,and the maximum expansion deformation will occur.

关 键 词：露天采石场 边坡稳定性分析 数值模拟 RBF神经网络 FLAC 

分 类 号：TU457[建筑科学—岩土工程]