Uncertainty in input fracture geometric parameters during analysis of the stability of jointed rock slopes is inevitable and therefore the stochastic discrete fracture network (DFN) — distinct element method (DEM) is an efficient modeling tool. In this research, potentially unstable conditions are detected in the right abutment of the Karun 4 dam and downstream of the dam body as a case study. Two extreme states with small and relatively large block sizes are selected and a series of numerical DEM models are generated using a number of validated DFN models. Stability of the rock slope is assessed in both static and dynamic loading states. Based on the design basis earthquake (DBE) and maximum credible earthquake (MCE) expected in the dam site, histories of seismic waves are applied to analyze the stability of the slope in dynamic earthquake conditions. The results indicate that a MCE is likely to trigger sliding of rock blocks on the rock slope major joint. Furthermore, the dynamic analysis also shows a local block failure by the DBE, which can consequently lead to slope instability over the long term. According to the seismic behavior of the two models, larger blocks are prone to greater instability and are less safe against earthquakes.

在分析节理岩质边坡稳定性过程中输入裂缝几何参数的不确定性是不可避免的，因此随机离散裂缝网络（DFN）-离散元方法（DEM）是一种有效的建模工具。在这项研究中，作为案例研究，在Karun 4坝的右岸和坝体的下游发现了潜在的不稳定状况。选择具有较小和相对较大块大小的两个极端状态，并使用许多经过验证的DFN模型生成一系列数值DEM模型。在静态和动态载荷状态下都可以评估岩石边坡的稳定性。根据设计基准地震（DBE）和大坝现场预计的最大可信地震（MCE），利用地震波的历史来分析动态地震条件下边坡的稳定性。结果表明，MCE可能触发岩石边坡主要节理上的岩石块滑动。此外，动态分析还显示了DBE造成的局部块体破坏，因此长期可能导致边坡不稳定。根据这两个模型的地震行为，较大的块体倾向于较大的不稳定性，并且对地震的安全性较低。