Variability effect of strength and geometric parameters on the stability factor of failure surfaces of rock slope by numerical analysis

Ahmed Z., Wang S., Jasim O. H., Xu Y., Wang P.

ARABIAN JOURNAL OF GEOSCIENCES, vol.13, no.21, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13 Issue: 21
  • Publication Date: 2020
  • Doi Number: 10.1007/s12517-020-06080-5
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), Geobase, INSPEC
  • Yıldız Technical University Affiliated: Yes


In loose or highly weathered rock slopes, the circular shear failure mechanism occurs in large scale. Most rock slope stability investigations ignore the influence of geometric parameters, i.e., failure surface entry point distance (le). This study presents failure surface determination based on constant element stress-based method. The failure surfaces and their sliding mechanism are analyzed first by using FLAC(3D) (Fast Lagrangian Analysis of Continua in three-dimension). A real case of instability corresponds to a loose rock is presented and its stability is determined by numerical analysis. To investigate the effectiveness of present method the influence of shear strength (c, phi) and geometric parameters (alpha, beta) on the safety factor (FS) is also analyzed by using Geo5, FLAC(3D) and ABAQUS computer codes. Then, Geo5 and Statistical Package for the Social Sciences (SPSS) softwares were used to determine the effect of dimensionless parameter lambda (lambda) on the failure surface entry point distance (le) and length of failure arc (L). The results show that shear failure may occur in non-homogeneous slope. Shear failure has exit and entry points situated either on the surface or near the toe of slope. The length of failure arc (L) is affected by the le and lambda. Moreover, it can be acknowledged that the relation of both L and le with shear strength parameters (c, phi) is logarithmic, respectively. So, based on the rock strength parameters, L and le are predictable by using the equations derived from non-linear regression.