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A Genetic Algorithm for Locating the Multiscale Critical Slip Surface in Jointed Rock Mass Slopes

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  • Qiang Xu
  • Jian-yun Chen
  • Jing Li
  • Hong-yuan Yue

Abstract

The joints have great influence on the strength of jointed rock mass and lead to the multiscale, nonhomogeneous, and anisotropic characteristics. In order to consider these effects, a new model based on a genetic algorithm is proposed for locating the critical slip surface (CSS) in jointed rock mass slope (JRMS) from its stress field. A finite element method (FEM) was employed to analyze the stress field. A method of calculating the mechanical persistence ratio (MPR) was used. The calculated multiscale and anisotropic characteristics of the MPR were used in the fitness function of genetic algorithm (GA) to calculate the factor of safety. The GA was used to solve optimization problems of JRMS stability. Some numerical examples were given. The results show that the multiscale and anisotropic characteristics of the MPR played an important role in locating the CSS in JRMS. The proposed model calculated the CSS and the factor of safety of the slope with satisfactory precision.

Suggested Citation

  • Qiang Xu & Jian-yun Chen & Jing Li & Hong-yuan Yue, 2014. "A Genetic Algorithm for Locating the Multiscale Critical Slip Surface in Jointed Rock Mass Slopes," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, February.
    • Handle: RePEc:hin:jnlmpe:543081
    DOI: 10.1155/2014/543081
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