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Volume 40 Issue 1
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WANG Jun-jie, FENG Deng, CHAI He-jun, LIU Yun-fei. Dominant discontinuities based on stereographic projection and K-means clustering algorithm[J]. Chinese Journal of Geotechnical Engineering, 2018, 40(1): 74-81. DOI: 10.11779/CJGE201801006
Citation: WANG Jun-jie, FENG Deng, CHAI He-jun, LIU Yun-fei. Dominant discontinuities based on stereographic projection and K-means clustering algorithm[J]. Chinese Journal of Geotechnical Engineering, 2018, 40(1): 74-81. DOI: 10.11779/CJGE201801006
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Dominant discontinuities based on stereographic projection and K-means clustering algorithm

  • 1.Key Laboratory for Hydraulic and Waterway Engineering of Ministry of Education, Chongqing Jiaotong University, Chongqing 400074, China
    2.National Engineering Laboratory for Road Engineering and Disaster Prevention and Reduction Technology in Mountainous Areas, China Merchants Chongqing Communications Technology Research &Design Institute Co., Ltd., Chongqing 400067, China
    3.Engineering Research Center of Diagnosis Technology and Instruments of Hydro-Construction, Chongqing Jiaotong University, Chongqing 400074, China

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  • Received Date: October 12, 2016
  • Published Date: January 24, 2018
    Graphical Abstract
    • Abstract
  • For the rock slope with many complicated discontinuities, the selection and analysis of the discontinuities are a very important work. The traditional analysis methods are insufficient and inadequate. The analysis results have a lot of subjective factors, and are inconvenient to be applied in practice. The selection and analysis of intersection lines of discontinuity are treated as the starting point. With the aid of stereographic projection, the possible sliding zone of sliding wedge can be first determined. The possible sliding line of intersection can be selected. So the range of calculation can be reduced. The symmetric axis center is used as the initial rallying point. The dominant orientations of discontinuities can be selected and analyzed through the probabilistic analysis of the stereographic projection based on the K-means clustering algorithm. A case study on a rock slope in Chongqing is used. The study shows that the results are reliable and reasonable, and the dominant orientations and classification are more precise.
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    • References (21)
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