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Probabilistic Kinematic Analysis of Rock Slope Stability Using Terrestrial LiDAR

지상라이다를 이용한 확률론적 해석기법 기반의 운동학적 안정성 해석

  • 홍석권 (세종대학교 지구정보공학과) ;
  • 박혁진 (세종대학교 지구정보공학과)
  • Received : 2019.02.07
  • Accepted : 2019.04.04
  • Published : 2019.06.28

Abstract

Kinematic analysis determines the stability of rock slope by analyzing the relationship between the slope face orientation and the discontinuity orientation. In this study, terrestrial LiDAR was used to obtain a large amount of discontinuity orientation data and then, the probabilistic characteristics of the orientation data obtained using terrestrial LiDAR were analyzed. Subsequently, the probabilistic kinematic analysis was carried out using the discontinuity orientations generated randomly from Fisher function in Monte Carlo simulation. In addition, the probabilistic kinematic analysis was also performed using the actual orientation data obtained from the terrestrial LiDAR to compare their results. Consequently, the results of both probabilistic analyses showed similar results. Therefore, if sufficient orientation data are provided by other means such as terrestrial LiDAR, the probabilistic analysis will show reasonable results using the actual field data without randomly generating orientation data. In addition, the deterministic kinematic analysis was also carried out using representative orientation of discontinuity sets. The analysis result of the probabilistic analysis showed similar results with the deterministic analysis because the dispersion of the discontinuity orientations in a joint set is not large.

Keywords

discontinuity;uncertainty;kinematic analysis;probabilistic analysis;terrestrial LiDAR

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Fig. 1. Flowchart for point cloud acquisition using Terrestrial LiDAR.

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Fig. 3. Scanning positions and point cloud acquired from various scanning positions.

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Fig. 4. Modes of rock slope failure. (a) plane failure, (b) wedge failure (modified from Norrish and Wyllie, 1996).

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Fig. 5. Location of study area and picture of the rock slope in the study area.

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Fig. 6. Acquisition process of discontinuity orientation data. (a) picture of the rock slope, (b) selected points from the point cloud, (c) generated plane data from point cloud.

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Fig. 7. Stereonet plots of data. (a) all discontinuity data, (b) three joint sets.

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Fig. 8. Results of probabilistic analysis for plane failure using randomly generated discontinuity orientation using Fisher distribution function. (a) joint1, (b) joint2, (c) joint3.

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Fig. 9. Results of probabilistic analysis for wedge failure using randomly generated discontinuity orientation using Fisher distribution function. (a) joint1&joint2, (b) joint1&joint3, (c) joint2&joint3.

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Fig. 10. Results of probabilistic analysis for plane failure using real discontinuity orientation data. (a) joint1, (b) joint2, (c) joint3.

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Fig. 11. Results of probabilistic analysis for wedge failure using real discontinuity orientation data. (a) joint1&joint2, (b) joint1&joint3, (c) joint2&joint3.

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Fig. 12. Results of deterministic analysis using representative discontinuity orientation data. (a) plane failure, (b) wedge failure.

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Fig. 2. (a) picture of the rock slope in the study area, (b) point cloud acquired using terrestrial LiDAR, (c) occlusion area of slope face.

Table 1. Specifications of terrestrial LiDAR that used in this study

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Table 2. Representative geometrical properties of discontinuity sets

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Table 3. Kinematic analysis result of deterministic analysis and probabilistic analysis and using original data

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Acknowledgement

Supported by : 한국연구재단

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