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Local geometric information and discontinuity features are key aspects of the analysis of the evolution and failure mechanisms of unstable rock blocks in rock tunnels. This study demonstrates the integration of terrestrial laser scanning (TLS) with distinct element method for rock mass characterization and stability analysis in tunnels. TLS records detailed geometric information of the surrounding rock mass by scanning and collecting the positions of millions of rock surface points without contact. By conducting a fuzzy K-means method, a discontinuity automatic identification algorithm was developed, and a method for obtaining the geometric parameters of discontinuities was proposed. This method permits the user to visually identify each discontinuity and acquire its spatial distribution features (e.g. occurrences, spacings, trace lengths) in great detail. Compared with hand mapping in conventional geotechnical surveys, the geometric information of discontinuities obtained by this approach is more accurate and the identification is more efficient. Then, a discrete fracture network with the same statistical characteristics as the actual discontinuities was generated with the distinct element method, and a representative numerical model of the jointed surrounding rock mass was established. By means of numerical simulation, potential unstable rock blocks were assessed, and failure mechanisms were analyzed. This method was applied to detection and assessment of unstable rock blocks in the spillway and sand flushing tunnel of the Hongshiyan hydropower project after a collapse. The results show that the noncontact detection of blocks was more labor-saving with lower safety risks compared with manual surveys, and the stability assessment was more reliable since the numerical model built by this method was more consistent with the distribution characteristics of actual joints. This study can provide a reference for geological survey and unstable rock block hazard mitigation in tunnels subjected to complex geology and active rockfalls.
Wang et al. (Thu,) studied this question.