Rockfall is a major geological disaster that frequently occurs on rock slopes in alpine and gorge regions and poses a significant threat to life and property in areas exposed to rockfall hazards. In this study, a methodology is presented for comprehensive rockfall hazard analysis, including data acquisition, source identification, numerical simulation, quantitative assessment and mitigation evaluation. A high-precision and high-resolution digital terrain model (DTM) is generated based on the point cloud data obtained by terrestrial laser scanning (TLS) and is utilized for rockfall simulation and automatic identification of structural planes. The model parameters are calibrated by three-dimensional (3D) back analysis, and the rockfall motion is simulated based on a probabilistic model and an energy dissipation model. Rockfall mitigation under passive protection is evaluated according to the rockfall interception ratio (RIR), hazard reduction rate (HRR) and statistics of the rockfall characteristics and hazards within the rockfall threat area. Under the influence of construction excavation, the diversion tunnel inlet slope of Jinchuan Hydropower Station has suffered from a series of rockfall events and potential overall instability, which has become a great threat to the construction personnel, equipment and vehicles below the slope. Thus, the presented methodology is applied to thoroughly study the example case of the rockfall events at the inlet slope of the diversion tunnel of Jinchuan Hydropower Station. The advantages, limitations and notes of each link of the presented methodology are discussed, and the suggestion of strengthening the cracked area with integral active support is proposed.


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    Title :

    Risk Assessment and Mitigation Evaluation for Rockfall Hazards at the Diversion Tunnel Inlet Slope of Jinchuan Hydropower Station by Using Three-dimensional Terrestrial Scanning Technology


    Additional title:

    KSCE J Civ Eng


    Contributors:
    Xia, Mao-pu (author) / Li, Hai-bo (author) / Jiang, Nan (author) / Chen, Jun-lin (author) / Zhou, Jia-wen (author)

    Published in:

    Publication date :

    2023-01-01


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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