Risk management of deep excavation is always an important issue. One of the core problems is to accurately simulate and predict the time series of displacement collected from the site sensors to monitor the risk variation. Meanwhile, the applications of building information modelling (BIM) and geographic information system (GIS) can integrate the construction structures into the surrounding environment, visualizing various information and supporting decision making for risk treatment. Therefore, this paper proposes a risk management system to monitor the risk variation for deep excavation based on optimized grey Verhulst model (GVMm), BIM-3DGIS framework and risk monitoring. The grey Verhulst model (GVM) has demonstrated well performance on saturation curve, such as displacement of deep excavation. This paper establishes the GVMm by improving GVM to predict the displacement more precisely. BIM-3DGIS framework is also built by integrating BIM and 3DGIS in the application level for the efficiency of system operation and the interaction with the risk management platform. BIM-3DGIS framework, working with the risk management platform, can monitor the risk variation of deep excavation effectively and provide visual decision-making supports. A real case of deep excavation is used as an illustrative example to verify the practicability. The results show that the prediction precision of GVMm is better than that of GVM. The application scenarios also demonstrate the effectiveness of the risk management system.


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    Titel :

    A Risk Management System for Deep Excavation Based on BIM-3DGIS Framework and Optimized Grey Verhulst Model


    Weitere Titelangaben:

    KSCE J Civ Eng


    Beteiligte:
    Lee, Pin-Chan (Autor:in) / Zheng, Li-Long (Autor:in) / Lo, Tzu-Ping (Autor:in) / Long, Dan-Bing (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2020-03-01


    Format / Umfang :

    12 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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