4.7 Article

Risk assessment and management via multi-source information fusion for undersea tunnel construction

Journal

AUTOMATION IN CONSTRUCTION
Volume 111, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.autcon.2019.103050

Keywords

Undersea tunnel construction; Multi-source information fusion; Construction risk; D-S evidence theory; Fuzzy matter element

Funding

  1. National Natural Science Foundation of China [71871192]
  2. China Railway South Investment Group Co. LTD.
  3. Xiamen Engineering Technology Center for Intelligent Maintenance of Infrastructures [TCIMI201802]
  4. Major Science and Technology Planning 2016 Xiamen Metro No. 3 Line Undersea Tunnel Construction Risk Integrated Control and System Development

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The construction of undersea tunnels is an extremely risky endeavor that is vulnerable to water seepage and gushing due to the high water pressure, complex geological conditions, and pore water trapped in unstable rocks. This risk can lead to the collapse of tunnels under construction and disastrous consequences of fatalities and injuries as well as project delays and financial losses. The current risk management practices for tunnel construction projects in China are static and rely on the subjective judgement of experts and practitioners and do not incorporate real-time monitoring data during the construction process at this time. This paper presents a new method and system to assess and manage the risks during the construction process by coupling the risk management system and the quality management system and integrating jobsite monitoring data, design data, and environmental data. In this new method and system, the risk factors are categorized into (hu)man, material, machine, method, and environment, or 4M1E, and are quantitatively measured. The Dempster-Shaffer (D-S) theory was adopted in this method to both fuse the 4M1E data and to compute the aggregate risk index. This new method and system was tested during the Xiamen Metro Line No. 3 project when a shield machine cutter accident occurred. The results show that, before the accident, the individual risk measures In all five dimensions (4M1E) and the aggregate risk index were extremely high, which clearly illustrated the feasibility and capability of the newly developed method and system.

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