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عنوان انگلیسی مقاله:
Risk assessment and management via multi-source information fusion for undersea tunnel construction
ترجمه فارسی عنوان مقاله:
ارزیابی و مدیریت ریسک از طریق تلفیق اطلاعات چند منبع برای ساخت تونل زیر زمینی
Sciencedirect - Elsevier - Automation in Construction, 111 (2020) 103050. doi:10.1016/j.autcon.2019.103050
Hong Zhoua,⁎, Yinghui Zhaob, Qiang Shenb, Liu Yangc, Hubo Caid
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.
Keywords: Undersea tunnel construction | Multi-source information fusion | Construction risk | D-S evidence theory | Fuzzy matter element