An Integrated Quantitative Risk Assessment Method for Urban Underground Utility Tunnels
Introduction
Urban utility tunnels (UUTs) are widely-used underground facilities in European countries and Japan for many years [1]. In the past few years, the rapid urbanization in China has greatly promoted the construction of UUTs, and the total length of which has increased remarkably since being encouraged by the Chinese government in 2015 [2]. Compared with the UUTs in Europe or Japan, those in China are more complex which contain most of city ‘lifelines’ such as gas pipelines, heat pipelines, water supply systems, sewer systems, electricity, and telecommunication cables. An allowable design of a utility tunnel prototype based on ‘Chinese Technical Code for Urban Utility Tunnel Engineering’ is illustrated in Fig. 1 [3].
UUTs integrate various city lifelines in the underground space, with extra operation space for workers to install, inspect and maintain [4]. As a result, there is no need to frequently excavate roads, which may cause inconvenience of city life. However, as the UUTs contain several high-risk pipelines (particularly the gas pipeline) in an adjacent and small compartment, it is likely to cause serious coupling accidents, which could result in catastrophic casualties, economic losses and social impacts. Over the past few years, several serious lifeline accidents (gas pipeline, sewer pipeline, and heat pipeline) happened in China [5]. In Qingdao City, 2013, an explosion of gas pipeline resulted in 62 deaths; in Taiwan, 2014, a gas pipeline leakage caused a serious successive explosion resulting in more than 300 casualties and 3 roads hardly damaged; recently, in Guizhou province, a serious landslide led to the natural gas pipeline ruptured and then arose a serious explosion which resulted in 45 casualties. In the UUTs, the high-risk pipelines are possible to initiate a serious accident, and they may easily make coupling accidents because of the escalated impact of the domino effects [6]. Therefore, it is essential to put forward a comprehensive risk assessment model to analyze the risk of UUTs and provide appropriate technical supports to make risk-based emergency management.
The UUTs are newly emerging urban facility, and there are currently just a few research achievements on utility tunnel. The research work has mainly focused on utility tunnel operation management (regular operation, maintenance and inspection) and optimal structure framework design. How to conduct land-use planning for utility tunnel on multiple criteria (finance, safety, environment, convenience) is analyzed [7], [8], [9]. Several researchers have reviewed the development of utility tunnels from different countries [10]. More recently, Building Information Modeling (BIM) has been used to support the maintenance and operation of UUTs [11]. For the safety assessment and management of utility tunnels, some research has been done to identify the UUT hazards and the potential accidents [12], [13], [14], [15], [16], to simulate the gas leakage in UUTs [17], [18], [19], and to examine the influence of crustal movement (earthquake) on their structure stability [20,21]. However, comprehensive and quantitative studies for risk assessment of utility tunnel are still scarce, especially for the newly emerging complex underground utility tunnels in China.
In the past few years, although the studies of the comprehensive risk analysis of underground utility tunnels are rare, there has been much research on risk assessment of oil and gas pipeline, water supply pipeline, sewer system, or electricity lines [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32]. These researches on pipeline risks could also provide technical supports for the risk analysis of utility tunnel accident. However, the conventional risk analysis methods such as fault tree are static with only binary states, which are often insufficient to make a comprehensive accident description and risk analysis. Furthermore, most UUT accident scenarios are dynamic with randomness and vagueness, and may involve secondary disasters due to domino effects. Compared with traditional risk analysis methods, Bayesian network (BN) is a promising technique that can incorporate uncertainties during the accident evolvement, perform probability updating given evidence, and handle multi-state variables [33,34]. Moreover, it can well demonstrate and assess accidents with secondary and derivative disasters due to domino effects [35], [36], [37], [38], [39].
In this study, an integrated risk assessment method based on Dynamic Hazard Scenarios Identification (DHSI), Bayesian network (BN) and risk analysis is proposed to evaluate and manage the safety of underground utility tunnel. DHSI is used to identify the worst-case scenario of utility tunnel accident, which may be initiated by gas leakage, sewer pipeline damage, heat pipeline failure or fire of wires and cables. Bayesian network is built based on the identified worst-case accident scenario. Risk analysis is calculated according to BN results. The proposed framework for risk assessment of UUTs could be helpful for the prevention and mitigation of utility tunnel accident and city land-use planning.
Section snippets
Methodology
The proposed framework for the integrated quantitative risk assessment of UUTs was illustrated in Fig. 2.
Application
In this section, the proposed methodology is applied to analyze a real UUT accident which includes several accident scenarios involving domino effects. Based on the BN-based model, the impact of emergency rescue and safety measures are evaluated, and the risk of accident consequences are also estimated.
Results and discussion
UUT accidents are complicated and may result in various consequences. In this section, we mainly discuss three typical UUT accident scenarios to demonstrate the application of the proposed BN-based method. The setting states of the parent nodes of these three accident scenarios are listed in Table 5 (the * means this node will change to each state for comparison). The first accident scenario is aiming at estimating the expected risk of utility tunnel accidents among different surroundings. The
Conclusion
In this paper, an integrated quantitative risk assessment method for urban underground utility tunnel was proposed based on the Bayesian network. The worst-case accident scenario was identified through dynamic hazard scenario identification (DHSI) and the escalated domino effects were taken into account during the establishment of the Bayesian network. The accident initiated by the gas pipeline leakage was identified as the worst-case accident scenario, and a 23-node Bayesian network of UUTs
CRediT authorship contribution statement
Jiansong Wu: Conceptualization, Methodology, Writing – original draft, Funding acquisition, Supervision. Yiping Bai: Visualization, Writing – original draft. Weipeng Fang: Software, Writing – original draft. Rui Zhou: Data curtion. Genserik Reniers: Formal analysis, Writing – review & editing. Nima Khakzad: Methodology, Writing – review & editing.
Declaration of Competing Interest
The authors declared no conflicts of interest with respect to the publication of this article.
Acknowledgements
This work was supported by the National Key Research and Development Program of China (Grant No. 2017YFC0805001), Beijing Nova Program (Grant No. Z201100006820072), the opening project of State Key Laboratory of Explosion Science and Technology (Grant No. KFJJ19–09 M) and the Yue Qi Young Scholar Program of China University of Mining & Technology, Beijing.
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