Quantifying the evolution of settlement risk for surrounding environments in underground construction via complex network analysis
Introduction
In accordance with the rapid development of urbanization, an increasing number of underground facilities, such as underground transportation infrastructures, has been developed in city-intensive areas (Qian, 2016). However, due to uncertain risks caused by excavation, underground construction inevitably causes damage to surrounding environments (i.e., adjacent buildings) (Castaldo et al., 2018, Li et al., 2018b, Zhou and Ding, 2017). For example, a significant change in soil stress causes settlement of adjacent buildings (Zhou and Ding, 2017). Other safety issues, such as cracks or collapses of adjacent structures and leakage or broken underground pipelines, are secondary risks induced by settlement (Castaldo et al., 2018). These surrounding environment risks will probably destroy the normal life of citizens or even affect public safety. Thus, evaluating and controlling settlement are considered crucial parts during underground construction in case of additional damages (Aye et al., 2006).
A plethora of studies has been undertaken to evaluate the risk of surrounding environments during underground construction (Fang et al., 2014, Kung et al., 2007). However, regardless of the type of settlement analysis methods, final risk assessments are established based on comparison of observed settlement value and thresholds (standards or designed requirements). These threshold-based methods demonstrate some limitations: (1) Considering accumulated settlement with threshold as the only indicator to represent risk level is inaccurate. In practice, points with settlement value exceeding threshold may be less risky than those below the threshold and vice versa (Zhou et al., 2018a). (2) Determining different monitoring points through a unified threshold lacks reasonability (Ding et al., 2013). For example, the same settlement values may result in larger settlement risk to high-density areas than that in low-density one (Li et al., 2019). (3) Simple threshold comparison could merely offer risk levels of individual points but fails to provide overall risk of the construction sites and quantitative risk evolution process. In practical construction management, determining the magnitude, time, and location of risk is urgently needed to timely consider appropriate measures to prevent damages on surrounding environment.
In summary, the “root cause” of the aforementioned limitations is that current methods are unable to assess settlement risks of surrounding environment from a systematic perspective. Moreover, underground construction is such a complicated system with various uncertainties in hydrogeological conditions and high-nonlinear interactions in risk mechanism (Bryn et al., 2017). Uncovering the dynamic and temporal evolution process of settlement risk by analytical representation method is difficult (Zhou et al., 2018a). Therefore, exploring an effective approach to assess settlement risk of surrounding environments in terms of dynamic and systematic aspects has a practical importance.
Complex network theory, which has been successfully developed in many fields to evaluate risk (such as stock market), has potential values in settlement analysis of surrounding environment (Wang et al., 2017). Topological properties of data-based network are used for capturing system dynamic evolution of complex system (Zanin et al., 2016). Thus, a data-based complex network approach is developed to analyze and evaluate risks of surrounding environments from a synthetic and dynamic perspective to address the aforementioned limitations. The goals of the current research are twofold: (1) to propose a new insight into settlement risk evaluation by overall risk assessment indicators; (2) to quantify the evolution of settlement risk (including spatial distributions and temporal features) for the surrounding environment to guide construction decisions in terms of topological structure. The surrounding environments refer to adjacent buildings and surrounding ground surface to limit the scope of the current research. A case of Wuhan metro project in China is used to verify the effectiveness and feasibility of the proposed approach.
This paper is organized as follows. Section 2 briefly reviews studies on settlement risks of surrounding environment in underground construction. Section 3 lists the methodology framework of the proposed method. Section 4 provides a deep excavation case study of the metro station project in the Wuhan Metro network in China to validate the feasibility. Section 5 presents a comprehensive discussion of the potential value in practice of the proposed approach in the risk assessment of surrounding environments. Finally, Section 6 summarizes the research work and proposes a prospect of further study.
Section snippets
Risk behaviors and complex safety factor of surrounding environment in underground construction
Underground construction inevitably poses a threat to surrounding environments at times, like cracks of municipal pipelines or collapse of nearby facilities. In 2008, almost 11 people died and three nearby buildings collapsed during construction of Hangzhou Metro by excessive excavation and weak support system (Jiang, 2012), as shown in Fig. 1a). Similarly in 2018, groundwater leakage caused a road cave-in with a hole (50 m long and 30 m wide) among Guangzhou Metro construction, which severely
Complex network framework for tracking settlement dynamics
The framework of the proposed method comprises three key parts, and the specific procedures are listed as follows (Fig. 2):
- (1)
Data preparation: Settlement monitoring data of different points must be collected and processed. Time window is mainly adopted to divide massive data into piles of small-scale settlement time series. The slide time window moves forward with a fixed step throughout underground construction (Rubinov et al., 2010). With the comparisons of multiple time series based network
Project overview
Zhuyeshan Station, a case of Wuhan Metro project in China, is used to evaluate the feasibility and effectiveness of the proposed approach. Zhuyeshan Station is a three-story underground structure with excavation face of approximately 220 m long, 42 m wide, and 20 m deep. And the retaining wall of the foundation pit is made of the diaphragm wall (800 mm thick) and inner support system. The surrounding facilities are rather complex including a railway- line on the north, an overpass on the east,
Risk assessment with deep excavation time windows
The relative risk values of settlement network in each time window are shown by the risk evolution graph to explore the temporal evolution of risk. The high-risk time period throughout the entire construction process is presented in Fig. 12. According to expert experience, the threshold of the relative risk values () for high risk is 0.6. Therefore, as shown in Fig. 12, the surrounding environment risk inevitably changes with construction progress, from which the temporal evolution of
Conclusion
In this research, a data-based complex network approach is developed to analyze and assess risks of surrounding environments due to underground construction. The developed approach comprises the following three parts: (1) network presentation, (2) network optimization, and (3) risk assessment based on topological structures. In the case of Wuhan Metro project, the new approach has successfully identified the key spot in four accidents and be clearly figured out by risk distribution map while
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgment
This research is supported by China’s National Natural Science Foundation under Grant Nos. (71671072, 71732001 and 71827001). The study is also supported in part by the National Key R&D Program of China (No. 2018YFB1306905). Thank you for the support from Wuhan Metro Group Co., Ltd.
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