Cause Mechanism of Metro Collapse Accident Based on Risk Coupling

Fang, Ming; Zhang, Yi; Zhu, Ming–Sheng; Chen, Shaopei

doi:10.3390/ijerph19042102

Cited by 14 publications

(5 citation statements)

References 16 publications

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“…In recent years, this issue has attracted more and more attention. To scientifically analyze the key causal factors of existing metro collapse accidents and their interaction coupling mechanism, Fang constructed the FTA-24 Model accident cause analysis framework based on the Fault Tree Analysis and Behavioral Safety "2-4" Model, combining their respective characteristics [21]. Fu established a general risk interaction modeling and analysis procedure based on association rule mining and weighted network theory and studied the interaction between the safety risks of metro-deep foundation pit projects with China as an example [22].…”

Section: Metro Construction Safety Risksmentioning

confidence: 99%

Study on the Mechanism of Safety Risk Propagation in Subway Construction Projects

Han,

Shen,

Zhu

et al. 2024

Sustainability

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Under the development trend of complexity and systematization of metro construction, there is an increasing number of risk factors potentially affecting construction safety, which has led to frequent accidents in metro construction projects, and the road to high-quality and sustainable development of metro construction is full of challenges. One of the essential reasons is that the propagation mechanism of safety risk factors in metro construction under hidden and delayed effects is not yet clear. This paper combines the theory of complex network and propagation dynamics and constructs a subway construction safety risk propagation model based on considering the hidden and delayed characteristics of construction safety risk propagation, which reveals the dynamic propagation law of subway construction safety risk and puts forward feasible coping strategies. The findings evince that the delay time T significantly affects the propagation behavior of risk and the achievement of the equilibrium state in the network. The transmissibility of the risk factor within the hidden state holds a pivotal sway over the entirety of risk propagation, and the latency in transmission significantly expedites the propagation of risk throughout the network. It is recommended that project managers monitor and warn safety state nodes and hidden state nodes to block the spread of risk in the network and control the delay time of risk in the network in time to reduce the probability of risk occurrence. This study significantly promotes the resilient management of safety risks in metro construction.

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Section: Metro Construction Safety Risksmentioning

confidence: 99%

Study on the Mechanism of Safety Risk Propagation in Subway Construction Projects

Han,

Shen,

Zhu

et al. 2024

Sustainability

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show abstract

“…Through further summary, 24Model and functional resonance analysis method (FRAM) both believe that the accident‐causation factors include human factors, physical factors, organizational factors, and organizational external factors and demonstrate that these factors interact and relate (Huang, Yin et al., 2022). The vast majority of safety management theories regard risk as an important component in the formation of accident causes, implying that the interaction and diversity of accident causes emphasize the existence of risk coupling effects (Fang et al., 2022; Huang, Yin et al., 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

Risk coupling analysis under accident scenario evolution: A methodological construct and application

Yao,

Zhang,

Wang

et al. 2023

Risk Analysis

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Dynamic processes in various fields exhibit risk coupling phenomena, but existing risk analysis studies tend to ignore the risk coupling effects of dynamic scenarios. Considering the principles of digitization, objective quantification, and the full process that should be adopted in the risk coupling analysis, an integrated risk coupling analysis framework is proposed. Specifically, the weighted Eclat algorithm is used to mine the risk association rules, then the key risk factors are extracted by social network analysis, and the stochastic Petri net is used to complete the construction, simulation, and evolution of accident scenarios. This universal framework can analyze the risk phenomena of accident scenario evolution in a process‐oriented manner and decouple risks based on key risk factors and disconnect the chain of the accident scenario evolution process. Finally, the proposed framework is applied to the coupled analysis of fire risk in Chinese urban communities to verify its feasibility and scientific validity.

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“…Fault tree analysis (FTA) is a logical directed graph from result to cause. It can analyze the causes of accidents [23][24][25]. It is assumed that X i and T represent the variables of basic events and top events, and 0 or 1 can be taken to represent the occurrence and non-occurrence of events, respectively.…”

Section: The Fault Tree and Bayesian Network 231 Basic Principles Of ...mentioning

confidence: 99%

A Coupled Mathematical Model of the Dissemination Route of Short-Term Fund-Raising Fraud

Shan

Wang

et al. 2022

Mathematics

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To effectively protect citizens’ property from the infringement of fund-raising fraud, it is necessary to investigate the dissemination, identification, and causation of fund-raising fraud. In this study, the Susceptible Infected Recovered (SIR) model, Back-Propagation (BP) neural network, Fault tree, and Bayesian network were used to analyze the dissemination, identification, and causation of fund-raising fraud. Firstly, relevant data about fund-raising fraud were collected from residents in the same area via a questionnaire survey. Secondly, the SIR model was used to simulate the dissemination of victims, susceptibles, alerts, and fraud amount; the BP neural network was used to identify the data of financial fraud and change the accuracy of the number analysis of neurons and hidden layers; the fault-tree model and the Bayesian network model were employed to analyze the causation and importance of basic events. Finally, the security measures of fund-raising fraud were simulated by changing the dissemination parameters. The results show that (1) for the spread of the scam, the scale of the victims expands sharply with the increase of the fraud cycle, and the victims of the final fraud cycle account for 12.5% of people in the region; (2) for the source of infection of the scam, the initial recognition rate of fraud by the BP neural network varies from 90.9% to 93.9%; (3) for the victims of the scam, reducing fraud publicity, improving risk awareness, and strengthening fraud supervision can effectively reduce the probability of fraud; and (4) reducing the fraud rate can reduce the number of victims and delay the outbreak time. Improving the alert rate can reduce victims on a large scale. Strengthening supervision can restrict the scale of victims and prolong the duration of fraud.

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Cause Mechanism of Metro Collapse Accident Based on Risk Coupling

Cited by 14 publications

References 16 publications

Study on the Mechanism of Safety Risk Propagation in Subway Construction Projects

Study on the Mechanism of Safety Risk Propagation in Subway Construction Projects

Risk coupling analysis under accident scenario evolution: A methodological construct and application

A Coupled Mathematical Model of the Dissemination Route of Short-Term Fund-Raising Fraud

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