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Dynamic coupling risk assessment model of utility tunnels based on multimethod fusion

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  • Hai, Nan
  • Gong, Daqing
  • Liu, Shifeng
  • Dai, Zixuan

Abstract

Accidents in utility tunnels are usually caused by coupling multifactor risks, and ignoring the coupled risks can lead to biased estimates of the actual risk threats and losses. However, there are complex types of risks and coupling relationships within utility tunnels, which clarifies the coupling relationships between various types of risks and improves the accuracy of the assessment model to fit in reality. Therefore, this paper simulates the evolution process of utility tunnel risks based on the latent Dirichlet allocation algorithm, the NK model and the system dynamics to realize unbiased and accurate estimates. First, the risk factors are analyzed and classified using the latent Dirichlet allocation, and the coupling relationship is screened for employing the NK model. As a result, a system dynamics simulation model is established to determine the key risk coupling factors with the greatest impact on utility tunnels. Finally, a case study is given to illustrate the practicality and effectiveness of the model. The results show that the changes in utility tunnel risk coupling relationship can effectively characterize the changes in the dynamic risk of the utility tunnel. Moreover, the results can also be used to determine the coupling relationship that has the greatest influence on utility tunnels.

Suggested Citation

  • Hai, Nan & Gong, Daqing & Liu, Shifeng & Dai, Zixuan, 2022. "Dynamic coupling risk assessment model of utility tunnels based on multimethod fusion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:reensy:v:228:y:2022:i:c:s0951832022003969
    DOI: 10.1016/j.ress.2022.108773
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    1. Xue, Gang & Liu, Shifeng & Ren, Long & Gong, Daqing, 2024. "Risk assessment of utility tunnels through risk interaction-based deep learning," Reliability Engineering and System Safety, Elsevier, vol. 241(C).

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