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Agent-based modeling methodology and temporal simulation for Natech events in chemical clusters

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  • Zhou, Lixing
  • Chen, Guohua
  • Zheng, Mianbin
  • Gao, Xiaoming
  • Luo, Chennan
  • Rao, Xiaohui

Abstract

In chemical clusters, technological accidents triggered by natural events (Natech events) can lead to the failure of large number of units and cause catastrophic consequences. Previous studies on Natech events give primary concerns on the static analysis at small-scale region with few thoughts the impact of various safety barriers. From the perspective of the large-scale region and temporal characteristics, an agent-based modeling methodology is proposed to present the dynamic evolution process. All the units associated with the evolution are divided into natural hazard agent, hazard-affected facility agent, safety barrier agent, and escalation factor agent to reduce the computational complexity. The time-dependent state transition mechanism of each agent is analyzed to represent the evolution process, simultaneously, the temporal effect of natural hazards, safety barrier and multi escalation factors is considered by utilization of time steps. Moreover, Monte Carlo simulation is adopted to quantify the uncertainties accompanying an accident evolution. The proposed methodology is demonstrated on a complex chemical system in the large-scale region. The results of simulation show that the number of failed hazard-affected facilities in the Natech events scenario will cyclically increase and keep constant, with strong temporal characteristic. The intensity of natural hazards and the probability of failure of safety barriers make a big impact on the temporal characteristic. The results are valuable to support natural hazard prevention in chemical cluster.

Suggested Citation

  • Zhou, Lixing & Chen, Guohua & Zheng, Mianbin & Gao, Xiaoming & Luo, Chennan & Rao, Xiaohui, 2024. "Agent-based modeling methodology and temporal simulation for Natech events in chemical clusters," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:reensy:v:243:y:2024:i:c:s0951832023008025
    DOI: 10.1016/j.ress.2023.109888
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    References listed on IDEAS

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