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A dynamic multi-agent approach for modeling the evolution of multi-hazard accident scenarios in chemical plants

机译：一种用于建模化工厂多灾害事故情景演变的动态多智能探测方法

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摘要

In the chemical industry, multi-hazard (toxic, flammable, and explosive) materials such as acrylonitrile are stored, transported, and processed in large quantities. A release of multi-hazard materials can simultaneously or sequentially lead to acute toxicity, fire and explosion. The spatial-temporal evolution of hazards may also result in cascading effects. In this study, a dynamic methodology called "Dynamic Graph Monte Carlo" (DGMC) is developed to model the evolution of multi-hazard accident scenarios and assess the vulnerability of humans and installations exposed to such hazards. In the DGMC model, chemical plants are modeled as a multi-agent system with three kinds of agents: hazardous installations, ignition sources, and humans while considering the uncertainties and interdependencies among the agents and their impacts on the evolution of hazards and possible escalation effects. A case study is analyzed using the DGMC methodology, demonstrating that the risk can be underestimated if the spatial-temporal evolution of multi-hazard scenarios is neglected. Vapor cloud explosion (VCEs) may lead to more severe damage than fire, and the safety distances which are implemented only based on fire hazards are not sufficient to prevent from the damage of VCEs.
机译：在化学工业中，多危害（毒性，易燃和爆炸性）材料，如丙烯腈，以大量储存，运输和加工。多危害材料的释放可以同时或依次导致急性毒性，火和爆炸。危险的空间演化也可能导致级联效果。在这项研究中，开发了一种称为“动态图形蒙特卡罗”（DGMC）的动态方法，以模拟多灾害事故情景的演变，并评估暴露于这种危害的人类和装置的脆弱性。在DGMC模型中，化学植物被建模为具有三种代理的多助理系统：危险设施，点火源和人类，同时考虑代理人的不确定性和相互依赖性及其对危害的演变和可能的升级效果的影响。使用DGMC方法分析一种案例研究，证明风险可以低估如果忽略了多危害情景的空间演化。蒸汽云爆炸（VCE）可能导致比火更严重的损坏，并且仅基于火灾危害实施的安全距离不足以防止导航的损坏。

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