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

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.