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The hazardous nature of the chemical materials is of significant concern in the economic viability of rail transportation globally. The potential risks of these materials to cause severe health impairments and catastrophic accidents have been widely studied and reported. Moreover, several models have been employed for assessing the risks associated with transporting hazardous materials by rail. However, a more holistic, quantitative, and robust model should incorporate more potential risk-triggered criteria, especially those causing severe health loss and devastating consequences like vapor cloud explosion. This study develops a risk assessment model by incorporating potential health risk factors and the obstacle circumstances. The potential risk factors are population density, route distance from residential areas, and the availability of sensitive third parties for health consequences. The proposed model utilizes Bayesian networks for causality modeling of the material release scenarios and fuzzy set theory for estimating the health effects and severity impact coefficient. Finally, individual risk curves and safe distances from the railway are developed. A real rail system for gasoline transportation in Tehran is investigated to evaluate the model’s effectiveness. The study provides panoramic leverages for risk-managed decision-making for safely transporting hazardous material by rail.

Quantitative Risk Analysis on Rail Transportation of Hazardous Materials