The first objective of this research is to develop a âStorage Hazard Factorâ (SHF) to evaluate and rank the inherent hazards of chemicals stored in logistic warehouses. In the factor calculation, the inherent hazard of chemicals is determined by various parameters (e.g., the NFPA rating, the flammability limit, and the protective action criteria values, etc.) and validated by the comparison with other indices. The current criteria for flammable hazard ratings are based on flash point, which is proved to be insufficient. Two machine learning based methods will be used for the classification of liquid flammability considering aerosolization based on DIPPR 801 database. Subsequently, SHF and other warehouse safety penalty factors (e.g., the quantity of the chemicals, the distance to the nearest fire department, etc.) are utilized to identify the Logistic Warehouse Hazard Index (LWHI) of the facilities. Last but not least, this method is applied to real-time data from Houston Chronicle, and several statistical analyses are used to prove the hazard index is helpful for hazard identification to emergency responders and hazard communication to the public.
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