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Citation |
Zeng L, Gao J, Wang Q, Chang L. Risk Anal. 2018; 38(11): 2379-2399. |
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Affiliation |
School of Mechanical Engineering, Tongji University, Shanghai, China. |
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Copyright |
(Copyright © 2018, Society for Risk Analysis, Publisher John Wiley and Sons) |
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DOI |
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PMID |
29975988 |
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Abstract |
The release of toxic airborne contaminants resulting from terrorist attacks on buildings can lead to disastrous consequences. To evaluate and reduce the effects of these emergencies, various methods and models have been developed in the past few years. Such work has provided effective tools for the building management system to do risk assessment of the contaminated areas. Although risk analysis methods to describe the contaminant dispersion scenarios made significant progress, these approaches did not generally consider the releasing scenario occurring in the ventilation system and the effect of human behavior during the developing process of an emergency event. Emergency strategies chosen by the decisionmaker are not always associated with the early-warning system, such as the sensor monitoring network and the source identification system inside the building. This study aims to provide a risk assessment model considering both the variation of contaminant concentration and occupant distribution after the release of toxic agents to obtain the exposure risk for people indoors. The contaminant dispersion is simulated using computational fluid dynamics. The evacuation process for people is modeled using Pathfinder, and the exposure risk for occupants under various emergency strategies is calculated using the efficiency factor of the contaminant source. The results of the exposure risk for 40 basic cases are discussed, and the optimal ventilation mode for these specific cases is recommended. Next, the impact of the variation of human behavior, contaminant detection time needed by sensors, and source identification time needed by inverse modeling on the exposure risk for people indoor is studied. The uncertainty and reproducibility of the numerical simulations are emphatically discussed in the Supporting Information. Language: en |
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Keywords |
Airborne contaminant; emergency ventilation; evacuation model; exposure risk |