Modeling and Simulation of Crowd Evacuations in Toxic Environments by Considering the Impact of Dosage
Abstract
In the event that control of process safety risk is lost, the effectiveness of mitigation barriers is paramount in reducing the consequences. When it results in an event such as a toxic gas release, a mitigation barrier that is present when humans are involved is emergency evacuation. The evacuation process is affected by various factors in such situations, which includes any physiological effects caused by exposure to the toxic gas. These symptoms have the potential to affect how humans make decisions or their ability to self-rescue. This presents a need for evacuation simulation approaches that account for toxic exposure effects in order to assist in the assessment of consequences in such scenarios.
This work involves the implementation of a dosage-based evacuation effects model based on the Toxic Load, which is an indicator of toxic injury. This level of toxic injury determines how fast or slow evacuating agents move compared to their desired evacuation speed. An algorithm that calculates the dosage accumulation rate depending on exposure time and concentration was implemented to determine the Toxic Load.
An advanced evacuation simulator, FDS+Evac, was modified to facilitate the implementation of the dosage effects model. A case study on a realistic building geometry was carried out, showing how the evacuation patterns of 30 people varied as a function of hydrogen sulfide concentration. The study showed that the typical results that come out of evacuation simulations (such as evacuation time) are not sufficient indicators of risk. Therefore, a contour plotting approach was developed to provide insights on consequences (such as toxic injury) as well as plausible solutions to reduce aforementioned consequences. The contour plotting approach allows more effective planning of emergency response, as well as building design.
Citation
Adia, Neil Alvin Bacal (2020). Modeling and Simulation of Crowd Evacuations in Toxic Environments by Considering the Impact of Dosage. Master's thesis, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /189539.