{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/44063"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/44063","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Evacuation of Special Facilities","abstract":"In this research, the issue of evacuating people from large public facilities has been studied. The focus has mostly been on the evacuation of hospitals. For the hospital evacuation planner, it is necessary to know how long it would take to evacuate the premises. To approach this problem, the entire evacuation process has been modeled as a queuing situation using a simulation language called SLAM. The evacuation time is affected by many variables such as the number of elevators in the building, the number of ambulances available to transport patients, and the number of staff available to assist in moving patients. All these variables have been incorporated in the model as servers of the queuing process and the simulation is carried out. The model has been applied to a case study of the evacuation of the Medical College of Virginia Hospitals in Richmond, VA. The sensitivity of the model to different system parameters has been studied and the relationships have been plotted.","abstract_html":"In this research, the issue of evacuating people from large public facilities has been studied. The focus has mostly been on the evacuation of hospitals. For the hospital evacuation planner, it is necessary to know how long it would take to evacuate the premises. To approach this problem, the entire evacuation process has been modeled as a queuing situation using a simulation language called SLAM. The evacuation time is affected by many variables such as the number of elevators in the building, the number of ambulances available to transport patients, and the number of staff available to assist in moving patients. All these variables have been incorporated in the model as servers of the queuing process and the simulation is carried out. The model has been applied to a case study of the evacuation of the Medical College of Virginia Hospitals in Richmond, VA. 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