Evacuation analysis of passenger ships is mandatory since June 2016 for all passenger ships as prescribed by the International Maritime Organisation (IMO) in the revised guidelines for evacuation analysis (MSC.Circ.1533). The advanced evacuation analysis defined in the IMO guidelines, relies on the usage of computer models to simulate the movement of people and their interactions with the environment and the other evacuees. These models are powerful tools which allow for a detailed representation of theEnvironment and the people specific characteristics and behaviour. Setting up and running simulations is a very time consuming process and the bigger and more complex the ship or building is, the longer it takes. In situations when time is critical such as during emergencies and when a fast assessment of theevacuation time is needed, then relying on evacuation simulation tools might not be an option. Having a simplified model that can capture the different factors influencing the evacuation process and predict the total evacuation time would be a real advantage. In the research presented here, an attempt to develop such a simplified model has been made. The work undertaken during this research focused on investigating the possibility to derive a parametric model that could be simple enough to produce fast estimates of evacuation times but also capture the different elements of the evacuation process to satisfactory accuracy. Different parametric models were investigated. The nature of the problem led to investigate arrival processes, which were a good candidate for the underlying model explaining the evacuation of passengers. A close analysis showed that a Batch Non-Homogeneous Poisson Process (Batch NHPP) was needed to model the problem at hand. The batch arrivals and the NHPP are independent of each other so they were modelled and studied separately.The data used in this research came from a number of simulations (8 000 individual runs) performed with the Evacuation simulation software Evi as well as from the validation dataset produced by the EU-funded project SAFEGUARD and its associated Evi simulation runs (about 200 runs). The work was split between the fitting of the batch sizes of the arrivals and the NHPP. A complete analysis of the data was performed. The fitting of the batch sizes as well as the arrivals with the selected models produced very good results. Then, using the fitted models, new data was generated and analysed. The results were compared to the original data for both the batch sizes and the NHPP.
|Date of Award||5 Jun 2017|
- University Of Strathclyde
|Supervisor||Dracos Vassalos (Supervisor) & Dimitrios Konovessis (Supervisor)|