Orlando Abreu

An Evacuation Model for High Speed Trains

In this paper we present a stochastic evacuation model specifically for high speed passenger trains. The proposed model is an object-oriented model in which passengers are represented using a cellular automata method and the train space by a fine network of 0.5 m x 0.5 m cells. The model is based on Monte Carlo methods in order to simulate the probability and effects of passengers’ actions and decisions during the evacuation process. The datasets used as default by the model are taken from video recordings of evacuation drills and virtual experiments conducted at the University of Cantabria. However, the flexibility of the model allows the user to modify this data. The results of this model are then compared with other validated evacuation models. The proposed model has a simple user interface and the results are given in real-time. This model could be a useful tool for evacuation management during real emergencies. The advantages of using a stochastic approach for modelling passengers’ behaviour in relation to a deterministic approach are discussed.

Future Challenges in Evacuation Modelling

Evacuation is a common strategy for preserving life safety. For this reason, there is a need for reliable and accurate predictions relating to this process. However, evacuation represents a unique, complex, and uncertain phenomenon. As a physical process, it involves the movement of people from their points of origin towards a destination point, under variable environmental conditions. As a behavioural process, it involves human characteristics, decisions, and actions. Therefore, it is evident that in most of cases, there is not a simple solution to solve the problem at hand. Over the last few decades, the evacuation process has begun to be analysed using computer modelling and simulation. To date (2014), there exist over 40 evacuation computer models. These facilitate analysis of the potential outcomes of an evacuation, during hypothetical emergencies. However, the application and credibility of such tools is questionable. The models’ capabilities, scrutiny, and validation have been the focus themes for the last few years. In addition, there exists a demand to extend the use of these models to the simulation of new scenarios and applications. Evacuation modelling will remain in use, and the evacuation models of the future will need to be adapted to meet new requirements. New processes will have to be simulated using new modelling approaches, while the need for empirical data and validation methods will remain the key issues for the evacuation modelling community. Although the future of evacuation modelling in the long-term is uncertain, it is possible to look at the current requirements, and thus, highlight future challenges in a short-term sense. This chapter discusses some of the future challenges in evacuation modelling. The chapter is divided into three sections. The first section addresses the problem of new scenarios, and highlights some factors for future model developments. The second addresses the problem of using deterministic and/or stochastic approaches in evacuation modelling. The third section proposes, and discusses, the use of evacuation models for supporting timely decisions in real-time.

Evacuation Modelling of Fire Scenarios in Passenger Trains

Fire incidents inside passenger trains constitute a significant risk factor for life safety. Therefore, it is necessary to count on a suitable evacuation strategy, during the instants previous to the rail vehicle halt and the subsequently evacuation. In this paper, the evacuation of passengers from different fire scenarios and several evacuation conditions were investigated. The analysis was divided into two stages of the evacuation process considering two different high speed trains: (1) the movement and behaviour of passengers in fire scenarios inside the vehicle before the train stopped, and (2) the analysis of train evacuation under different conditions. The results, obtained by means of the egress model STEPS (see MacDonald, STEPS Simulation of Transient and Pedestrian Movements User Manual), allowed to determine the influence of the limitations of the different train geometries under different evacuation conditions, give an estimation of the evacuation times and analyse the impact of human parameters considered in the evacuation process.

Pyrolysis Characterization of a Lineal Low Density Polyethylene

A set of parameters for pyrolysis characterization of linear low density polyethylene (LLDPE) were chosen to measure its combustion behaviour. Two kinds of parameters were selected, material and reaction. The material parameters were: effective values of the mass density (ρ); specific heat capacity (c); thermal conductivity (k); absorption coefficient (қ) and emissivity (e). The reaction parameters were the exponential factor (Z), the energy of activation (E) and the reaction mechanism f(α). In addition simultaneous thermal analysis (STA) tests were carried out at heating rates of 2, 5 and 10 K/min in N2 atmosphere to obtain the kinetic triplet and cone calorimeter tests at irradiance levels of 25, 40, 50 and 75 kW/m to compare the simulated mass loss rate against real mass loss rate. Finally the cone calorimeter tests were used as input values to optimize the parameter set to perform real mass loss rate.