J. A. Capote

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.

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.

Numerical Simulation of Fire Growth, Transition to Flashover, and Post-Flashover Dynamics in the Dalmarnock Fire Test

The objective of the present study is to evaluate the ability of current Computational Fluid Dynamics (CFD) tools to simulate compartment fires with flashover followed by under-ventilated and/or quasistoichiometric, partially-under-ventilated conditions. Current CFD capabilities are illustrated using the Fire Dynamics Simulator (FDS, Version 5), developed by the National Institute of Standards and Technology, USA. The FDS modeling capability is evaluated by detailed comparisons with an experimental database previously developed by the University of Edinburgh, UK. The test configuration corresponds to a fullscale fire test known as the Dalmarnock fire test (test 1). The description of the flammable content in the fire room is based on a standard modeling approach in which the ignition time of flammable objects and materials is calculated using a local heat transfer solver, while the fuel mass loss rate after ignition is prescribed using experimental data from cone/furniture calorimeter tests. The simulated Dalmarnock fire scenario includes flashover, a first post-flashover stage that is under-ventilated and characterized by burning outside the fire room, and a second post-flashover stage that is partially-under-ventilated and characterized by distributed burning inside the fire room. Transition to this second stage is triggered by window breakage in the fire room. The different stages of the fire scenario are analyzed in terms of the fire room global equivalence ratio (GER), which is considered as the main controlling parameter of the fire behavior. Comparisons between numerical results and experimental data are relatively good when considering the global features of the fire dynamics, e.g., the time history of the spatially-averaged heat release rate. Comparisons are not as good when considering local features, e.g., the time history of gas or wall temperatures, or that of wall heat fluxes.

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.