CFD Simulation of fires

CFD codes have also been developed to predict the outcome of a fire in a tunnel or a subway system. Simcox et al. (1992) examined the effect of varying heat release rates, heat release area, and different boundary conditions through simulations investigating the King's Cross fire. Further research by Woodburn and Britter (1996a; 1996b) was concerned with investigating and quantifying several sensitive factors between CFD simulation and experimental measurements of a fire in a tunnel. They found that the naive use of a CFD simulations code is likely to cause large uncertainties. Errors between simulation and experiment were up to 60%. They established the need for the precise specification of ventilation velocity profile, natural convective, radiative heat transfer, wall roughness, boundary condition, turbulence model and heat input rate for the simulation.

In the early research, Chow (1996) predicted five fires that would have a high likelihood of occurring in a tunnel from a self-developed fire field model for studying the aerodynamic and smoke movement in a tunnel. Further, experimental data collected in a smaller tunnel from an abandoned copper mine in Norway was used to justify the prediction. Those experiment were validated the numerical simulating tunnel fires in different scenarios. A study by Lee and Ryou (2006) modified and developed CFD models to predict the effect of the aspect ratio on smoke movement in tunnel fires using FDS 3.0. Fire Dynamics Simulator (FDS) is a large-eddy simulation (LES) code for low-speed flows, with an emphasis on smoke and heat transport from fires. Their results were compared with a full scale experiment. Their numerical simulation showed the predicted temperature distribution under the ceiling was in good agreement with experimental values within 10^oC. Results from varying the aspect ratio showed good agreement with experimental data. The temperature near the fire source decreased

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with the increase of the aspect ratio but the rate of the temperature decrease was reduced by a decrease of the heat loss in the slantwise direction. This work confirmed the possibility of the application of FDS code to predict the smoke movement in tunnel fires. Subsequently it has been used to predict the temperature and smoke distribution of a tunnel fire (Wen et al., 2007) and a simulation of temperature and smoke distribution of a tunnel fire were performed by Xiaojun (2008). In this study some modifications to the model were presented including the governing equations, radiation heat transfer models and flow rate through openings.

A review of several papers indicated that a station ventilation system is the most important component of the subway systems when events involving heavy smoke occur. Research by Teodosiu et al. (2016) analysed the efficiency of a mid-tunnel fan mechanical ventilation system when a train on fire and stopped at a platform. This work was performed using the CFD modelling software ANSYS Fluent 15.0. The results showed that a good ventilation strategy can lead to the safe evacuation of passengers once they have left the train. In a similar study by Meng et al. (2014) used CFD simulations to study the effectiveness of different ventilation modes in case of a train fire in a subway station. Results showed that appropriate activation of the air supply system can improve the efficiency of the ventilation system in smoke control, and vice versa. It was better to activate a lobby air supply system and meanwhile close the platform air supply system. The additional smoke barrier, smoke propagation in a subway station can controlled by optimal use of the ventilation system. Zhou and Zhang (2012) also evaluated the effectiveness of an air curtain to improve the ventilation in the subway station fires using CFD simulations. This research of Chen, et al. (2003) of three-dimensional smoke flow fields under various kinds of fires were computed by CFD modelling to investigate the effectiveness of the smoke control scheme of the Gong-Guan subway station (GGSS) which is a typical subway station of the Taipei Rapid transport system. The results indicate that the stack effect plays a deterministic role in smoke control when a fire occurs near the stairwell and no mechanical smoke control is necessary. When a fire occurs in other places, such as at the end or the centre of the platform, the current mechanical control schemes are effective which is controlled smoke confined to a small region or is evacuated from the station, leaving the four exits free of smoke so that the passengers can escape through them. This research also investigated the effectiveness of the smoke control system and proposed an innovative smoke control scheme for fires occurring on the chassis of a train with the smoke control on platform edge door. This study provides both

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valuable information for the design of passenger evacuation routes in fires as well as criteria for the design of a smoke control system for subway stations.

2.5.2 Validation

The tunnel ventilation systems typically consist of ventilation shafts located at each end of station and/or between two stations to provide longitudinal forced ventilation for the control and extraction of smoke from a fire in the tunnels, to maintain tolerable conditions in the non-incident tunnel, and to control and extract smoke in the event of fire on a train at a station platform (Ting et al., 2012). The CFD simulations are traditionally validated by detailed wind-tunnel experiments or in field measurements.

Order-of-accuracy verification is necessary to ensure that software correctly solves a given set of equations and experimental results are required to set up accurate boundary conditions. For example, Apte et al. (1991) who investigated the effects of varying ventilation velocities and fuel pan size on the spread of smoke in a tunnel compared their simulation results with experiments performed in a large scale wind tunnel. The dispersion of a pollutant emitted from a roof stack in the wake of a tower, in a two-building configuration was examined by numerical simulation (CFD) by Stathopoulos (2004) and validated by experiments in which sulfur-hexafluoride (SF6) tracer gas was released on the roof of building and concentrations were measured at several locations on this roof and on the facade of a neighbouring high-rise building.

Lateb et al. (2011) validated his LES simulation of pollutant dispersion in an actual building group in downtown Montreal. A comparison of numerical simulations and experimental tests of ventilation in tunnels has been performed by Ingason et al. (1999) who evaluated the effects and influence of longitudinal ventilation on the smoke spread in tunnels when using thermal and mechanical point exhaust ventilation. Ribot et al.

(1999) performed a numerical simulation of smoke extraction by roof ventilation in a tunnel by using CFX Fluent and compared it with experimental results.

Experimental validation of CFD results can be done in several ways. For small and relatively simple tests which do not involve high velocities wind tunnel tests can be performed based on Reynolds number scaling. This is adequate for architectural elements such as stair wells for instance but will be very difficult to undertake for a complete station. Direct measurements of the airflow can be undertaken with sensors placed at discrete locations within a station (Pflitsch et al., 2010) measuring airflow in subway system. This requires robust sensors if they are to be kept in place for any length of time but the use of ultra-sonic anemometers has proved to be a reliable and

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successful means of obtaining air flow data from subway systems. A more detailed understanding of the airflow in a building can be obtained by the application of tracer gas tests. In this a tracer gas is released inside a building and sensors placed in the building that have been synchronised to the gas release time record the time and concentration of the tracer gas. In recent tests in Berlin, the Cave and Subway Climatology group at the Ruhr-University released sulphur hexafluoride (SF6) as a tracer gas to evaluate the efficiency of evacuation routes. SF6 is a well-established tracer gas that is used in mines and to detect for leaks in electrical switch gear. It behaves like normal air, it is colourless, odourless and non-flammable and normally exists in very small quantities in air as it is entirely man made (Turk et al., 1968; Pflitsch et al., 2012, Brune et al., 2016). In these series of measurements air samples were taken in syringes at different locations in the station. The time after the release time of the SF6 was recorded and the sample was then taken to a laboratory for analysis. This sampling rate was inevitable slow involving a large number of student volunteers to take the measurements. Analysis of the results reflected the trajectories of toxic airborne agents from a source to the exits of the station and pointed out the safest escape routes. The tracer gas experiments plus air flow measurements can give answers to the spreading of toxic agents in subway stations but they can also be used to provide boundary conditions for CFD analysis of complete buildings and also validate the subsequent CFD results. They are also very useful tool for examining the dynamic interaction of the background air flow and the train induced flows in a subway system.

Pedestrian simulations were used to calculate evacuation times for possible escape routes. Designated evacuation routes in a multi agent simulation show the importance of a dynamic guiding system on the evacuation process. Combining these methods, an empirical investigation for different evacuation strategies can be analysed and assessed in respect to safety.