51 resultados para Fire Model
em Greenwich Academic Literature Archive - UK
Resumo:
This paper describes a project aimed at making Computational Fluid Dynamics (CFD) based fire simulation accessible to members of the fire safety engineering community. Over the past few years, the practise of CFD based fire simulation has begun the transition from the confines of the research laboratory to the desk of the fire safety engineer. To a certain extent, this move has been driven by the demands of performance based building codes. However, while CFD modelling has many benefits over other forms of fire simulation, it requires a great deal of expertise on the user’s part to obtain reasonable simulation results. The project described in this paper, SMARTFIRE, aims to relieve some of this dependence on expertise so that users are less concerned with the details of CFD analysis and can concentrate on results. This aim is achieved by the use of an expert system component as part of the software suite which takes some of the expertise burden away from the user. SMARTFIRE also makes use of the latest developments in CFD technology in order to make the CFD analysis more efficient. This paper describes design considerations of the SMARTFIRE software, emphasising its open architecture, CFD engine and knowledge based systems.
Resumo:
This paper describes a project aimed at making Computational Fluid Dynamics (CFD)- based fire simulation accessible to members of the fire safety engineering community. Over the past few years, the practice of CFD-based fire simulation has begun the transition from the confines of the research laboratory to the desk of the fire safety engineer. To a certain extent, this move has been driven by the demands of performance based building codes. However, while CFD modeling has many benefits over other forms of fire simulation, it requires a great deal of expertise on the user’s part to obtain reasonable simulation results. The project described in this paper, SMARTFIRE, aims to relieve some of this dependence on expertise so that users are less concerned with the details of CFD analysis and can concentrate on results. This aim is achieved by the use of an expert system component as part of the software suite which takes some of the expertise burden away from the user. SMARTFIRE also makes use of the latest developments in CFD technology in order to make the CFD analysis more efficient. This paper describes design considerations of the SMARTFIRE software, emphasizing its open architecture, CFD engine and knowledge-based systems.
Resumo:
The FIREDASS (FIRE Detection And Suppression Simulation) project is concerned with the development of fine water mist systems as a possible replacement for the halon fire suppression system currently used in aircraft cargo holds. The project is funded by the European Commission, under the BRITE EURAM programme. The FIREDASS consortium is made up of a combination of Industrial, Academic, Research and Regulatory partners. As part of this programme of work, a computational model has been developed to help engineers optimise the design of the water mist suppression system. This computational model is based on Computational Fluid Dynamics (CFD) and is composed of the following components: fire model; mist model; two-phase radiation model; suppression model and detector/activation model. The fire model - developed by the University of Greenwich - uses prescribed release rates for heat and gaseous combustion products to represent the fire load. Typical release rates have been determined through experimentation conducted by SINTEF. The mist model - developed by the University of Greenwich - is a Lagrangian particle tracking procedure that is fully coupled to both the gas phase and the radiation field. The radiation model - developed by the National Technical University of Athens - is described using a six-flux radiation model. The suppression model - developed by SINTEF and the University of Greenwich - is based on an extinguishment crietrion that relies on oxygen concentration and temperature. The detector/ activation model - developed by Cerberus - allows the configuration of many different detector and mist configurations to be tested within the computational model. These sub-models have been integrated by the University of Greenwich into the FIREDASS software package. The model has been validated using data from the SINTEF/GEC test campaigns and it has been found that the computational model gives good agreement with these experimental results. The best agreement is obtained at the ceiling which is where the detectors and misting nozzles would be located in a real system. In this paper the model is briefly described and some results from the validation of the fire and mist model are presented.
Resumo:
The FIRE Detection and Suppression Simulation (FIREDASS) project was concerned with the development of water misting systems as a possible replacement for halon based fire suppression systems currently used in aircraft cargo holds and ship engine rooms. As part of this program of work, a computational model was developed to assist engineers optimize the design of water mist suppression systems. The model is based on Computational Fluid Dynamics (CFD) and comprised of the following components: fire model; mist model; two-phase radiation model; suppression model; detector/activation model. In this paper the FIREDASS software package is described and the theory behind the fire and radiation sub-models is detailed. The fire model uses prescribed release rates for heat and gaseous combustion products to represent the fire load. Typical release rates have been determined through experimentation. The radiation model is a six-flux model coupled to the gas (and mist) phase. As part of the FIREDASS project, a detailed series of fire experiments were conducted in order to validate the fire model. Model predictions are compared with data from these experiments and good agreement is found.
Resumo:
In this paper, we present some early work concerned with the development of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modeling and represents an extension of this technique to situations involving the combustion of solid cellulosic fuels. A simple solid fuel combustion model consisting of a thermal pyrolysis model, a six flux radiation model and an eddy-dissipation model for gaseous combustion have been developed and implemented within the CFD code CFDS-FLOW3D. The model is briefly described and demonstrated through two applications involving fire spread in a compartment with a plywood lined ceiling. The two scenarios considered involve a fire in an open and closed compartment. The model is shown to be able to qualitatively predict behaviors similar to "flashover"—in the case of the open room—and "backdraft"— in the case of the initially closed room.
Resumo:
An integrated fire spread model is presented in this study including several sub-models representing different phenomena of gaseous and solid combustion. The integrated model comprises of the following sub-models: a gaseous combustion model, a thermal radiation model that includes the effects of soot, and a pyrolysis model for charring combustible solids. The interaction of the gaseous and solid phases are linked together through the boundary conditions of the governing equations for the flow domain and the solid region respectively. The integrated model is used to simulate a fire spread experiment conducted in a half-scale test compartment. Good qualitative and reasonable quantitative agreement is achieved between the experiment and numerical predictions.
Resumo:
When evacuating through fire environments, the presence of smoke may not only have a physiological impact on the evacuees but may also lead occupants to adapt their evacuation strategy through the adoption of another exit. This paper attempts to introduce this type of adaptive behaviour within the buildingEXODUS evacuation model through enabling occupants to make decisions concerning the selection of the most viable available exit during an evacuation involving fire. The development of this adaptive behaviour requires the introduction of several new capabilities namely, the representation of the occupants’ familiarity with the structure, the behaviour of an occupant that is engulfed in smoke and the behaviour of an occupant that is faced with a smoke barrier. The appropriateness of the redirection decision is dependent upon behavioural data gathered from real fire incidents (in the UK and USA) that is used to construct the redirection probabilities. The implementation is shown to provide a more complex and arguably more realistic representation of this behaviour than that provided previously.
Resumo:
Numerical predictions produced by the SMARTFIRE fire field model are compared with experimental data. The predictions consist of gas temperatures at several locations within the compartment over a 60 min period. The test fire, produced by a burning wood crib attained a maximum heat release rate of approximately 11MW. The fire is intended to represent a nonspreading fire (i.e. single fuel source) in a moderately sized ventilated room. The experimental data formed part of the CIB Round Robin test series. Two simulations are produced, one involving a relatively coarse mesh and the other with a finer mesh. While the SMARTFIRE simulations made use of a simple volumetric heat release rate model, both simulations were found capable of reproducing the overall qualitative results. Both simulations tended to overpredict the measured temperatures. However, the finer mesh simulation was better able to reproduce the qualitative features of the experimental data. The maximum recorded experimental temperature (12141C after 39 min) was over-predicted in the fine mesh simulation by 12%. (C) 2001 Elsevier Science Ltd. All rights reserved.
Resumo:
Parallel processing techniques have been used in the past to provide high performance computing resources for activities such as fire-field modelling. This has traditionally been achieved using specialized hardware and software, the expense of which would be difficult to justify for many fire engineering practices. In this article we demonstrate how typical office-based PCs attached to a Local Area Network has the potential to offer the benefits of parallel processing with minimal costs associated with the purchase of additional hardware or software. It was found that good speedups could be achieved on homogeneous networks of PCs, for example a problem composed of ~100,000 cells would run 9.3 times faster on a network of 12 800MHz PCs than on a single 800MHz PC. It was also found that a network of eight 3.2GHz Pentium 4 PCs would run 7.04 times faster than a single 3.2GHz Pentium computer. A dynamic load balancing scheme was also devised to allow the effective use of the software on heterogeneous PC networks. This scheme also ensured that the impact between the parallel processing task and other computer users on the network was minimized.
Resumo:
The amount of atmospheric hydrogen chloride (HCl) within fire enclosures produced from the combustion of chloride-based materials tends to decay as the fire effluent is transported through the enclosure due to mixing with fresh air and absorption by solids. This paper describes an HCl decay model, typically used in zone models, which has been modified and applied to a computational fluid dynamics (CFD)-based fire field model. While the modified model still makes use of some empirical formulations to represent the deposition mechanisms, these have been reduced from the original three to two through the use of the CFD framework. Furthermore, the effect of HCl flow to the wall surfaces on the time to reach equilibrium between HCl in the boundary layer and on wall surfaces is addressed by the modified model. Simulation results using the modified HCl decay model are compared with data from three experiments. The model is found to be able to reproduce the experimental trends and the predicted HCl levels are in good agreement with measured values