On the modelling of fire atmosphere/sprinkler spray interacting using an Euler-Lagrange framework

An Euler-Lagrange particle tracking model, developed for simulating fire atmosphere/sprinkler spray interactions, is described. Full details of the model along with the approximations made and restrictions applying are presented. Errors commonly found in previous formulations of the source terms used in this two-phase approach are described and corrected. In order to demonstrate the capabilities of the model it is applied to the simulation of a fire in a long corridor containing a sprinkler. The simulation presented is three-dimensional and transient and considers mass, momentum and energy transfer between the gaseous atmosphere and injected liquid droplets.

Principles and Practice of Fire Modelling: A Collection of Lecture Notes for a Short Course

Once the preserve of university academics and research laboratories with high-powered and expensive computers, the power of sophisticated mathematical fire models has now arrived on the desk top of the fire safety engineer. It is a revolution made possible by parallel advances in PC technology and fire modelling software. But while the tools have proliferated, there has not been a corresponding transfer of knowledge and understanding of the discipline from expert to general user. It is a serious shortfall of which the lack of suitable engineering courses dealing with the subject is symptomatic, if not the cause. The computational vehicles to run the models and an understanding of fire dynamics are not enough to exploit these sophisticated tools. Too often, they become 'black boxes' producing magic answers in exciting three-dimensional colour graphics and client-satisfying 'virtual reality' imagery. As well as a fundamental understanding of the physics and chemistry of fire, the fire safety engineer must have at least a rudimentary understanding of the theoretical basis supporting fire models to appreciate their limitations and capabilities. The five day short course, "Principles and Practice of Fire Modelling" run by the University of Greenwich attempt to bridge the divide between the expert and the general user, providing them with the expertise they need to understand the results of mathematical fire modelling. The course and associated text book, "Mathematical Modelling of Fire Phenomena" are aimed at students and professionals with a wide and varied background, they offer a friendly guide through the unfamiliar terrain of mathematical modelling. These concepts and techniques are introduced and demonstrated in seminars. Those attending also gain experience in using the methods during "hands-on" tutorial and workshop sessions. On completion of this short course, those participating should: - be familiar with the concept of zone and field modelling; - be familiar with zone and field model assumptions; - have an understanding of the capabilities and limitations of modelling software packages for zone and field modelling; - be able to select and use the most appropriate mathematical software and demonstrate their use in compartment fire applications; and - be able to interpret model predictions. The result is that the fire safety engineer is empowered to realise the full value of mathematical models to help in the prediction of fire development, and to determine the consequences of fire under a variety of conditions. This in turn enables him or her to design and implement safety measures which can potentially control, or at the very least reduce the impact of fire.

The use of mathematical modelling in fire safety engineering

Fire is a form of uncontrolled combustion which generates heat, smoke, toxic and irritant gases. All of these products are harmful to man and account for the heavy annual cost of 800 lives and £1,000,000,000 worth of property damage in Britain alone. The new discipline of Fire Safety Engineering has developed as a means of reducing these unacceptable losses. One of the main tools of Fire Safety Engineering is the mathematical model and over the past 15 years a number of mathematical models have emerged to cater for the needs of this discipline. Part of the difficulty faced by the Fire Safety Engineer is the selection of the most appropriate modelling tool to use for the job. To make an informed choice it is essential to have a good understanding of the various modelling approaches, their capabilities and limitations. In this paper some of the fundamental modelling tools used to predict fire and evacuation are investigated as are the issues associated with their use and recent developments in modelling technology.

The FIREDASS (Fire Detection and Suppression Simulation) Model

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.

Enhancing the numerical performance of fire field models (CMS Paper)

This paper describes two new techniques designed to enhance the performance of fire field modelling software. The two techniques are "group solvers" and automated dynamic control of the solution process, both of which are currently under development within the SMARTFIRE Computational Fluid Dynamics environment. The "group solver" is a derivation of common solver techniques used to obtain numerical solutions to the algebraic equations associated with fire field modelling. The purpose of "group solvers" is to reduce the computational overheads associated with traditional numerical solvers typically used in fire field modelling applications. In an example, discussed in this paper, the group solver is shown to provide a 37% saving in computational time compared with a traditional solver. The second technique is the automated dynamic control of the solution process, which is achieved through the use of artificial intelligence techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxation using an integrated production rule engine with a blackboard to monitor and implement the required control changes during solution processing. Initial results for a two-dimensional fire simulation are presented that demonstrate the potential for considerable savings in simulation run-times when compared with control sets from various sources. Furthermore, the results demonstrate the potential for enhanced solution reliability due to obtaining acceptable convergence within each time step, unlike some of the comparison simulations.

SFPE Engineering Guide to Human Behavior in Fire

Abstract not available