Mr. S.P. Dharne, Ex-Executive Director, Nuclear Power Corporation of India, Mumbai
Holds Bachelor’s Degree in Mechanical Engineering from University of Mumbai. Completed graduation from BARC Training School and Intensive Programmeon “Artificial Intelligence and Expert Systems” from IIT, Bombay. Specilisation in HR Services, Power Plant Dynamics, Fire Analysis, Thermal Hydraulics
Fire is a very important consideration with respect to human safety, safety of structures and equipment and economics, in all the walks of life and especially so in the industry. Various fire safety strategies are employed to prevent or minimize risk to various equipment / systems and personnel in line with the current trends in the industry. Various codes, guidelines and rules & regulations exist at national as well as state level, specifying the responsibilities of various stakeholders like administration, owners of the facilities and the constructors.
However, the emphasis is always seen on the methods of fighting the fire and escape from it. Very few attempts are made to understand the fundamentals of fire and it’s dynamics, which can help a long way in highly improving the probability of fire prevention, fire fighting methods as well as evacuation of the personnel in case of a fire in the building or industrial facility. The paper describes the basics of fire, various methods of fire modeling, the Fire Hazard Analysis and the suggested approach augmenting the conventional techniques with modern tools like study of fire dynamics. The scope of this paper limits to the deterministic studies only and excludes the probabilistic fire models.
KEYWORDS : Industral Facilities; Hazards; Safety Management and Fire Safety, Fire Hazard Analysis, 3-D Fire Analysis
1.0 INTRODUCTION
The best way to deal with fire hazard is to prevent it if not eliminate it. However, a survey of the codes, acts and rules & regulations with respect to fire, shows that the emphasis is on the mitigation of the fire and mechanisms to fight it rather than preventing it with a thorough understanding of the basics of fire and it’s dynamics.
Indian Standard Code of Practice for Fire Safety of Buildings (General), IS:1644 [1] puts various stipulations with respect to the requirements like exits, internal and external staircases, corridors, passageways, fire escapes and roof exits for the buildings categorized in ten categories from A to J. The “Maharashtra Fire Prevention and Life Safety Measures Act 2006 as published in 2009 [2],” specifies the responsibilities of stakeholders like local governing bodies and roles of various agencies like police and licensing authorities before, during and after the fire incidence.
The ideal goal of any fire prevention programme should be to eliminate the fire probability. Though impossible to achieve it in practice, the understanding of the fundamentals of the fire, fire phenomena and complimenting the same with study of fire dynamics reduces the fire probability to a very low and practicable level.
2.0 FIRE FUNDAMENTALS
Fire, as has been aptly described by Hottel [3], is the most complex phenomenon to understand, next to the life process. It involves the complex interactions between a number of components viz.:
- The fuel and the combustion process
- The multi-phase flow and the turbulent mixing
- The radiative and conjugate heat transfer
A pictorial depiction of fire components and the associated studies required to understand and model the fire, is given in Fig. 1. The figure elaborates the components of fire like fuel, flame, combustion products and modes of heat transport involved. The figure also shows the associated studies like, rate of burning depending the type of fuel (solid/liquid/gas), heat release rate per unit are (HRRPUA), heat transfer analysis, combustion product modeling and analysis as well as fire suppression means and their effectiveness. The scope of these studies is very vast and very complex.
3.0 FIRE HAZARD ANALYSIS (FHA)
The goals of a FHA are to estimate the consequences of a fire scenario and to ascertain the adequacy of fire protection measures. The scenario is defined by a number of parameters like building/room dimensions, plan of the building depicting the relative positions of various enclosures, structural materials used in construction, the material in the room which can catch fire (termed as fire load), positions and number of vents/windows/doors, number and type of personnel who may be present at a given time, etc. FHA considers fire in all its stages viz. ignition, growth and flashover. A typical diagram of fire growth is given as Fig. 2.
There are many methods used for carrying out the FHA. Fire modelling is one such deterministic method. A fire model can be a physical full scale model, a scaled down physical model or a mathematical model comprising of many governing equations, empirical correlations. A mathematical model generally ends up in a form of computer code or software package with appropriate user interface. Fig. 3 depicts various fire models in a hierarchical format.
A mathematical fire model attempts to encode the physical fire phenomena in the mathematical form. Hence the applicability and the so called “correctness” of prediction by the fire model will totally depend on the how close and how truthfully the phenomenon is captured by the mathematical model. As a recommended practice, FHA of every plant/industrial facility should be carried out to assess the fire potentials, fire protection strategies, detection mechanisms and suppression means at the plant locations. In fact in certain industries like nuclear, the detailed FHA is mandatory. It should also be so in the hazardous industries like petrochemical and explosive chemicals.
4.0 FIRE MODELS
As depicted in the figure above, fire studies can be carried out using physical models either in full scale or reduced scale. However this option can be used only for the simple, representative and fundamental studies considering its feasibility and economic limitations. Given the accidental nature of fire and the numerous scenarios it poses, there is no alternative but to resort to mathematical modelling and build the predictive capabilities with validated models. Here again, the experiments or the physical models are required as validation mechanisms for the predictive tools thus developed.
The mathematical models can be deterministic or probabilistic in nature. The deterministic model is a set of equations with appropriate initial and boundary conditions to represent the physical phenomena. The process of modeling is depicted in Fig. 4.
As said above, the scope of this paper restricts to deterministic models. In deterministic models, as of date, there are two classes of fire models available to us, the “Zone Models” and the “Field Models”. The modeler may choose to employ a particular type of model or a combination of models to analyze a fire scenario. It is obvious that modeling complexities and efforts increase as one moves from simple zone models to elaborate field models.
4.1 Zone Models
Zone models are designed with the concept that the fire compartment under consideration can be divided into two distinct but homogeneous zones viz. hot (upper) zone and cold (lower) zone. Mass & energy balances are considered within these two zones. The fire plume is assumed to act as a pump of mass (smoke particles) and heat to the upper (hot) zone. The schematic diagram of one zone model is shown in Fig. 5.
The basic equations can be enhanced with inclusion of correlations for various phenomena like ventilation, solid fuel pyrolysis etc. The zone models therefore are simple models based on easy formulations and do not consume large computing resources.
The most commonly used zone model based codes are CALFIRE, CFAST, ASET, FIRE-MD, SmokePro or an in house model based on the zone model philosophy.
The emphasis of zone model is on computation of fire duration, variation of hot zone temperature with time, oxygen availability, visibility index and fire barrier rating for the compartment. The basic equation used in this model is reproduced below.
The equation for growth of fire is given by [4]
Q = α.t²………………………………(4.1.1)
Where Q is the Heat Release Rate in KW, ‘a’ is an empirical constant KW/s² and ‘t’ is time in seconds. a Values are estimated by NIST as follows:
∝ = 0.00293 For slow fire growth (CV < 4500 Kcal/Kg)
= 0.01172 For medium fire growth (CV between 4500 – 9000)
= 0.0469 For fast fire growth (CV between 9000 – 10000)
= 0.1876 For ultra fast fire growth (CV > 10,000)
This equation can also be employed for field models if found reasonable.
The McCaffrey, Quintiere and Harkleroad equation [5] can be used for computation of hot layer temperature in a naturally ventilated compartment.
While the same can be modeled using Foote, Pagani and Alvares [6], for a forced ventilation situation.
The mass loss rate is estimated from the heat release rate
m = Q/(CV) ….(4.1.4)
Where Q is Heat release rate, KW and CV is weighted average calorific value of combustibles in KJ/Kg
The mass production rate of smoke-filled gas is estimated [7] as:
Where
M – smoke filled gas production rate, Kg/s
Q – total heat release rate, KW
ρ∝ density of air, Kg/m3
CP Sp. heat of air at constant pressure, KJ/KgK
T – ambient gas temp, K
g – acceleration due to gravity, m/s2
Y – Dist. from the virtual point source
for the fire to bottom of smoke layer, m
4.1.1 Limitations of zone models:
There are a plethora of the zone models available to the user. As mentioned earlier, these are very simple to understand, use and are very light on the computing resources. They give a reasonably good first hand feel about the fire scenario & prove themselves as a handy tool for certain class of users like on the spot fire inspectors. However due to their simplistic constructs, they have their own set of limitations like:
- Approximate due to empirical correlations
- The plume volume is assumed to be negligible as compared to the hot and cold zones. Further, plume description is limited by the sub-model simulating the phenomenon.
- Local effects viz. hot & cold spots are ignored
- Geometric modelling is restrictive due to approximation of every compartment as a cuboid.
- Uneven combustion and its effects are not accountable
- The hot and cold layers are assumed to be homogeneous and uniform which is not the case in reality
- Too simplistic re-radiation model
- Room contents and its effect on heat transport and smoke distribution is ignored
These limitations obviously have their impact on the predictions and they essentially drive the user to use the field models whenever a deep insight into the fire scenario is necessary.
4.1.2 Field Models
Field models, developed using Computational Fluid Dynamics (CFD) techniques, solve the fundamental conservation equations for the mass/species, momentum & energy alongwith the associate equations for combustion, suppression and various other source term computations. Depending on the requirement one may choose the level of detail and complexity level and use 1-D, 2-D and 3-D formulations. The field models, based on the level of detail/complexity deployment, provide detailed information about fire propagation, spatial distribution of temperature, velocity, soot and other parameters within the domain under consideration, both for steady state & time varying scenarios.
Field models allow modeling of complex geometry and phenomena with fewer assumptions providing scope for more realistic simulation of the dynamic, fast, and highly energetic nature of fire. Detail combustion and turbulence modules add further realism into the simulation and also cover the effects of fire generated turbulence within the domain of interest. The capability to cover effects of doors, windows and vents provides additional realism to the simulation.
Field models also provide the means to assess, evaluate and check adequacy of fire detection and suppression systems as well as help in optimizing their locations and layout.
Fire Dynamics Simuator (FDS) is a tailor made CFD tool for simulating fire scenarios. It is a free ware and readily available for use. A typical set of equations used in the Fire Dynamic Simulator (FDS), a widely used field model based software code is reproduced below [8] as Fig. 6.
The turbulence is modeled using the Large Eddy Simulation (LES) formulation while the choice is available to the user to use the Direct Numerical Simulation (DNS) method. This has a bearing on the use of combustion model. While in DNS, there is a possibility of modelling the diffusion of fuel and oxygen and thereby the combustion rate, the same can not be done while using the LES route. FDS uses the mixture fraction model for use with LES model. The governing equations for mixture fraction model, combustion as well as the gross chemical reaction for hydrocarbon fuel are given in Fig. 7.
In addition the equations for various phenomena like the radiation term in the energy equation, turbulence effects in the momentum equation, rate of solid fuel pyrolysis/charring or evaporation of liquid fuels which ultimately governs the rate of its combustion are employed by FDS.
5.0 FIRE MODELLING CHALLENGES
Fire being complex and multi-disciplinary phenomena, it can be best understood when all the factors contributing to it can be understood and characterized to the desired level.
The challenges in fire modeling are posed by the lack of the deep understanding of complex phenomena, complexity of field models, the tightly coupled nature of multitude of parameters, the numerical techniques required to solve the governing equations and on top of everything, the need for realistic input data.
Even in present era of abundant computing power, a realistic study like fire in turbine hall poses a formidable demand on computational resources.
6.0 SUGGESTED APPROACH FOR FHA
As clearly brought out in section 4.1.1 the zone models alone are too simplistic and their predictions are useful only upto a certain extent. A realistic prediction can come out of a combination of Zone Models and Field Models. This can be well illustrated by an example shown in Fig. 8. It shows the prediction by zone model as well as field model. We can clearly see the correct and logical prediction by field model. Innumerable studies have been carried out for various fire scenarios in critical areas of power plants. These studies have given a great insight into the fire scenarios and their consequences leading to vital inputs in the design of new power plant layouts and equipment positioning.
7.0 CONCLUSION
Fire hazard Analysis of critical areas to have the realistic consequence predictions for a fire scenario, for any industrial facility, can be realistically done by adopting the novel approach of combining the Zone model and Field Model studies.
8.0 REFERENCES:
- Indian Standard Code of Practice for Fire Safety of Buildings (General): Exit Requirements and Personal Hazard, IS 1644 : 1988, (Reaffirmed 2002)
- Maharashtra Fire Prevention and Life Safety Measures Act, 2006, Maharashtra Government extra-Ordinary Gazzete, Part 4-B, June 23, 2009
- H.C. Hottel. Stimulation of Fire Research in the United States after 1940 (A Historical Account), Combustion Science and Technology, 39:1–10, 1984.
- IAEA–TECDOC–1134, Use of operational experience in fire safety assessment of nuclear power plants, January 2000.
- Fire Safety Engineering – Part 2, “Design Fire Scenarios and Design Fires”, ISO Technical Report, ISO/TR 13387-2(E), 1999.
- SFPE Handbook of Fire Protection Engineering, 3rd Edition, 2002.
- Grant C., Pagni P. J. – Ed. Fire Safety Science: Proceedings of the First International Symposium, Taylor & Francis, 1986.
- McGrattan K., Ed. Fire Dynamics Simulator (Version 4) Technical Reference Guide, NIST Special Publication 1018, February 2005.