The Fuel Size in Heat Release Rate - Term Paper Example

Table of Contents Mathematical models 2 Turbulence 4 Combustion 6 Numerical techniques 9 Domains and Meshes 10 Design fires 12 Effect of fuel and mesh size 15 Procedure: 16 Materials 16 Fire heat release rate: 17 References 23 Mathematical models a). Please list the governing equations of fire simulation and explain the physical meaning of each equation. Mass balance Momentum Conservation The momentum equation for a turbulent flow in the x (longitudinal) direction is derived from the general Navier-Stokes equation as where  is the density of gas flow is the mean point velocity in the x direction is the mean point velocity in the y direction t is time  is the absolute coefficient of viscosity which represents viscous shear stresses in the air. isthe ‘eddy viscosity’ which represents turbulent shear stresses in the air. The magnitude of for a given flow has to be evaluated, for example, by the k–ε turbulence model. , and contribution due to body forces. =0 = - g =0 viscous stresses: Dimensional steady state flow equation is made  The need boundary conditions When solving the equations, one needs to consider boundary conditions such as mass flow rate, pressure and temperature b).Explain the reasons why CFD codes are written in low speed solver and high speed solvers. CFD codes are written in low speed solver solve flows in low speed and uses low memory. CFD codes written in high speed solvers use large memory and are capable of solving large problems as well as those with higher speed flows, they also take into account turbulent flows. A student is simulating an object flying at a velocity of 290m/s in the air using FDS6 will not get acceptable results as he is using low speed solver for high speed object c). background pressure used in FDS is initial pressure. CFD codes simulations will begin with initial values of the flow and then converge to the final solution after a number of iterations. Initial values would certainly affect the time taken by the solution to converge to the final value Background pressures varies with height but are otherwise constant in a pressure zone, this means that different rooms can have different background pressures FDS decomposes the pressure into background and dynamic components Turbulence a). Explain the reasons why turbulence models are required in CFD. When choosing the sub models it is important to put into consideration the degree of accuracy desired (Karlsson and Quintiere 2000). In most instances the large Eddy Simulation has been found to the most applicable method in FDS (Yang, D & Hu, L ,2010; Merci , B & Vandevelde, P. 2007). In situations where there is the use of grid resolutions that is fine enough it is possible to model the turbulent flow with no necessity for a sub-grid approximation which is known as Direct Numerical Simulation (DNS). The DNS model finds its application exclusively in compartment fire application in also in research situation owing to its computational cost (Bishop, S & Drysdale, D 1995). A large eddy simulation has the capability of fully simulating all the fluctuations which are large than the mesh size. When an estimation is being made for smaller eddies there is little uncertainties due to the fact that the eddies are of a uniform character (Novozhilov, 2001). Large Eddy Simulation (LES)- According to Utiskul, 2003 CFD in modelling of a stickler make use of the technique of k-epsilon. Through this, LES technique which finds application in FDS model gives a temporal resolution that plays a vital in the evaluation of entrainment. It can therefore, be seen that a time averaged technique may have a very serious on the total air that is entrained into fire. The development of basic model for FDS was through a mathematical approach which is common in CDF models where proper emphasis is placed on slowing down the flow of heat transfer that is brought about by fire. Direct Numerical Simulation (DNS)- DNS simulations possess various problems in respect to modelling an environment with the computational resources currently available. This calls for highly fine grid resolution for example, the Kolmogorov micro scale. Further, DNS has a problem with the amount of grid points required. It raises three-fold the Reynolds number (Re3). Consequently, the Reynolds number for fire and smoke movement within a compartment is close to 105, thus; the total number of cells crucial for solving the movements within a room goes up to the value of 1013. The current super computers have the capacity to attain the grid resolution of 5123 (134,217,728) cells. Thus, the existing computer technology cannot give solutions of such motions The parameters of the LES model used in the FDS software are Heat release rate, Pool size, Radiation model, Radiation mesh and Flow mesh/ b)Based on Kolmogorov’s turbulence theory, explain the mesh resolution required by DNS and LES. Critically compare their pros and cons. Kolmogorov scale of velocity in homogeneous turbulence depends on the kinematic viscosity coefficient v [m2/s], specific dissipation rate [J/(kg s)] and, maybe, of fluid density [kg/m3]. Obtain the formula for this dependence using ∼⇒ (1/3 Where is tή timescale, u is turbulence intensity and η is small length ratio. Kinematic viscosity coefficient v [m2/s], where it changes is calculated from Reynolds number and it is formula is as follows; Re = = When the two equations are combined, the following formulae are obtained. The results for the out the formulas is shown below. Time scale is =( )1/2 Kolmogorov scale of velocity: V = Combustion a). combustion model is required in fire simulations as it this model has the capacity of treating the processes of conversion of fuel and oxygen to products and heat and with this makes FDS to have the ability to simulate a fire and the effects it has on its immediate environment in addition to simply the flow of fluid. In this there is utilization of two models: finite rate reaction model and the mixture fraction combustion model (Bullen ML, Thomas PH, 1978). The finite rate reaction model is the most appropriate in checking for resolutions of DNS calculations when resolving the diffusion of gas species. The occurrence of the reaction is instantaneous when there is the mixing of oxygen and fuel in the cells when the combining of the gas and oxygen fall in Burn zone. On the other hand if the combining of the gas and oxygen happen to fall in the “No Burn” zone there will be mixing of fuel and oxygen but no reaction will occur (Quintiere, 2004; Bishop. et al. 1992). The occurrence of such a situation is described as a null reaction. In the instantaneous reaction models products that are produced may include CO2 H2O, CO and soot through the combustion process which is in proportion with the rate at which the fuels are being consumed. It is thus appropriate to give the yields of the products bearing in mind the mass of the fuel that has been consumed (Thomas, 1981; Epstein, 1988). Understanding of compartmental fire behaviour is of importance as it enables the deriving of straight predictions over the impact it has on the structural elements. There has been little which has been done on fuel properties, ventilation and configuration and this remains a setback that need to be solved. The issue of regions with limited ventilations has been discussed in great length by authors Takede and Akita. In there research it was found that increasing the opening area of compartment resulted in a change in the regimes including: stable laminar burning, extinction, unstable oscillation and stable burning that included a possibility of oscillation (Yang, D & Hu, L, 2010). It has been discovered from fire field models there is limited ability to have access to accurately predict thermal conditions and chemical species in ventilated compartment fires. Further, in formal ventilation progress it has shown that if a well ventilated compartment is accessed, with the exception of grunge, field models have been found to perform well in the prediction of temperatures and in proper species if the experiment uncertainities is well accounted for (Merci , B & Vandevelde, 2007; Epstein, 1988; Bishop. et al. 1992 ). With the availability of an inaccurate prediction of an incomplete burning levels thud impacts the calculations derived from radioactive heat transfer and burning rates which are estimated by human tenability’s. High quality which comes in with quantified uncertainty and relatively low temperatures provides measurements of fires gas species from the interior of the under ventilated compartment fires that are needed for guiding the development and also for validation of improved fire fields models. FDS can simulate pre-mixed combustion and explosion due the nature b). Mixture fraction Z is defined as Where - mass fraction of fuel - mass fraction of oxygen - fuel mass fraction in the fuel stream - mass fraction of oxygen at infinity - ratio of oxygen and fuel molecular weight in stoichiometric mixture It is known that =0.94, =0.23 and s = 0.64. Calculate Z on the flame front . Z= = =0.6320 If at some position = 0.78, calculate Z at this position. When use a value that is not given, please explain the reason for taking that value. Z= = =0.5402 Numerical techniques a). Write procedures to numerically solve the 1D unsteady heat conduction equation using explicit scheme and implicit scheme. The overall solution technique may thus be summarized as follows: 1. Form the system of 2N − 2 continuity and momentum equations for h and Q in finite difference form using the Preissman four-point scheme. 2. Set up the two boundary conditions. 3. Solve the system of 2N equations using matrix methods and using current values of A, P, K as initial estimates of A, P, K at the next time step. 4. Using an efficient iterative technique, repeat step 3 with computed values of A, P, K until convergence to the desired level of accuracy is achieved. 5. Repeat steps 1–4 at each time step for the duration of the unsteady flow event. b). Consider a thin insulated rod 0.11 m long with k = 0.835×10-4 m2/s. Let Δx = 0.022 m and Δ t = 0.1 seconds. At t=0 the temperature of the rod is zero. If one of the two ends is maintained at a temperature of zero and the other end is raised to a constant temperature 24°C immediately after 0s. Calculate the temperature distribution at t = 1 sec. = 0.835×10-4 m2/s Then = 0.835×10-4 m2/s x =0.0173 Number of time steps= = = 10 The boundary conditions Setting and in Equation (7) gives the temperature of the nodes inside the rod when time, . = 0.4152 = 0.8447 Part 2 Domains and Meshes A domain has dimensions of 18m by 12m by 9m in the x, y and z directions, respectively, write appropriate lines of code for each of the following: a). Please draw a figure to show the original point of your coordinate system and the domain in your coordinate system. Using a single mesh, specify a uniform cell size of 0.1m using FDS instructions. How many cells does the mesh contain? x: 18m (-9.0m - +9.0m) dx: 0.1m (180 cells) y: 12m ( -1.0m - +12.0m) dy: 0.1m (120 cells) x: 18m (-9.0m - +9.0m) dx: 0.1m (180 cells) y: 12m ( -0.1m - +11.8m) dy: 0.1m (30 cells) geometry: x: -8.0m - +8.0m (inside walls) y: -0.1m - +11.0m (inside walls) &MESH IJK=180,30,1, XB= -9,9, -0.1,11.9, 0.1,0.4, ID='MainEvacGrid'/uniform mesh 0.1*0.1 b).Split the domain into 3 meshes along the x axis. Specify a uniform cell size of 0.1m for the central mesh. Specify a cell size of 0.2m in the x and y direction and 0.1m in the z direction for the two neighbouring meshes. Meshes should be given approximately equal physical dimensions. How many cells does each mesh and the domain contain? x: 18m (-9.0m - +9.0m) dx: 0.2m (90 cells) y: 12m ( -1.0m - +20.0m) dy: 0.2m (60 cells) x: 18m (-9.0m - +9.0m) dx: 0.1m (180 cells) y: 12m ( -0.2m - +11.8m) dy: 0.1m (30 cells) geometry: x: -42.0m - +42.0m (inside walls) y: -0.0m - +19.0m (inside walls) &MESH IJK=90,30,1, XB= -9,9, -0.2,11.8, 0.1,0.4, cell size =.TRUE., cell size =.TRUE., cell size _Z_OFFSET=0.2, ID='MainEvacGrid'/ center cell size mesh 0.2*0.1 &MESH IJK=90,30,1, XB= -9,9, -0.2,11.8, 0.1,0.4, cell size =.TRUE., cell size =.TRUE., cell size _Z_OFFSET=0.2, ID='ExitEvacGrid'/exit mesh 0.1*0.1 c).Discuss the importance of cell size in CFD. How to do cell sensitivity analysis? (2 marks) The CFD models involves the division of the compartment in numerous control cells and through application of the model it is possible to calculate the heat and fluid flow occurring between each cell through use of fundamental physics equations. The number of cells which is used has a considerable effect on the results obtained. In is always desirable to have a large number of cells but his would call for more computer resources which will translate to high expenses (Hume, 2009). Halving the size of the grid cells in each direction will result in the doubling of the run time for each dimension in space and time. Changing the dimensions a mesh from a resolution of 4 cm to 2 cm will men better results, however, the reduction in cell size will take sixteen times longer to run. Design fires For each of the following, select an appropriate design fire, provide any assumptions made and justify your selection with reference to suitable documents. In addition, write the appropriate lines of code. a). A sprinkler controlled shop fire specified by heat release rate and TAU_Q. b). An office fire grows continuously from 0s to 900s, starting from a point. c). A fire reproducing the following HRR v Time graph. Comment how heat release rate density affects the input lines of code. Effect of fuel and mesh size A brief description of the modelling There are different stages that have been identified in compartment fires; these are ignition stage, growth stage, flashover stage, and fully developed stage and decay stage. During the Early stages of a fire, the compartment Has no effect on the fire growth and development. As the fire grows the smoke and hot gases produced will form a layer under the ceiling and will start to flow out of the compartment, if the fire continues to grow and the opening is too small to carry away the combustion products at the rate, which they are generated, the upper layer will increase and descend to the floor. The fire may develop and flashover may occur, leading to the compartment full involvement. When the fuel in compartment has been consumed the fire will start to decay until it extinguishes itself due to the lack of fuel (Bradford 2009). I did the experiment 3 times ones when the fuel PMMA size is (15cm X 15cm) and the 2nd time when the fuel size is (20cm X 20cm), the 3rd experiment the size of fuel is (10cm X 10cm). Procedure: The following is the procedure that has to be followed in conducting the experiments. The procedure for each test is the same. All thermocouples are cleaned (in order that the readings could not be affected by soot or dirty) and put back into the fire box through the holes by the side. The thermocouples are connected to the Squirrel data logger, and results recorded. A sample of fuel (PMMA) of the required size is placed on a tray. Some PMMA chips and fine PMMA powder are placed over the fuel sample, to enable the fuel slab to ignite and spread the fire faster through the whole surface of the fuel slab. The fuel is located centrally at a distance of 33cm from the vent opening. The initial mass of fuel PMMA was recorded, Squirrel data logger is started. Throughout the experiment record the mass of the sample and the height of the smoke layer every minute. The smoke extract system is switched on, the fuel is ignited. The vent opening was adjusted to the required size. The Squirrel data logger is stopped when the fire ceases; the smoke extract system is switched off, which is located above the vertical opening of the firebox and the rising smoke (Bradford 2009). Materials Square slabs of PMMA (Polymethyl Methacrylate) are burnt in the small-scale fire compartment. This material is widely used in small-scale compartment fire experiments. The fuel thickness is 1cm and one PMMA samples are burnt, measuring (10cm X 10cm), (15cm X 15cm) and (20cm X 20cm). The mass balance equation: Where and are the mass flow rate of outside ambient air into the compartment and mass flow rate of inside hot gases out of the compartment via the vent opening respectively; is the fuel mass loss rate inside the compartment. Fire heat release rate: The fire heat release rate within the fire compartment,, is the cause for the elevated compartment temperature. The heat release rate from the fire inside the compartment depends on the mass loss rate of the fuel and the air inflow rate into the compartment. The HRR is then calculated using the following equation: Where: = heat release rate (kW) = burning or mass loss rate (kg/sec) = effective heat of combustion (kJ/kg) Results Obscuration of smoke has more cycles in the compartment with no ventilation as compared to those with ventilation that is why there is more soot in the first compartments. This is because the ventilations allow smoke escape from the compartments. If proper ventilation is not provided property may be lost due to collapse as result of pressure from smoke and heat from fire. Smoke is said to be stratified and needs to be cooled down by fresh air and release of heat. Smoke is known to move upward therefore the height of the compartment. The low obscuration or soot formation in the third compartment is due to air movement in the compartment in the interval of small, medium and large fuel size thus drawing into the heated air plume and hot layer. At a small there high formation of soot and visibility decreases as compared to a large , this is due to smoke levels are increasing. When smoke levels increases visibility is reduced. With the growth of the fire a layer will form under the ceiling as a result of the smoke and gases that are generated by the fire. The fire at this point may start flowing out of the compartment and with increased growth of the fire where the opening is small to be able to carry out the products generated during combustion at the rate of production there will be an increase in the upper layer making it to descent to the floor. The figure below shows that as time increased the temperature increased to a certain level before beginning to decrease. It further shows that a large flame had a higher peak for both the experiment temperature and the FDS. The fuel size 0.2 by 0.2 had greatest peak for the experiment and FDS followed by fuel size 0.15 by 0.15. The fuel size 0.1 by 0.1 had a lower peak for both the FDS and experiment. The graph has shown that there is relation between change in temperature of the fire and time the fire has taken to burn to certain level when the temperature begins to come done. There is also relationship between the size of fire and peak of temperature. When the fire is large the temperature recorded was higher. Fig 2: shows The Temperature in the 4th Thermocouple Experiment and FDS vs time(s). Average temperature for the three experiments and FDS vs Time Figure 3 shows Average temperature for the three experiments and FDS vs Time which confirms that as time increases the temperature of the fire increases to optimum then begins to falls. The graph shows that a large fire has higher temperatures but it reaches its peak at earlier time as compared to the small fire. It further shows that a large flame had a higher peak for both the experiment temperature and the FDS. This means that fuel size 0.2 by 0.2 had greatest peak for the experiment and FDS followed by fuel size 0.15 by 0.15. Fuel size 0.1 by 0.1 had a lower peak for both the FDS and experiment. The graph has shown that there is relation between change in temperature of the fire and time the fire has taken to burn to certain level when the temperature begins to come done. There is also relationship between the size of fire and peak of temperature. When the fire is large the temperature recorded was higher. Fig 3: Shows the average temperature for the three experiments and FDS vs Time. Fuel size and average temperature for the three experiments and FDS Fuel size Average temperature Experiment FDS (0.1*0.1) 148.263 115.022 (0.15*0.15) 235.2268 209.19 (0.2*0.2) 338.1522 337.667 Fig 4: Shows the average temperature for the three experiments and FDS. The figure 4 above shows that that a small fire had greater experiment temperature than FDS while large fire had almost the same temperature for FDS and experiment. However one observation can be made that is as the size of the fire increases the average temperature increases. This means that large fuel size will have high temperatures. The observations from figure 6 above largely suggest closely similar values for fuel sizes although some deviations are encountered. At lower values of fuel size though, deviations are observed where the graph follows a steep form which could be due to very high values of heat flux at smaller magnitudes of the ratio of emitter temperature to the FDS temperature. Discussion of the results The fuel size plays an important role in determining peak heat release rate. If the fuel size is small peak heat release rate is lower as compared to larger fuel size. The peak temperature is also influenced by fuel size. This was shown in the three experiments where 12 thermocouples were used to measure heat of combustion. In the first result temperature was observed to be increasing and verity to one thermocouple to another. The lowest peak temperature was 69.78 for fuel size 0.2*0.2. For fuel size 0.25*0.25 the lowest peak temperature 194 while the maximum was 586.5 while corresponding FDS temperature was 383.89. When the time taken to reach the peak was recorded it was found that a small fuel size had lower average temperature as compared to a large fuel size. This is contested with FDS result which showed an upward trend as the fuel size increases. The findings indicate that a larger fuel size will emit heat at a higher rate because of oxygen concentration and fire die out faster unlike a small fuel. Conclusions. The result gotten from the experiments had two major observations that as the fuel size increases the rate of heat generation is high and temperature increase to certain level before it begins fallen down. The other observation have been made is that time varies to different sizes of fuel. Observations from the thermocouple indicate variations of temperatures from the same fuel size, but the trend is similar in all the 12 thermocouples. This experiment has shown how heat is quickly transferred through radiation that involves transfer of heat through emission and absorption of electromagnetic waves called thermal radiation. Radiation does not require any medium to be communicated as compared to the other two forms of heat transfer; making it particularly important and interesting in the study of thermal physics. Thermal radiations are known to be emitted in the range of 0.1 to 100 microns-this includes the wavelength of visible light. This has been measured by heat release rate. References Bishop , S & Drysdale, D (1995) Experimental Comparison With A Compartment Fire Model. International Communications in Heat and Mass Transfer. Bradford T, (2009).Fire Box Experiment in the Laboratory. Bullen ML, Thomas PH (1978). Compartment fires with non-cellulosic fuels. Proc Combust Inst. Doty, S & Turner, CW 2009, Energy management handbook, Fairmont press Inc. Lilburn, GA- USA. Drystlale. Et al (1985). Smoke prcjducticm in tires, Small scale experiments. Fit-oSufity: Scicww utzd Ett~itwritt~. ASTM STP 8X?. T.Z. Harmathy. Ed. (American Society forTesting and Materials. 1985) pp. 285 300. Emmons HW (1997). A universal flow orifice formula. In: NISTIR 6030, vol. 1. Gaithersburg, MD:National Institute of Technology and Standards. Epstein M. (1988). Buoyancy-driven exchange flow through small openings in horizontal partitions. J Heat Transfer. Euler, SD (ed.) 2002, Mine ventilation, Swets & Zeitlinger B.V, Lisse the Netherlands. Holhorn. P.G.. Bishop. S.R.. Drysdale. D.D. and Beard. A.N.. Experimental and tha)retical models ctf flashover. Fire SLifkty Jourtiul (in press). Hume, B, 2009) The Use of CFD Computer Models for Fire Safety Design in buildings Available: http://www.communities.gov.uk/documents/fire/pdf/381249.pdf Last accessed 15th February, 2015 Kim IK, & Ohtani H, 1993. Experimental study on oscillating behaviour in a small-scale compartment fire (short communication). Fire Saf J Kohl, A & Nielsen, R 1997, Gas purification, Gulf publishing company, Houston Texas USA. Kreith, F, Manglik, RM & bohn, SM 2011, Principles of heat transfer, Cengage Learning, Stanford UK Merci , B & Vandevelde, P (2007) Experimental study of natural roof ventilation in full-scale enclosure fire tests in a small compartment . Fire Safety Journal. 42 () p523-535 Novozhilov, V (2001) Computational fluid dynamics modelling of compartment fires. Progress in energy and combustion science. 27 () p611-666 Quintiere JG (1980). Fire behaviour in building compartments. Proc Combust Inst Quintiere JG(2004). A theory for flame extinction based on flame temperature. Fire Mater. Rangwala AS. (2002). Mathematical modeling of low ventilation small-scale compartment fires. MS Thesis,Department of Fire Protection Engineering, University of Maryland, College Park, MD. Rawlins, CA & Phillips, HR 2001, Reduction of in mine heat load 7th. International mine ventilation congress, pp. 381-389. Ringwelski BA (2001). Low ventilation small-scale compartment fire phenomena: wall vents. MS Thesis,Department of Fire Protection Engineering, University of Maryland, College Park, MD,. Takeda H, & Akita K.( 2002). Critical phenomenon in compartment fires with liquid fuels. Proc Combust Ins. Tewarson A. (1973). Some observations on experimental fires in enclosures, part II—ethyl alcohol and paraffin oil. Combust Flame Thomas PH. (1981). Fire modelling and fire behaviour in rooms. 18th Symposium (int.) on combustion, The Combustion Institute, Utiskul , Y & Quintiere, J (2005) Compartment fire phenomena under limited ventilation. Fire Safety Journal. 40 () p367-390 Utiskul Y. (2003).Extensive study of wall-vent compartment fire behavior under limited ventilation. MSThesis, Department of Fire Protection Engineering, University of Maryland, College Park, MD. Wakatsuki K. (2001). Low ventilation small-scale compartment fire phenomena: ceiling vents. MS Thesis, Department of Fire Protection Engineering, University of Maryland, College Park, MD,. Yang, D & Hu, L (2010) Comparison on FDS predictions by different combustion models with measured data for enclosure fires. Fire Safety journal. 45. Read More

Consequently, the Reynolds number for fire and smoke movement within a compartment is close to 105, thus; the total number of cells crucial for solving the movements within a room goes up to the value of 1013. The current super computers have the capacity to attain the grid resolution of 5123 (134,217,728) cells. Thus, the existing computer technology cannot give solutions of such motions The parameters of the LES model used in the FDS software are Heat release rate, Pool size, Radiation model, Radiation mesh and Flow mesh/ b)Based on Kolmogorov’s turbulence theory, explain the mesh resolution required by DNS and LES.

Critically compare their pros and cons. Kolmogorov scale of velocity in homogeneous turbulence depends on the kinematic viscosity coefficient v [m2/s], specific dissipation rate [J/(kg s)] and, maybe, of fluid density [kg/m3]. Obtain the formula for this dependence using ∼⇒ (1/3 Where is tή timescale, u is turbulence intensity and η is small length ratio. Kinematic viscosity coefficient v [m2/s], where it changes is calculated from Reynolds number and it is formula is as follows; Re = = When the two equations are combined, the following formulae are obtained.

The results for the out the formulas is shown below. Time scale is =( )1/2 Kolmogorov scale of velocity: V = Combustion a). combustion model is required in fire simulations as it this model has the capacity of treating the processes of conversion of fuel and oxygen to products and heat and with this makes FDS to have the ability to simulate a fire and the effects it has on its immediate environment in addition to simply the flow of fluid. In this there is utilization of two models: finite rate reaction model and the mixture fraction combustion model (Bullen ML, Thomas PH, 1978).

The finite rate reaction model is the most appropriate in checking for resolutions of DNS calculations when resolving the diffusion of gas species. The occurrence of the reaction is instantaneous when there is the mixing of oxygen and fuel in the cells when the combining of the gas and oxygen fall in Burn zone. On the other hand if the combining of the gas and oxygen happen to fall in the “No Burn” zone there will be mixing of fuel and oxygen but no reaction will occur (Quintiere, 2004; Bishop. et al. 1992).

The occurrence of such a situation is described as a null reaction. In the instantaneous reaction models products that are produced may include CO2 H2O, CO and soot through the combustion process which is in proportion with the rate at which the fuels are being consumed. It is thus appropriate to give the yields of the products bearing in mind the mass of the fuel that has been consumed (Thomas, 1981; Epstein, 1988). Understanding of compartmental fire behaviour is of importance as it enables the deriving of straight predictions over the impact it has on the structural elements.

There has been little which has been done on fuel properties, ventilation and configuration and this remains a setback that need to be solved. The issue of regions with limited ventilations has been discussed in great length by authors Takede and Akita. In there research it was found that increasing the opening area of compartment resulted in a change in the regimes including: stable laminar burning, extinction, unstable oscillation and stable burning that included a possibility of oscillation (Yang, D & Hu, L, 2010).

It has been discovered from fire field models there is limited ability to have access to accurately predict thermal conditions and chemical species in ventilated compartment fires. Further, in formal ventilation progress it has shown that if a well ventilated compartment is accessed, with the exception of grunge, field models have been found to perform well in the prediction of temperatures and in proper species if the experiment uncertainities is well accounted for (Merci , B & Vandevelde, 2007; Epstein, 1988; Bishop. et al. 1992 ).

With the availability of an inaccurate prediction of an incomplete burning levels thud impacts the calculations derived from radioactive heat transfer and burning rates which are estimated by human tenability’s.

Read More