5 combustion products

Chapter 5

Combustion Products in Fires

Table of Contents 1. Introduction................................................................................89 2. State of the Art ..........................................................................89 3. Fuel Chemistry ...........................................................................94 3.1 Stoichiometric Ratio of Fuel to Oxygen .................................94 3.2 Species Yield ..........................................................................95 3.3 Free Burn or Unlimited Air Species Yield..............................95 3.5 Normalized Species Yield .......................................................95 3.4 Maximum Species Yield .........................................................95 3.5 Equivalence Ratio ..................................................................96 3.6 Mass Fraction of Species ........................................................97 3.7 Fuel Mixture Fraction............................................................97 4. Conservation Equation for Species..............................................97 4.1 Control Volume Formulation .................................................97 4.2 Application to a Fire Compartment..................................... 100 5. Prediction of Species Concentration in Compartment Fires: Yield Correlations .................................................................................. 101

6. Validation of the Conservation Equation of Species.................. 104 6.1 Design and Procedure of Fleischmann’s Experiments........... 104 6.2 Compartment Fire Modeling................................................ 110 6.3 Results of the Simulation ..................................................... 111 7. Conclusions............................................................................... 121

5. Combustion Products in Fires

1. Introduction The ability to estimate the combustion products (unburnt or burnt) in a fire compartment is imperative to analyse and predict the possibility of the backdraft phenomenon.

The combustion products released into a compartment may be diluted by air entering the compartment or may escape through the openings. Having a higher quantity of unburnt products accumulated in the compartment increases the risk of the occurrence of backdraft or another rapid spread flame process such as smoke explosions. To quantify the accumulated gases, a mass balance based on the species yield has been developed and implemented in OZone.

Validation using Fleischmann’s experiment is provided (Fleischmann, 1993).

2. State of the Art Understanding the generation of combustion products involves detailed knowledge of the chemical properties of the burning materials. This is very a complex undertaking, because the nature of the combustion products depends on, for a given fuel, the combustion model (flaming, smoldering, thermal degradation), and the availability of air and the addition of chemical agents.

That is the reason why, normally, a fire engineer must rely on measurements, not fundamental theory, to make predictions.

A good review of the existing experiments used for predicting the yield species released when different combustible materials burn in different ventilation conditions is given in Karlsson, 2000. Yield species is defined as the mass of species i produced per mass of fuel burnt (g/g). The species of interest to the fire engineer is often carbon monoxide (CO), carbon dioxide (CO2), oxygen (O2), unburnt hydrocarbons and soot.

The types of experiments carried out in order to obtain the yield species can be divided into: hood experiments and compartment fire experiments.

Hood experiments differ from compartment experiments along the following lines. Obviously, these differences influence the obtained yield species: •

•

The hood setup allows for considerable radiation towards the laboratory space below. However, a real compartment would contain most of the radiation, thus resulting in higher a temperature in the walls and gases.

Consequently, this provokes a higher fuel volatilization rate (for pool fires) than would be expected for an actual compartment fire.

The hood setup results in a lower layer that has an infinite supply of air which is neither vitiated nor heated. In real compartment fire, the air supply is limited by the ventilation openings and by the depth of the upper layer.

89

5. Combustion Products in Fires •

•

The hood experiments did not include any significant ceiling and wall flame jets. These dynamic flame structures enhance mixing of the upper layer in actual compartment fires and extend the flame zone beyond the plume.

The hood experiment correlations were developed from sustained steadystate burning conditions. Actual fires are usually transient events in nature.

Beyler, 1986 was the first to publish major species production rates in a smallscale two-layer environment. He conducted his experiments under a hood. The test revealed a reasonably well-mixed uniform layer both in temperature and chemical composition during the steady-state conditions.

He also calculated the global equivalence ratio (assuming the layer to be wellstirred) by extracting a known amount of gas from the hood to give a constant layer height and by using the measured fuel flow rate and compositions of the upper layer.

Other conclusions found that, for over-ventilated burning conditions, the yields of CO2 and H2O and depletion O2 are at a maximum value, and there is virtually no production of CO, H2 or unburnt hydrocarbon. However, for underventilated conditions, products of incomplete combustion such as CO, H2 and unburnt hydrocarbon are in fact generated.

The term “equivalence ratio” previously introduced tells us if the mixture is found in a stoichiometric (φ = 1) relation or in a lack (φ > 1) or excess (φ < 1) of oxygen relation. This term can also be applied to the plume, φp, or the upper layer, φul (see Section 3: “Fuel Chemistry”).

Figure 5-1 represents the normalised yields of measured chemical species as a function of the equivalence ratio for propane experiments using a 13-cm (o) or 19 cm (x) burner with supply rates corresponding to a theoretical heat release rate ranging from 8 to 32 kW. These results clearly show the generation of incomplete products for under-ventilated conditions (φ > 1). Although if this figure is for propane, the same trends are observed for other types of fuels (Gottuk and Robin, 1995).

Other authors have also carried out hood experiments for obtaining the species yields of different combustible fuels. For example, Toner et al., 1985 and Zukoski et al., 1989 used a cube hood of 1.2 m, insulated on the inside with ceramic fibre insulation board. In their experiments, it was concluded that species concentrations correlated with the upper layer equivalence ratio. His observation on CO production for the under-ventilated fires led them to suggest that the oxidation of CO was “frozen out” before completion. Since the results showed that species production was independent of temperature for the range studied (490-870K), Toner et al. concluded that, if a freeze-out temperature existed, it had to be higher than 900K.

90

(Ď&#x2020; = 1)

(Ď&#x2020; = 1)

5. Combustion Products in Fires

Figure 5-1: Normalised yield of major species for propane as a function of the global equivalence ratio.

91

5. Combustion Products in Fires Zukoski, Morehart et al., 1991 performed a second series of tests similar to Tonerâ&#x20AC;&#x2122;s. The only difference was the collection hood (uninsulated). The correlation obtained deviated from those obtained by Toner et al. For overventilated conditions, Morehart et al. observed higher CO and hydrocarbon yields, signifying that the fires conducted by Morehart et al. burned less completely. For under-ventilated methane fires, Morehart et al. observed lower CO, CO2 and H2O and higher hydrocarbon and O2 concentrations than Toner et al. The only apparent difference between these experiments was that Morehart et al. found that layer temperature were 120 K to 200 K lower for fires with the same equivalence ratio as those observed by Toner et al. (from 488 to 675 K).

Due to the similarity in the experimental apparatus, except for the hood, Morehart concluded that the temperature difference resulted from having a larger uninsulated hood. Figure 5-2 shows the results obtained by Toner and Morehart, respectively.

Under-ventilated

Well-ventilated

Figure 5-2: Carbon monoxide yields as a function of the equivalence ratio for methane fires studied in hood experiments.

Gottuk et al., 1992 and Gottuk, 1992 conducted reduced-scale compartment fire tests in order to determine the yield-equivalence ratio correlation for various fuels burning in a compartment fire. The fuels investigated were hexane, PMMA, spruce, and flexible polyurethane foam. The results of these compartment tests showed quite similar correlations as those observed for Beylerâ&#x20AC;&#x2122;s hood correlation. However, some significant quantitative differences exist in the CO yield correlations. This difference in CO formation can be explained in terms of temperature effects since the temperature range between 800K and 900K is a transition range in which the oxidation of CO to CO2 changes from a very slow to fast reaction. That is the reason why, for temperatures below 800K, the conversion of CO to CO2 does not occur at an appreciable enough rate to affect CO yields. Since the oxidation of fuel first 92

5. Combustion Products in Fires results in the production of CO, which further reacts to form CO2, the low temperature (< 800 K) prevents CO from oxidizing. This results in high CO yields.

The National Institute of Standards and Technology, Building and Fire Research Laboratory, has also performed reduced-scaled compartment fire experiments using a natural gas burner for the heat source with wood-lined compartments. The results showed that for tests in which wood pyrolysis occurred, increased levels of CO were observed. The reason for that high concentration of CO is that, first, the fuel-bound oxygen allows the fuel to generate CO by pyrolysis and, second, due to the preferential oxidation of hydrocarbons over CO, the limited oxygen in the upper layer reacts with the pyrolising wood to form additional CO. Tewarson collected a vast amount of data from experiments carried out in a bench-scale test apparatus called the flammability apparatus. In Tewarson, 1995 reports species yields for CO2, CO and soot for well-ventilated fires (Ď&#x2020; < 1). He found that the former values were relatively constant for a given fuel and are usually slightly lower that the maximum possible yield (due to the fact that combustion in nearly never 100% efficient). He has also reported some data on yields of CO, HCl, and H2 for a number of fuels for under-ventilated conditions (Ď&#x2020; > 1). The yields are a strong function of the equivalence ratio (that depends very strongly on the availability of oxygen) and a single yield value for underventilated fire is seldom. Table 5-1 represents some typical combustion fuel yields for various fuels (Karlsson, 2000).

Originally, these studies were focused on estimating the toxic hazards of combustion gases in fire compartments. Most notably, CO production is of primary importance due to its toxicity. That is the reason why there is much information and many correlations on estimating the CO yield for different fuels and ventilation conditions. Yields of H2O, CO2 and unburnt hydrocarbons are also found in the literature for several fuels. A considerable collection of such data is given in the appendices to the SFPE Handbook of Fire Protection Engineering.

Fuel

yCO2 [g/g]

Well-Ventilated yCO [g/g]

Propane Acetylene Ethanol Heptane Wood PVC

2.85 2.6 1.77 2.85 1.33 0.46

0.005 0.042 0.001 0.01 0.005 0.063

yHCl [g/g] ----------0.5

Under-Ventilated yCO yH2 [g/g] [g/g] 0.23 --0.22 --0.14 0.4

0.011 --0.0098 --0.0024 ---

Table 5-1: Typical product yields for various fuels.

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5. Combustion Products in Fires

3. Fuel Chemistry Some important terms and concepts necessary for understanding the chapter are explained below.

3.1 Stoichiometric Ratio of Fuel to Oxygen The stoichiometric fuel to oxygen ratio of a combustion reaction, r, represents the quantity of mass of oxygen needed for combusting one unit of mass of fuel.

As an example of how to obtain r, let’s suppose that the combustion chemistry of a cellulosic material (C4H6O3) is simplified to a single chemical reaction, Eq. (5-1).

C4 H6O3 + 4O2 → 4CO2 + 3H2O

(5-1)

Considering the mass of each molecule, the mass balance of Eq. (5-1) can be written as: 102 + 128 ⇒ 176 + 54

(5-2)

The burning of wood can be simplified into Eq. (5-3) stating that, in a fire, 1.0 kg of wood plus 1.3 kg of oxygen gives 2.3 kg of combustion products and releases an energy of Hc Joules.

1 kg of fuel + 1.3 kg of 02 = 2.3 kg of combustion products + Hc J

(5-3)

This reaction can be generalised to any other fuel by introducing the stoichiometric ratio r of the oxygen requirement of the fuel, Eq. (5-5).

1 kg of fuel + r kg of 02 = (1 + r) kg of combustion products + Hc J

(5-5)

For wood, the oxygen/fuel stoichiometric ratio is 1.3. As the oxygen fraction in air is about 23%, the air/fuel stoichiometric ratio for wood is 5.6. In Table 5-2 some examples of fuel properties are given. Other values can be found in various publications (Drysdale, 1999; Karlsson, 2000; SFPE, 1995).

The ratio fuel to oxygen (or air) can be applied not only to stoichiometric combustion but also to combustion with lack or excess of oxygen (or air).

94

5. Combustion Products in Fires

Molecular Weight Fuel [g/mol] Ethanol 46 Propane 44 Methane 16 Nylon 43 Heptane 100 Polyvinilchloride (PVC) 62.5 Polymethylmethacrylate 100

1/r [-] 0.480 0.276 0.250 0.428 0.284 0.710 0.521

Table 5-2: Example of fuel properties

3.2 Species Yield Species yield i is defined as:

yi =

mi mf

(5-6)

Where mi is the mass of species i produced and mf is the mass of the gaseous fuel supplied, or the mass lost in gasification. Inert species and retardant can be included in mf.

Note that the oxygen yield would have a negative yield since it is consumed.

3.3 Free Burn or Unlimited Air Species Yield This yield is denoted by yi,â&#x2C6;&#x17E; and is to be taken as the value of species yield in well-ventilated conditions, yi,wv, which is invariably measured under ample air supply. It depends on fuel and on the burning configuration.

3.5 Normalized Species Yield The normalized yield of species i is the yield divided by the unlimited air yield, yi/yi,â&#x2C6;&#x17E;.

3.4 Maximum Species Yield This is the maximum theoretical yield of species i, denoted yi,max. These values are very easily calculated from stoichiometry. Table 5-3 gives the values for some materials.

95

5. Combustion Products in Fires

Fuel Ethanol Propane Nylon Heptane Wood Polyvinilchloride (PVC) Polymethylmethacrylate

YCO2,max 1.91 3.00 2.32 3.08 1.40 1.42 2.2

YO2,max 2.09 3.64 2.61 3.52 1.13 1.42 1.92

YCO,max 1.22 1.91 1.48 1.96 0.89 0.903 1.4

Table 5-3: Typical combustion product yields for various fuels.

3.5 Equivalence Ratio This ratio is defined in Eq. (5-7):

mf φ=

mO2 r

(4-7)

where mf is the available fuel mass in the mixture, mO2 is the available oxygen in the mixture and r is the ideal reaction stoichiometric mass with regard to the fuel to oxygen ratio necessary for complete combustion.

There are three possible conditions for the equivalence ratio: • • •

φ<1: lean mixture. There is excess air. CO or H2 is not formed. φ=1: stoichiometric mixture. Only CO2, H2O and N2 are formed. φ>1: rich mixture. Combustion is incomplete, CO and H2 are produced due to the CO2 + H2 → CO + H2O reaction.

The equivalence ratio can be applied to the upper layer and to the plume, as shown in Eq. (5-8) and Eq. (4-9), respectively: m ful φul =

r m fp

φp =

mO2ul

mO2p r

(5-8)

(5-9)

where m ful is the available fuel mass in the upper layer, mO2ul is the available oxygen in the upper layer, m fp is the available fuel mass in the plume, mO2p is the available oxygen in the plume and r is the ideal reaction stoichiometric mass with regard to the fuel to oxygen ratio necessary for complete combustion.

96

5. Combustion Products in Fires One should observe that the equivalence ratio could be also calculated in terms of air by replacing mO2 with mair and by recalculating r to give the stoichiometric fuel/air ratio instead of the fuel/oxygen ratio.

3.6 Mass Fraction of Species This is defined as: Yi =

mi m

(5-10)

where m is the total mass of the gaseous mixture and mi is the mass of the species i.

3.7 Fuel Mixture Fraction This is defined as:

f =

φ 1 φ+ r

(5-11)

where φ is the equivalent ratio defined in Eq. (5-7) and r is the ideal reaction stoichiometric mass with regard to the fuel to oxygen ratio necessary for complete combustion. It can be observed how φ and f are related. Note that f ranges from 0 to 1, while φ ranges from 0 to infinity for pure oxygen to pure fuel, respectively.

4. Conservation Equation for Species The conservation equation for each species as a function of the yield species is developed below with the purpose of calculating the accumulated gas inside a fire compartment.

4.1 Control Volume Formulation The conservation equation for each species will be calculated for the control volume, CV, defined in Figure 5-3. To use a more general approach, the control volume is assumed to be moving at the local velocity, w (x, y, z, t). This velocity is different from the bulk fluid velocity, v , and the diffusion velocity of each species, V . The latter is due to molecular diffusions arising from a concentration difference in the species (Karlsson, 2000).

The conservation of species i states that:

97

5. Combustion Products in Fires

Rate of change  Rate of production      Net rate of  Mass loss rate   of the mass of species    of the mass of   + mass flow of i = − due to surface     species i in   i due to chemical         leaving the CV   deposition     reaction  the CV         (5-12) This equation can be written mathematically as Eq. (5-15) by taking into account: • •

Fick’s law, Eq. (5-13), where D is the diffusion coefficient of species i in the mixture, ρi is the species density and Yi is the mass fraction of species i .

That the mass flux species i across a boundary can be due to bulk flows as well as diffusion; the mass flow rate of species i flowing through surface dS is given by the species moving in the normal direction as in Eq. (5-14)

ρi Vi = −ρD∇Yi

(5-13)

ɺ i,dS = ρi ·( v + Vi − w i )·ndS m

(5-14)

d ρYi dV + ∫∫ ρYi ( v + Vi − w i )·ndS = dt ∫∫∫ CV CS

∫∫∫ y mɺ ′′′dV − mɺ i

f

i,loss

(5-15)

CV

The first term on the right of Eq. (5-15) is expressed in terms of yield and the ɺ '''f . The last term of this expression represents fuel loss rate per unit volume, m the loss due to surface deposition or settling of particles.

98

5. Combustion Products in Fires

V , diffusion of species i n , normal vector v , bulk velocity W, CV velocity

Yi

Yi,j

Deposition of

CV

particles Settling of particles

Wall

Figure 5-3: Conservation species in a general control volume, CV.

Surface, dS

( v + V â&#x2C6;&#x2019; w ), relative velocity of species i to the moving surface normal vector N, normal vector

Figure 5-4: Mass flux of specie i through a surface.

99

5. Combustion Products in Fires

4.2 Application to a Fire Compartment Eq. (5-15) has been adapted in order to apply it to fire compartments. For this purpose, the following assumptions are made: • • • •

The control volume is considered to be equivalent to the total compartment volume, one-zone ( w = 0.0).

The control volume is assumed to have uniform properties, i.e. Yi not dependent on x, y, z.

Any number of openings can be present in the compartment.

Thermal and mass diffusion is neglected in this analysis. Wall soot deposition is likewise not considered.

The fire compartment considered is shown schematically in Figure 5-5.

CV

ɺ out m ρ T p Yi

ɺ in m

ɺf m

Figure 5-5: Control volumes selected in zone modeling.

Thus, Eq. (5-15) can be rewritten as Eq. (5-18), since the mass in the CV and the net mass flow rate out the CV can be expressed by Eq. (5-16) and Eq. (517), respectively. m=

∫∫∫ ρdV

(5-16)

ɺ = m

∫∫ ρ·v·ndS

(5-17)

d ( mYi ) + dt

N

∑

j=1 net flow

ɺ jYi,j = y i m ɺf −m ɺ i,loss m

(5-18)

ɺ i,loss now contains all of the diffusion and deposition loss terms. The first where m term on the left of Eq. (5-18) represents the variation of mass of species i and the second term on the left represents all of the mass flow rates of species i in 100

5. Combustion Products in Fires the bulk flow leaving (-) or entering (+) the CV. Yi,j represents the ith species leaving or entering in the jth stream.

Arranging Eq. (5-18), we obtain: d ( mYi ) + dt

N

∑

j=1 net flow

ɺ out, jYi, j − m

N

∑

j=1 net flow

ɺ in, jYi, j = y im ɺf m

(5-18)

Assuming quite reasonably that the mass fraction of species “i” flows out of the compartment, we then obtain: d ( mYi ) + dt

N

∑

j=1 net flow

ɺ out,jYi − m

N

∑

j=1 net flow

ɺ in, jYi = y i m ɺf m

(5-19)

ɺ out, j is the mass flowing out of the compartment per unit of time, m ɺ in, j where m is the mass flow rate drawn into the compartment per unit of time through the opening j, and Yi is the mass fraction of species i in the well-mixed compartment.

Eq. (5-19) gives the mass balance equation that enables us to calculate the mass fraction of species i in a compartment.

5. Prediction of Species Concentration in Compartment Fires: Yield Correlations In light of experimental work and chemical kinetics, several correlations can be used as a guideline for predicting yield species. The production of chemical species in compartment fires has been shown to correlate best with the global equivalence ratio.

Assumptions of the model: • • •

For φ<1 [well-ventilated conditions], all of the hydrogen (H) of the combustible fuel becomes H2O and all the carbon (C) goes to CO2.

For φ>1 [under-ventilated conditions], all of the excess fuel is considered to be local hydrocarbon (HC).

Although the theoretical maximum yield of CO and H2 is based on all the C and H forming these compounds only, in the ideal complete reaction, no CO and H2 form.

These assumptions allow us to write the equation for normalized yields (in the ideal case of a complete reaction) in terms of unlimited air yields of species (yi,∞). Since the yields of H2O, CO2 and O2 are constant and at a maximum for φ<1 (values empirically justified), then it follows that:

101

5. Combustion Products in Fires

yCO2 yCO2 ,∞

y H 2O

=

y H2O,∞

=

yO2 yO2 ,∞

=1

(5-20)

yCO = y H2 = y HC = 0

(5-21)

For φ>1

yi B = i y i,∞ φ y HC = 1 −

(5-22) 1 φ

(5-23)

Suggested average yields coefficients for compartment fires of elevated temperatures (T>900K) are 0.88 for BCO2, 0.97 for BO2, and 1 for BH2O. Suggested values for low temperatures (T<800K) are 0.77 for BCO2, 0.92 for BO2, and 0.95 for BH2O. It should be noted that the above are ideal results, assuming no production of CO and H2. To include the production of CO, there are four correlations that represent varying degrees of complexity (SFPE Handbook of Fire Protection Engineering, 2nd ed. Chapter 2, pp. 65).

A simple correlation for the data could be written:

yCO = 0

for φ < 1

(5-24)

yCO = 0.21

for φ > 1

(5-25)

Anther simple correlation is to consider the yields of CO as 1/10 times those of CO2 at free burning. Thus, yCO =

yCO2 ,∞

(5-27)

10

Another correlation is represented by Eqs. (5-26), (5-27) and (5-28), which accounts for some of the temperature effects by including a linear rise in CO yield over the transition region of φ from 0.5 to 1.2.

yCO = 0

for φ < 0.5

(5-26)

yCO = 0.3φ − 0.15

for 0.5 < φ < 1.2

(5-27)

yCO = 0.21

for φ > 1.2

(5-28)

102

5. Combustion Products in Fires The temperature effect on CO production is best represented in the following correlations. Eq. (5-29) is suggested for compartment fires with an average temperature below 800K. Eq. (5-30) is used for fires with an average temperature above 900K. These correlations were fitted to hexane data of Beyler’s hood experiments; however, they can be used for other fuels. yCO =

0.19 tan −1 (10 ( φ − 0.8 ) ) + 0.095 180

for T < 800K

(5-29)

yCO =

0.22 tan −1 (10 ( φ − 1.25 ) ) + 0.11 180

for T > 900K

(5-30)

Example:

A pool of propane is burning in a compartment, and the radiation to the pool surface results in a mass flow rate of 0.1 kg/s. The mass flow rate of air is 0.9 kg/s. Estimate the yield of CO and CO2 in the upper layer (see Figure 5-6).

0.1 kg/s

0.9 kg/s

Figure 5-6: Steady-state fire in a compartment with ceiling ventilation.

The stoichiometric fuel-oxygen ratio for propane is 0.276 (from Table 5-2). Since the mass fraction in the air is 23%, the mass flow rate of oxygen is 0.9·0.23 = 0.207 kg/s.

Knowing this, the equivalence ratio can be calculated as follows:

φ=

0.1

0.207 = 1.75 0.276

(5-31)

The unlimited yield of CO2 is 3.00 [g/g], from Table 5-2. Eq. (5-22) gives the CO2 yield as yCO2 = 3.00 / 1.75 = 1.71 [g/g] and Eq. (5-28) gives the CO yields as yCO = 0.21 g/g.

103

5. Combustion Products in Fires

6. Validation of the Conservation Equation of Species Fleischmann, 1993 in his work “Backdraft Phenomena” conducted several backdraft experiments in which the mass concentration of species such as CO2, CO and hydrocarbon accumulated in the compartment were recorded.

These data are now used to validate the conservation equation of species implemented in OZone. Further information about OZone (sub-models, governing equations, etc.) is given in Chapter 11: “Implementation in OZone”.

Having good results in this section in essential for being able to analyse and predict a backdraft since this phenomenon is governed by the kind of mixture in the compartment just before creating the opening.

This clause is divided into three parts. The first deals with the experimental apparatus used by Fleischmann. The second part deals with the input data with which the species concentrations are calculated by OZone. Finally, the last part shows and compares the results.

6.1 Design and Procedure of Fleischmann’s Experiments In this work, the experiments were conducted in a small-scale compartment.

Figure 5-7 shows a schematic of the compartment giving its internal dimensions and the locations of the instrumentation. The interior surfaces were linked by a 50 mm thick refractory fibre blanket installed over the gypsum wallboard on the walls and ceiling. This insulation allowed for repeated experiments without the need to rebuild the compartment.

To simulate a window or door, a 0.4 m high by 1.1 m wide opening was centred on the short wall opposite the burner. This opening was covered with a hatch which was opened after the fire had been burning for several minutes. A methane burner, 0.3 m square and 0.3 m high, was used in all of these experiments. A pilot flame was used to ignite the burner and was turned off 10 s after the start of each experiment. The primary ignition source for the backdraft was a spark igniter located 0.45 m above the floor and centred over the top of the burner.

Every effort was made to seal all the construction holes to control leakage. The primary source of leakage into the compartment was found to be around the pressure relief panel and the opening hatch. Gaskets made of refractory fibre blanket were compressed around the edges of these openings to reduce the leakage. A small 0.1 m diameter pressure relief vent was placed at floor level to relieve the pressure from the initial burner ignition. Without this vent, a rise in pressure sufficient to activate the pressure relief panel was produced. A computer controlled cover closed over this vent 15 s after ignition.

In order to characterize the compartment condition prior to backdraft, the species histories in the upper layer were recorded. Gas concentrations measured 104

5. Combustion Products in Fires were: oxygen (O2), carbon dioxide (CO2), carbon monoxide (CO) and hydrocarbon (HC).

The experimental parameters are summarized in Table 5-4 and Table 5-5.

Column 1 and 2 represent the burner characteristics, i.e. the burner flow rate and the time the burner gas is flowing. Column 3-5 gives the compartment species concentration at opening for hydrocarbon (HC), carbon monoxide (CO), total combustible gas (FUEL = HC + CO), carbon dioxide (CO2) and oxygen (O2), respectively. Columns 8 and 9 give the lower layer temperature and the upper layer temperature. Column 10 provides the run name which corresponds to the data given in Annex II.

Burner

1.2 m

1.2 m TC tree

2.4 m Pressure relief panel Opening hatch

Bidirectional probes Leakage vent

Figure 5-7: Diagram of the Fleischmannâ&#x20AC;&#x2122;s compartment.

Experiments were conducted using a 70 kW and 200 kW fire source. In the 70 kW experiment, the flow rate presents some minor fluctuations as can be seen in Column 1 of Table 5-4. Burn times ranged from 295 s to 775 s. Times greater than 775 s were felt to be too dangerous to attempt safely (Fleischmann, 1993).

In these experiments the flame dies out at about 170 s. Burn times for the experiments conducted using a 200 kW fire source vary from 115 s to 235 s, while the flame dies out at about 130 s.

105

Fuel Flow [kW] 72 72 72 72 69 77 69 69 73 71 68 70

Burner Time [s] 295 355 415 475 535 535 555 595 655 715 715 775

YHC [%] 0.10 0.12 0.14 0.16 0.16 0.2 0.19 0.19 0.21 0.20 0.22 0.22

YCO [%] 0.005 0.004 0.004 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.003 0.002

YFUEL [%] 0.105 0.124 0.144 0.163 0.163 0.203 0.193 0.193 0.213 0.203 0.223 0.222

YCO2 [%] 0.07 0.06 0.06 0.05 0.05 0.05 0.05 0.04 0.04 0.04 0.04 0.04

YO2 [%] 0.09 0.11 0.11 0.11 0.11 0.11 0.11 0.12 0.12 0.11 0.12 0.12

Tul [K] 417 390 379 362 377 363 359 363 350 348 347 344

Tl [K] 378 361 353 339 356 344 340 346 331 332 332 330

Run Name P3EXP38 P3EXP36 P3EXP35 P3EXP34 P3EXP33 P3EXP45 P3EXP32 P3EXP42 P3EXP39 P3EXP40 P3EXP43 P3EXP41

Table 5-4: Summary data from 70 kW backdraft experiments showing burner characteristics, species concentrations at opening and idealised layer temperature.

Fuel Flow [kW] 200 200 200 200 200

Burner Time [s] 115 145 175 205 235

YHC [%]

YCO [%]

YFUEL [%]

YCO2 [%]

0.13 0.10 0.24 0.29 0.29

0.012 0.012 0.009 0.008 0.007

0.142 0.112 0.249 0.298 0.297

0.09 0.1 0.07 0.06 0.06

YO2 [%] 0.04 0.04 0.05 0.06 0.06

Tu [K] 517 570 474 447 433

Tl [K] 445 475 427 408 400

Run Name P3EXP26 P3EXP30 P3EXP27 P3EXP28 P3EXP29

Table 5-5: Summary data from 200 kW backdraft experiments showing burner characteristics, species concentrations at opening and idealised layer temperature.

5. Combustion Products in Fires

6.2 Compartment Fire Modeling The input data used in the simulation are the following: â&#x20AC;˘

The model assumes that fire develops in one zone.

â&#x20AC;˘

All the partitions of the compartment consist of one layer of gypsum and one layer of ceramic blanket. The properties are summarized in Table 56.

Material Gypsum Ceramic fibre

Thickness [cm] 3.2 5.0

Unit mass Conductivity Specific heat [kg/m3] [W/mK] [J/kgK] 900 0.25 1000 60 0.03 1030

Table 5-6: Properties of the partition of the compartment.

External side Gypsum Fibre Internal side

Figure 5-8: Detail of the partitions. External and internal sides. â&#x20AC;˘

Three openings are considered. The first one corresponds to the opening hatch, the second corresponds to the pressure relief vent and the third is introduced for purpose of considering other leakages in the compartment.

Their dimensions and initial state are summarized in Table 5-7.

Opening Hatch Pressure relief vent Leakage vent

Initial state Close Open Open

Final state Open Close Open

Sill [m] 0.4 0.0 0.0

Soffit [m] 0.800 0.125 0.005

Width [m] 1.100 0.125 0.090

Table 5-7: Dimensions and initial state of the openings.

The hatch opening changes from closed to open 5.0 s after the burner is switched off. The burner time is shown in Table 5-4 and Table 5-5. For the pressure relief vent, it is closed 5.0 s before the burner time. OZone does not permit the use of circular vents. Therefore, to simulate this vent 110

5. Combustion Products in Fires a rectangular one with the same area is considered. The leakage vent has been defined considering a gap of 0.20 mm along the edges of the openings. â&#x20AC;˘

The species considered are carbon dioxide (CO2), carbon monoxide (CO), water (H2O), nitrogen (N2), oxygen (O2) and methane (CH4). For the CO yields the correlations given in Eq. (5-26), (5-27) and (5-28) are chosen.

For the other species Eq. (5-20), (5-21), (5-22) and (5-23) are used with an average yield coefficients of B = 0.9.

â&#x20AC;˘

The fire source was a methane gas burner, 0.09 m2. The combustion heat of methane is considered to be 50.0 kJ/g (Drysdale, 1999). For the experiments with a flow rate of about 70 kW, the flame is set to die out at 170 s from the beginning of the fire and 130 s for the experiments with a flow rate about 200 kW.

6.3 Results of the Simulation A comparison for experiment PEXP41 (70 kW) is shown from Figure 5-9 to Figure 5-12. Figure 5-9 represents the mass fraction of the different species accumulated in the compartment during the experimental. Figure 5-10 shows the mass fraction obtained by OZone. Figure 5-11 gives the idealized two-zone upper layer and lower layer temperatures and Figure 5-12 represents the average temperature of the simulated compartment.

HC

O2 CO2 CO

Figure 5-9: Species concentration histories from backdraft experiment PEXP41 (70 kW).

111

5. Combustion Products in Fires

0.25 CO CO2

0.2

[% mass]

H2O HC

0.15

O2 0.1

0.05

0 0

60

120

180

240

300

360

420

480

540

600

660

720

780

840

Time [s]

Figure 5-10: Species concentration obtained by OZone from backdraft experiment PEXP41 (70 kW).

Figure 5-11: Idealized two zone upper layer (-) and lower layer (--) histories from a PEXP41.

112

5. Combustion Products in Fires

850

750

[K]

650

Average gas temperature in the compartment

550

450

350

250 0

60

120

180

240

300

360

420

480

540

600

660

720

780

840

Time [s]

Figure 5-12: Average temperature computed by OZone for backdraft experiment PEXP41 (70 kW).

It may readily be observed how the O2 concentration drops as the fire consumes the available O2 while the CO2 concentration increases as a result of the combustion. At approximately 80 s, the compartment becomes ventilationcontrolled. From 80 s to 170 s the average temperature in the compartment also drops as the fire diminishes. Fluctuating temperatures present in the experiments (see Figure 5-9) was not predicted by OZone.

Over the same time period the HC starts to be released and its concentration rises as well as the CO, CO2 and H2O concentrations. After 170 s the flames die off and the compartment starts to cool exponentially. From this moment on, the oxygen concentration increases as the air leaks into the compartment.

Obviously, concentrations of CO, H2O and CO2 have the opposite effect. As the burner is not off until 775 s, the concentration of HC continues to increase.

At 780 s the hatch is opened and the gas concentration of each species, except for O2, drops. The ignition of the mixture is not simulated here, which is why figures present a different evolution from this moment of time on.

Figure 5-13 to Figure 5-16 represent the same results but for backdraft experiments of 200 kW, (PEXP29). Figure 5-13 and Figure 5-14 shows the species mass fraction for O2, CO, CO2 and HC in the upper layer from the experiments and OZone, respectively. Figure 5-15 and Figure 5-16 show the temperature evolution in the compartment.

A phenomenon worth remarking in this experiment is the reduction of the HC concentration between 130 s and 180 s. This is due to the appearance of dancing flames at the spark that move around the floor of the compartment, consuming hydrocarbons (Fleischmann, 1993).

113

5. Combustion Products in Fires

Figure 5-13: Species concentration histories from backdraft experiment PEXP29 (200 kW).

0.3 CO2

0.25

H2O

[Mass fraction]

HC 0.2

O2 CO

0.15

0.1

0.05

0 0

60

120

180

240

300

Time [s]

Figure 5-14: Species concentration obtained by OZone from backdraft experiment PEXP29 (200 kW).

114

5. Combustion Products in Fires

Figure 5-15: Idealized two-zone upper layer (-) and lower layer (--) histories from PEXP29.

850 800 750 700 650

[K]

600 550 500 450 400 350 300 250 0

60

120

180

240

300

Time [s]

Figure 5-16: Average temperature computed by OZone for backdraft experiment PEXP29 (200 kW).

The results obtained with OZone are summarized in Table 5-8. Columns1 and 2 represent the burner characteristics, i.e. the burner flow rate and the time the burner gas is flowing. Columns 3-5 show the compartment species concentration at the opening for hydrocarbon (HC), carbon monoxide (CO), water (H2O), carbon dioxide (CO2) and oxygen (O2), respectively. Column 8 gives the average temperature, while Column 9 gives the run name which corresponds to the data given in Annex II. 115

Fuel Flow [kW] 72 72 72 72 69 77 69 69 73 71 68 70

Burner Time [s] 295 355 415 475 535 535 555 595 655 715 715 775

YHC [%] 9.39 11.2 13.0 14.5 15.3 17.2 17.2 17.2 19.0 19.6 18.7 20.4

YCO [%] 1.14 1.01 0.92 0.77 0.72 0.74 0.70 0.73 0.66 0.61 0.63 0.57

YH2O [%] 5.7 5.1 4.7 4.2 3.9 3.8 3.8 3.6 3.3 3.1 3.1 2.9

YCO2 [%] 7.8 6.9 6.3 5.3 4.9 5.1 4.8 5.0 4.5 4.2 4.3 3.9

YO2 [%] 8.3 9.2 9.8 10.1 10.7 10.3 10.5 11.0 11.1 11.5 11.6 11.7

Tu [K] 422.36 409.75 399.51 391.32 384.01 385.64 382.15 379.46 375.28 370.06 372.50 366.83

Run Name P3EXP38 P3EXP36 P3EXP35 P3EXP34 P3EXP33 P3EXP45 P3EXP32 P3EXP42 P3EXP39 P3EXP40 P3EXP43 P3EXP41

Table 5-8: Summary data from 70 kW backdraft simulation showing burner characteristics, species concentrations at opening and average gas temperature.

Fuel Flow [kW] 200 200 200 200 200

Burner Time [s] 115 145 175 205 235

YHC [%] 13.602 16.673 19.692 23.646 27.689

YCO [%] 1.32 1.18 1.09 1.00 0.93

YH2O [%] 7.58 6.809 6.273 5.74 5.347

YCO2 [%] 9.011 8.094 7.456 6.824 6.354

YO2 [%] 4.198 4.857 5.236 5.494 5.424

Tu [K] 498.77 470.358 453.611 440.655 431.816

Run Name P3EXP26 P3EXP30 P3EXP27 P3EXP28 P3EXP29

Table 5-9: Summary data from 200 kW backdraft simulation showing burner characteristics, species concentrations at opening and average gas temperature.

5. Combustion Products in Fires A more convenient examination of the computed results could be made by means of the following diagrams, which compare the species concentration of CO2, O2 and HC computed by OZone and recorded in tests at opening the hatch.

For the experiments at 70kW:

1.0

24.0 R elative error [% ]

20.0 16.0 12.0 8.0 4.0

0.8 0.6 0.4 0.2

3 P4

9 P3

2 P3

P3

EX

EX

P3

P3

5

P3

1.0

14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0

0.8 0.6 0.4 0.2

3

9

P4 P3 E

P3 E

X

X

X

P3

P3

3 P3 E

X P3 E

P3 E

O2concentration test vs. OZone

P3

5

14.0

P3

12.0

X

10.0

8

8.0

Oxygen concentration [tests]

P3 E

6.0

P3

4.0

X

2.0

2

0.0 0.0

O2 relative error: test vs. OZone

8.0 7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0

1.0 Relative error [%]

0.8 0.6 0.4 0.2

CO2 concentration: test vs. OZone

3

9

P4 EX

P3

P3

EX

P3 EX

P3

P3

2

3

8.0

P3

7.0

P3

6.0

EX

5.0

P3

4.0

P3

3.0

CO2 concentration [tests]

EX

2.0

8

1.0

P3

0.0

5

0.0

EX

CO2 concentration [OZone]

EX

EX P3

CH4 relative error: test vs. OZone Relative error [%]

Oxygen concentration [OZone]

CH4 concentration test vs. OZone

P3

24.0

EX

20.0

P3

16.0

P3

12.0

8

8.0

Methane concentration [tests]

EX

4.0

P3

0.0

3

0.0

0.0

P3

Methane concentration [OZone]

Along the x-axis of Figure 5-17-(a), the species concentration recorded experimentally is represented. The y-axis shows the species concentration computed by OZone. Figure 5-17-(b) represents the relative error between the test results and those calculate using OZone.

CO2 relative error: test vs. OZone

118

2.0

1.0 R elative error [% ]

1.5 1.0 0.5

0.8 0.6 0.4 0.2

0.0

0.0

3 P4

9 P3

EX

P3

2 EX P3

EX

P3

P3

P3 P3

EX P3

3

0.6

P3

0.5

EX

0.4

5

0.3

P3

0.2

CO concentration [tests]

P3

0.1

8

0.0

EX

CO concentration [OZone]

5. Combustion Products in Fires

CO concentration: test vs. OZone

CO relative error: test vs. OZone

(a)

(b)

Figure 5-17: (a) species concentration from OZone and test comparison; (b) absolute relative error. (70 kW experiments).

For the experiments at 200 kW:

28.0 Relative error [%]

1.0

21.0 14.0 7.0

0.8 0.6 0.4 0.2

P3 EX

P2 8 P3 EX

CH4 relative error: test vs. OZone

7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00

1.0 Relative error [% ]

0.8 0.6 0.4 0.2

O2 concentration: test vs. OZone

9 P3

EX

P2

8 P3

EX

P2

7 P2 EX

7.00

P3

6.00

P3

5.00

P3

4.00

EX

3.00

P3

2.00

Oxygen concentration [tests]

6

1.00

P2

0.00

0

0.0

EX

Oxygen concentration [OZone]

CH4 concentration: test vs. OZone

P2 7

28.0

P3 EX

21.0

Methane concentration [tests]

P3 0

14.0

P3 EX

7.0

P2 6

0.0

P2 9

0.0

0.0

P3 EX

Methane concentration [OZone]

In the x-axis of Figure 5-18-(a), the species concentration recorded during the experiments is represented. The y-axis shows the species concentration computed by OZone. Figure 5-18-b represents the relative error between the test results and those obtained using OZone.

O2 relative error: test vs. OZone 119

1.0

12.0

Relative error [%]

10.0

0.8

8.0

0.6

6.0

0.4

4.0

0.2

2.0

9

8 P3

P3

EX

EX

P2

P2

P2

0

CO2 relative error: test vs. OZone

1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

1.0 R elative error [% ]

0.8 0.6 0.4 0.2

(a)

9 P3

EX

P2

P2 EX P3

P3

CO2 concentration: test vs. OZone

7

1.6

P2

1.4

EX

1.2

P3

1.0

0

0.8

P3

0.6

CO concentration [tests]

EX

0.4

P3

0.2

6

0.0

8

0.0

P2

CO concentration [OZone]

CO2 concentration: test vs. OZone

P3

P3

CO2 concentration [tests]

EX

12.0

P3

10.0

EX

8.0

P3

6.0

6

4.0

P2

2.0

EX

0.0

7

0.0

0.0

EX

CO2 concentration [OZone]

5. Combustion Products in Fires

CO relative error: test vs. OZone (b)

Figure 5-18: (a) species concentration from OZone and test comparison; (b) absolute relative error. (200 kW experiments).

One can clearly see that the agreement between the experiments and OZone simulations is quite good. One exception is the CO concentration computed for the 70 kW experiments and for methane concentration in 200 kW experiments.

An average deviation of 50.7% and 69% is found, respectively. Eq. (5-32) is used to obtain the average species derivation.

Y − Yi,Experiment  100  i,OZone   Yi,OZone   δi = S

(5-32)

where Yi,OZone is the mass fraction computed by OZone, Yi,Experiment is the experimental mass fraction and S is the number of samples (12 for 70 kW experiments and 5 for 200 kW experiments).

A possible reason for the deviation seen in methane levels could be the dancing flames occurring during the tests. The model does not simulate this phenomenon.

120

5. Combustion Products in Fires The average minimum derivation obtained for the CO2 concentration is 0.6% and 0.1% in for 70 kW and 200 kW experiments, respectively. Normal average derivations are anywhere between 0% and 20%.

Figure 5-19 represents the average temperature calculated by OZone, defined as a black circle and the idealized upper and lower temperatures found during the experiments, defined as a red rhombus and blue triangle, respectively.

Higher temperature values are predicted by OZone for the 70 kW experiments and intermediate values for 200 kW. 600 575

Ozone

Upper

Lower

550 525

70kW

500 [K]

475 450 425 400 375

200kW

350 325 300 0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

Run name

Figure 5-19: Comparison of average gas temperature (OZone), with idealized upper and lower temperatures (Fleischmann).

Figure 5-17, Figure 5-18 and Figure 5-19 were calculated at the opening; consequently other results would have obtained if another time had been chosen. However, visual comparison between computed results and test reveals good agreement.

7. Conclusions A mass balance equation, as a function of the yield species generated in fires has been developed and implemented in OZone. This allows us to obtain the mass species accumulation in the compartment during the fireâ&#x20AC;&#x2122;s development.

Data validation using 17 experiments has been carried out. In all these experiments, the fuel used was methane. 12 out of 17 experiments were carried out with a flow rate of 70 kW and the other 5 with a flow rate of 200 kW. Comparison made at the opening shows a good agreement between both recorded and computed results, except in the case of CO. 121

5. Combustion Products in Fires

Knowing the type and the quantity of gases accumulated in a compartment is essential for being able to check the flammability of the mixture, and therefore predicting the occurrence of backdraft. The energy released in a backdraft phenomenon is also dependent on the mass species accumulation.

Although if this thesis focuses principally on the analysis and prediction of the backdraft phenomenon, the implementation of the mass balance equation as well as the model for estimating the yield species provides us with the ability to estimate the toxic hazards of combustion gases in fire compartments.

122

5. Combustion Products in Fires

123