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* C.WalkerRavena@ed.ac.uk, 1.4 John Muir Building, Colin

Maclaurin Road, The University of Edinburgh, King's

Buildings, Edinburgh, EH9 3DW.

The Influence of Structure on the Flammability of Wildland Fuels under Radiative Heating

Carlos Walker-Ravena*1, Zakary Campbell-Lochrie1, Rory M. Hadden1

1School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom

C.WalkerRavena@ed.ac.uk, Z.Campbell.Lochrie@ed.ac.uk, R.Hadden@ed.ac.uk

Keywords: Biomass; Flammability; Ignition; Porous Fuels; Pyrolysis; Wildland Fuels.

Introduction

Wildland fuels are usually composed of individual elements (leaves, branches, etc.) that form a characteristic structure.

In particular, the litter layer in a pine-dominated system can be characterised as a porous matrix, comprised of needles

and air. The structure and hence porosity of the layer will influence the mechanisms that control the key flammability

parameters of ignitability and heat release rate. Describing fuel bed structure is not trivial and here we use the porosity

as a surrogate to explore the impact of fuel bed structure on flammability.

Different fuel structures were generated by mechanical means with porosities in the range 0.51 to 0.97. This is a much

greater range than has been studied previously. In order to eliminate the influence of permeability through the sample

and thus mitigate the convective cooling, samples were held in non-porous sample holders thereby allowing the effect

of structure on the intra-bed heat transfer to be isolated. The same source material was used in all tests and as such, the

intrinsic material (element) properties were constant. Piloted ignition experiments were undertaken using the FM

Global Fire Propagation Apparatus (FPA) building upon previous studies of wildland fuel flammability (Schemel et

al. 2008; Mindykowski et al. 2011; Simeoni 2011; Jervis and Rein 2016; Thomas et al. 2017; El Houssami et al. 2018).

Specifically, this work aims to observe the effects the structure has on the radiative and conductive heat transfer

processes controlling the pyrolysis and subsequent ignition.

Materials and Methods

Experimental Setup

Experiments were conducted under quiescent conditions using a non-permeable circular sample holder of diameter

126 mm and height 30 mm.

The samples were subjected to a radiant heat flux of 25 kW/m2 and an ethylene/air pre-mixed flame was positioned

20 mm above the sample surface to induce piloted ignition. Time to ignition was observed visually by analysis of video

footage after the experiment. Sample mass and concentrations of O2, CO2 and CO in the exhaust duct were measured

at a frequency of 1 Hz. These measurements were processed to obtain the mass loss rate and the heat release rate as in

(Thomas et al. 2017). Data are normalised to facilitate comparison between datasets.

Materials The source material used was dead Pitch Pine (Pinus Rigida) needles collected in New Jersey, USA. Fuel beds of

varying porosities were generated by manually manipulating the length of the pine needles thereby changing the

packing efficiency and hence porosity. This allows exploration of the effect of fuel structure with constant fuel

chemistry.

Seven different porosities are studied at constant sample volume (i.e. different fuel loads). These properties and the

methods of sample preparation are given in Table 1, with Figure 1 showing an overhead view of the non-powder cases.

Past work (Simeoni 2011; El Houssami et al. 2016; Jervis and Rein 2016) has focused on the porosity range of 0.99-

0.93 whereas here we manipulate the fuel allowing us to extend this range to 0.51. Porosity was calculated using where

𝜌𝑛𝑒𝑒𝑑𝑙𝑒 = 607𝑘𝑔/𝑚3 (El Houssami et al. 2016) and 𝜌𝑎𝑖𝑟 = 1.18 𝑘𝑔/𝑚3 (calculated using the ideal gas law at 25°C).

𝜙 = 𝜌𝑛𝑒𝑒𝑑𝑙𝑒 − 𝜌𝑏𝑢𝑙𝑘

𝜌𝑛𝑒𝑒𝑑𝑙𝑒 − 𝜌𝑎𝑖𝑟

Equation 1

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Figure 1 – Collage of sample baskets showing fuel structure for all non-powder experiments with decreasing porosity from left to

right. A white sheet was positioned at the bottom to highlight the opacity.

Table 1– Experimental cases tested

Wet Mass

[g]

Average Dry

Mass

[g]

Average Dry

Bulk density

[kgm-3]

Porosity Sample Preparation

7.5 7.0 19 0.97 Natural needles dropped into the sample holder.

Lengths extending beyond its volume were cut.

15 14 37 0.94 Natural needles packed into the sample holder.

Lengths extending beyond its volume were cut.

25 23 62 0.90 Needles cut to 7cm lengths.

Laid flat in the sample holder.

35 32 86 0.85 Needles cut to 3-4cm lengths.

Dropped into the sample holder.

60 56 150 0.75 Needles cut to 1-2.5cm lengths.

Dropped into the sample holder.

95 88 230 0.62 Needles cut to <1.5cm lengths.

Dropped into the sample holder.

120 110 300 0.51 Needles ground to a powder.

Sample holder filled.

Prior to testing, samples were oven dried at 60 °C for 24 hours with a weight on top to remove the influence of fuel

moisture content (FMC) and ensure a flat surface for the irradiated face. Due to the rapid uptake of moisture upon

removal from the oven, this resulted in a FMC in the range 0-1% at testing compared to the average FMC before drying

of 8%.

Results and Discussion Each sample was subjected to the incident heat flux for 10 minutes and time to ignition and time to flame out was

recorded. To allow comparison, the mass was normalised by the initial and final mass and the time was shifted so that

tig = 0 for each experiment.

Figure 2 shows the sample mass as a function of time for the seven different porosity cases. Data was smoothed using

a Savitzky–Golay filter and a 10s time average. For the high porosity cases, the mass loss after ignition is characterised

by a period of high mass loss rate followed by a tail of lower mass loss rate. As the porosity decreases, the mass loss

rate after ignition decreases.

For all the cases except the powder case (𝜙 = 0.51) the sample was observed to flame continuously until the sample

had been completely consumed or the test was completed (600 seconds). In the powder case the samples were observed

to behave as a charring solid with a period of flaming followed by a char oxidation. These samples were observed to

sporadically reignite around the perimeter of the sample holder after flame out. Flaming around the perimeter was also

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seen with the lower porosity cases (0.62 - 0.75). This and the similarity in the normalised mass indicates that these are

burning like a charring solid.

Figure 2 - Representative normalised mass vs time for the different porosity cases. Where each test has been shifted so that

ignition is at t = 0.

The mass lost during ignition, flaming and the entirety of the test are presented in Table 2. Here we see that the amount

of mass lost during flaming increased from 5.4 to 39g for decreasing porosities from 0.97 to 0.75. However, for lower

porosity cases the mass lost during flaming decreased. It is hypothesised that this decrease in mass lost is due to an

increase in the effective thermal conductivity reducing the heat to the reacting surface; a decrease in permeability with

decreasing porosity and an increase in radiation attenuation with depth. This reduces the heat to the surface, reduces

the gas transport into and out of the sample and reduces the heat delivered into the sample subsequently, there is a

reduction in the flame’s ability to sustain itself and hence it cannot consume as much fuel.

Table 2 – Mass lost at different stages of burning for the different porosity. Porosity Mass lost at ignition

[g]

Mass lost during flaming

[g]

Mass lost after 600s

[g]

0.97 1.5 5.4 6.2

0.94 0.84 11 14

0.90 1.2 19 21

0.85 0.71 25 29

0.75 0.77 39 40

0.62 1.4 34 38

0.51 1.0 13 34

Figure 3 shows the time to and mass lost at ignition. Given the experimental set up this is dominated by the time for

pyrolysis and hence is dominated by heat transfer process. These data therefore show the competing heat transfer

effects as the structure is changed. In the results presented, decreasing the porosity initially results in a decrease in both

the time to and mass lost at ignition however beyond a porosity of 0.85 further decreases increases both the time to

and mass lost at ignition. This suggests the presence of two regimes – one for low porosity and another for high

porosity.

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Figure 3 – (Left) Time to ignition for the different porosity cases. (Right) Mass lost at ignition for the different porosity cases.

Where, the values are averages across the repeat tests and the error bars represent the standard deviation in this value.

In the high porosity regime, the decrease in the time to ignition is hypothesised to be due to an increase in the pyrolysis

rate as a greater surface area of fuel is exposed to irradiation. The increase in the time to ignition, in the low porosity

regime, is hypothesised to be due to an increase in needle-needle connections allowing for an increase in the effective

conductivity to the colder back face – increasing heat losses from the surface.

To explore the burning further, the peak and average mass loss rate are presented in Figure 4. Where the average mass

loss rate is taken over the first 10 seconds after ignition. The peak mass loss rate varies from 0.21 to 0.27 g/s as porosity

increases from 0.51 to 0.97 and the average mass loss rate varies from 0.16 to 0.21 g/s. The increase in mass loss rate

as the samples become more porous is hypothesised to occur due to a higher pyrolysis rate due to lower heat losses

through the sample and due to increased in-depth heating as the radiation penetration is higher at higher porosities.

The variability at high porosities indicates that mixing or other transport phenomena may be important under conditions

of low bulk density.

Figure 4 - (Left) Peak mass loss rate during ignition for the different porosity cases. (Right) Average mass loss rate, for the first

10s after ignition, for the different porosity cases. Where, the values are averages across the repeat tests and the error bars

represent the standard deviation in this value.

The peak and average heat release rate are shown in Figure 5. Where the average heat release rate is taken over the

first 10 seconds after ignition. The peak heat release rate increases from 2.1 to 2.7 kW whilst the average heat release

rate increases from 1.1 to 1.8 kW as the porosity increases from 0.51 to 0.97. Thus, the heat release rate increases

with increasing porosity regardless of the decreasing fuel density. Similar to the mass loss rate, this is hypothesised to

be due to radiation penetrating deeper into the sample allowing a greater proportion of the sample volume to be

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irradiated. Losses from the sample are reduced due to low conductivity of air, which results in a decreased effective

conductivity – insulating the irradiated surface from the colder back face.

Figure 5 – (Left) Average peak heat release rate of the different porosity cases. (Right) Average heat release rate, for the first 10s

after ignition, for the different porosity cases. Where, the values are averages across the repeat tests and the error bars represent

the standard deviation in this value.

Figure 6 - Collage of representative tests at the time of peak heat release rate. Change in image tone is due to the use of a

different camera lens filter.

Table 3 – Results for the different porosity cases.

Porosity Time to

ignition

[s-1]

Peak mass loss

rate

[gs-1 ]

Average mass

loss rate

[gs-1]

Peak heat

release rate

[kW]

Average heat

release rate

[kW]

0.97 51 0.27 0.21 2.7 1.8

0.94 38 0.27 0.23 3.1 1.6

0.90 30 0.29 0.24 3.6 1.9

0.85 29 0.25 0.20 2.8 1.4

0.75 31 0.24 0.20 3.1 1.5

0.62 48 0.22 0.19 2.8 1.3

0.51 37 0.18 0.16 2.1 1.1

In the high porosity regime, 𝜙 > 0.75, a decrease in porosity means a greater exposed surface area is being irradiated

at one time and so time taken for the amount of mass to reach the required temperature field is less. Additionally the

lack of needle-needle connections results in the surface being insulated from the cooler back face and as such, the heat

is concentrated at the surface, increasing the amount of pyrolysis – leading to lower ignition times. However, the

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increased availability of oxygen and reduced heat losses leads to a greater average heat release rate compared to the

low porosity regime.

In the low porosity regime, 𝜙 < 0.75, the decrease in porosity has reached a point at which the increase in irradiated

surface is no longer sufficient to negate the effect of the increase in needle-needle connections. These conduct the heat

away from the top surface and to the back face and as such results in an overall lower temperature sample and so less

pyrolysis occurs – leading to higher ignition times.

It is expected that an imposed airflow would alter these results due to transport effects such as convection and dilution.

The higher porosity cases are the most prone to these due to their permeability and as such deviation in the results at

these is accounted for as the samples being affected by their own buoyant plume.

Conclusions These preliminary data suggest that the fuel structure plays a strong role in the flammability of wildland fuels. This

appears to be primarily through changes in the heat transfer processes moving from interactions between the individual

fuel elements to a bulk fuel. Future work should consist of supplementing these hypotheses through closer

interrogation of the energy balance within the samples - such as the radiation penetration, the temperature at depth and

measuring the buoyant flow produced by the combustion process. Verification of the phenomena observed with another

fuel should also be conducted ensuring the examination of particle parameters for example surface to volume ratio or

emissivity.

Acknowledgements The authors wish to thank the Strategic Environmental Research and Development Program (SERDP) for their

financial support under the project grant RC-2641. The authors would also like to thank Dr Michael Gallagher for

providing the fuels used in this study.

References: El Houssami M, Lamorlette A, Morvan D, Hadden RM, Simeoni A (2018) Framework for submodel improvement in wildfire

modeling. Combustion and Flame 190, 12–24. doi:10.1016/j.combustflame.2017.09.038.

El Houssami M, Thomas JC, Lamorlette A, Morvan D, Chaos M, Hadden R, Simeoni A (2016) Experimental and numerical

studies characterizing the burning dynamics of wildland fuels. Combustion and Flame 168, 113–126.

doi:10.1016/j.combustflame.2016.04.004.

Jervis FX, Rein G (2016) Experimental study on the burning behaviour of Pinus halepensis needles using small-scale fire

calorimetry of live, aged and dead samples. Fire and Materials 40, 385–395. doi:10.1002/fam.2293.

Mindykowski P, Fuentes A, Consalvi JL, Porterie B (2011) Piloted ignition of wildland fuels. Fire Safety Journal 46, 34–40.

doi:10.1016/j.firesaf.2010.09.003.

Schemel CF, Simeoni A, Biteau H, Rivera JD, Torero JL (2008) A calorimetric study of wildland fuels. Experimental Thermal

and Fluid Science 32, 1381–1389. doi:10.1016/j.expthermflusci.2007.11.011.

Simeoni A (2011) On the Role of Bulk Properties and Fuel Species on the Burning Dynamics of Pine Forest Litters. Fire Safety

Science 10, 459–470. doi:http://dx.doi.org/10.3801/IAFSS.FSS.10-1401.

Thomas JC, Hadden RM, Simeoni A (2017) Experimental investigation of the impact of oxygen flux on the burning dynamics of

forest fuel beds. Fire Safety Journal 91, 855–863. doi:10.1016/j.firesaf.2017.03.086.

Torero JL, Simeoni A (2010) Heat and Mass Transfer in Fires: Scaling Laws, Ignition of Solid Fuels and Application to Forest

Fires. The Open Thermodynamics Journal 4, 145–155. doi:10.2174/1874396X01004010145.

Presenter’s bio: Carlos Walker-Ravena is a British-Spanish Fire Safety Engineering PhD student at the University of Edinburgh. Originally, from Liverpool, he

attended Imperial College London and completed a 4-year master in Mechanical Engineering with a Year Abroad - the year abroad being undertaken

at TU Delft. He is now part of University of Edinburgh Wildfire group, which conducts experiments at both a laboratory scale in Edinburgh, UK and at the field scale in the New Jersey Pine Barrens, USA.