Paper #070FR-0208 Topic: Fire

8th U. S. National Combustion Meeting Organized by the Western States Section of the Combustion Institute

and hosted by the University of Utah May 19-22, 2013

Numerical investigation of influence of initial moisture content on

thermal behavior of heated wood

S. Ferguson1 B.L. Yashwanth1 B. Shotorban1 S. Mahalingam1 D.R. Weise2

1Department of Mechanical and Aerospace Engineering, The University of Alabama in Huntsville,

Huntsville, AL 35899, USA 2Pacific Southwest Research Station, USDA Forest Service, Riverside, California, USA

The influence of the initial moisture content of the wood on its pyrolysis was numerically studied for a one-dimensional wet wood domain subjected to a constant heat flux. Cases with various initial moisture contents, ranging from 0 to 50% on a dry wood basis were considered. Conservation equations for gaseous and solid mass, energy, species, and gaseous momentum (Darcy’s law approximation) inside the decomposing solid were solved, using gpyro, a generalized pyrolysis model (Lautenberger, 2007), to obtain profiles of temperature and moisture content inside the decomposing wood at various times. The correlations given by Ragland and Aerts (1991) for the thermal properties of wood were employed. The thermal behavior and drying process for wood with 30% initial moisture content were found to substantially differ from that with 5 % initial moisture content. 1. Introduction Wildland fires can cause a significant amount of property damage, cost millions in resources to manage, and most importantly, they can be a major threat to the safety of people and wildlife under vigorous burning conditions. Thermal degradation is one of the beginning processes to wildland fires. The degradation of the wood leads to the release of pyrolysis gases from a wood that has been subjected to a heat flux. The released pyrolysis gases are oxidized by the air and result in a chemical runaway reaction which cause ignition of the gases. Since the thermal degradation is the leading cause of this reaction, it is important to accurately model the thermal degradation of wood.

Recent studies show that including live vegetation in wildland fire models is necessary since these fires consume both living and dead vegetation. Therefore, live vegetation should be also included when modeling the thermal degradation of fuel in wildland fires. Moisture content of living vegetation ranges from approximately 50% to over 300% on a dry mass basis. As reported by Sun et al. (2006), it is generally accepted that the fuel can be considered essentially dead when the fuel moisture content is below a threshold of 30%. In live vegetation the moisture content varies both with the season and climate. In order to accurately account for living vegetation, a model would need to allow for moisture content greater than 30%, which is approximately the fiber saturation point of wood.

The purpose of this work is to investigate the influence of the initial moisture content on thermal behavior of heated wood. The generalized pyrolysis model, Gpyro developed by Lautenberger (2007), is employed to conduct this study.

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2. Setup and Approaches A one-dimensional decomposing wood domain with a thickness of 3.8 cm in a nitrogen environment was subjected to a constant externally applied radiative heat flux of 40 kW/m2. The wood domain is a condensed phase coupled to the gas phase inside the pores of the decomposing solid. The gas outside of the wood domain was not modeled. The initial temperature, pressure, gaseous species mass fractions, and condensed phase species were uniform throughout the solid. On the left side at 𝑥 = 0, the constant external radiative heat flux was applied with convective and radiative cooling. On the right side at 𝑥 = 𝐿, a convective boundary condition was applied. The initial density was 380 kg/m3. Conservation equations for gaseous and solid mass, energy, species and gaseous momentum (Darcy’s law approximation) inside the decomposing solid were solved to calculate the variation of temperature and moisture content. In the current model white pine wood was simulated as three condensed phase species: (1) wet wood, (2) dry wood, and (3) char. The bulk density of each species was considered constant. The thermal conductivities and specific heat capacities were both considered temperature and moisture dependent, following the correlations given by Ragland and Aerts, (1991). The specific heat of the dry wood as well as the specific heat of the char were only dependent on temperature T. The specific heat of char 𝑐 char was assumed to be the same as graphite which varies from 0.715 kJ kg-1 K-1 at 300 K to 2.04 (kJ kg-1 K-1) at 2000 K. The following equation proposed by Stull (1971) was used, which is obtained by curve fitting the data from 700 to 2000 K is within a 5% margin of error:

𝑐 char = 1.39+ 0.00036  𝑇                  (kJ  kg!!K!!) The specific heats of dry wood and wet wood given by Tenwolde et al. (1988) were used. For the dry wood:

𝑐 dry = 0.1031+ 0.00386  𝑇                  (kJ  kg!!K!!) The energy absorbed by the wood-water bonds results in the specific heat of wet wood being greater than that found by the simple law of mixing. The specific heat of wet wood 𝑐 wet is dependent on both temperature 𝑇 and moisture content on dry basis 𝑀:

𝑐 wet =𝑐 dry + 4.19  𝑀

1+𝑀 + 𝐴                  (kJ  kg!!K!!) Tenwolde et al. (1988) states that the specific heat for wet wood can be used for wood below the fiber saturation point, approximately 30%, for

𝐴 = 0.02355𝑇 − 1.32𝑀 − 6.191 𝑀 and Ragland and Aerts (1991) state that for above the fiber saturation point 𝐴 should be set to zero.

The thermal conductivity of wood approximated by TenWolde et al. (1988) was utilized. It is dependent on density, moisture content and temperature:

𝑘 = 𝑆 0.1941+ 0.4064𝑀 + 0.01864                  (W  m!!K!!)      

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where 𝑆 is the specific gravity based on volume at the current moisture content and weight wen oven dry. The thermal conductivity of wood increases 0.2% per oC above room temperature. The temperature correlation for the thermal conductivity was based on limited data.

Two condensed phase heterogeneous reactions were considered. Reaction 1 converts wet wood to dry wood and water vapor and reaction 2 is the anaerobic conversion of dry wood to char plus thermal pyrolysates:

wet  wood  

 𝜈!"dry  wood+  𝜈!!!H!O

dry  wood  

 𝜈!!!"char+  𝜈!"thermal  pyrolysate

The thermal pyrolysates used in this model include four main gaseous of wood (CO, H2, CH4, and CO2) measured by Klose et al. (2000). However, the thermal pyrolysates are not significant in this model since no homogeneous reactions are considered. All parameters excluding the thermal properties described above are matched to that used by Lautenberger et al (2009b). 3. Results and Discussions Figure 1 displays the spatial variation of the moisture content. In fig. 1(a), the moisture content variations are shown at various times for a case with 30% initial moisture content. The wood starts drying from the left boundary, which is exposed to the constant radiative heat flux. The moist region retreats as time progresses. At 600 seconds, the completely dried region spans a distance of approximately 0.014 m from the left boundary into the wood. In fig. 1(b), moisture content of the wood is plotted against 𝑥 at 𝑡 = 600 seconds for four cases with different initial moisture contents. The drying process is shown to significantly change between wood with an initial moisture content of 20% and 30% at a time of 600 sec. A moisture content of 50% is a representation of live vegetation since it is greater than the fiber saturation point. It is seen in fig. 1(b) that the size of the domain that is completely dried is almost the same for the cases with 50% and 30% initial moisture contents. This size for the cases with 5% and 20% is somewhat larger.

Figure 2 shows time evolutions of temperature at the left boundary 𝑥 = 0 and a point within the wood 𝑥 = 0.01 m. Various curves are for cases with different initial moisture contents. Since the drying process occurs rapidly on the left boundary, no substantial deviations are observed between different cases for this point at later times. On the other hand, at early times although there are some deviations between the cases, the trends of the time evolution of temperature are similar. Also, the trends of the time history of temperature at = 0.01 m for all cases, excluding the case with initial moisture content of 50%, are similar. At this point, the evolution of temperature at the initial stage for the case with initial moisture content of 50% is completely different from the other cases. However, later on the temperature of this case is very close to the case with initial moisture content of 30%. It is noted he temperature profile is in agreement with results of Lautenberger and Fernandez-Pello, (2009a and 2009b) which are available for 5% initial moisture content. 4. Summary and Conclusions A one-dimensional wet wood domain was modeled using a generalized pyrolysis model, Gpyro (Lautenberger, 2007), along with thermal property correlations given by Ragland and Aerts (1991). Cases with different initial moisture contents ranging from 0% to 50% on a dry wood basis were considered. For a point located within the wood, there was a substantial difference between the temperature histories of cases with initial moisture contents of 5% and 20%, and those with initial

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moisture contents of 30% and 50%. The wet wood with an initial moisture content of 50%, which is above the fiber saturation point, showed a slightly different trend from that of 30%. This deviation might be due to the specific heat model (Tenwolde et al, 1988) used in the current study. Tenwolde et al (1988) recommended use of this model for moisture content below the fiber saturation point, which is 30%. Acknowledgements

The authors gratefully acknowledge financial support from the USDA Forest Service PSW Research Station through cooperative agreement 10-JV-11272166-091 with The University of Alabama in Huntsville. The authors thank Christopher W. Lautenberger for providing assistance on configuring and using Gpyro. References Lautenberger, C., “A Generalized Pyrolysis Model for Combustible Solids”, Ph.D. Dissertation,

Department of Mechanical Engineering, University of California, Berkeley, 2007 Lautenberger, C. and Fernandez-Pello, C. 2009a. A model for the oxidative pyrolysis of wood.

Combustion and Flame, 156, 1503-1513. Lautenberger, C. and Fernandez-Pello, C. 2009b. Generalized pyrolysis model for combustible

solids. Fire Safety Journal, 44, 819-839. Ragland, K.W. and Aerts, D. J. 1991. Properties of Wood for Combustion Analysis. Bioresource

Technology, 37, 161-168. Sun, L., Zhou, X., Mahalingam, S., and Weise, D.R. 2006. Comparison of burning characteristics of

live and dead chaparral fuels. Combustion and Flame, 144, 349-359. Stull, D. R. and Prophet, H. 1971. JANAF thermochemical tables, NSRDS-NBS 37, US Government

Printing Office. Tenwolde, A., McNatt, J., and Krahn, L. 1988. Thermal properties of wood and wood panel products

for use in buildings. DOE/USDA-21697/1, Oak Ridge National Laboratory, Oak Ridge, TN.

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Figure 1. Spatial distribution of moisture content; (a) at different times for a wet wood with 30%

initial moisture content; (b) for different initial moisture contents at 600 sec.

distance x(m)

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Figure 2. Time history of temperature at 𝑥 = 0 m and 𝑥 = 0.01  m for various initial moisture

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