Abstract
This study investigated the transverse thermal conductivity of low-density plantation wood species and tropical hardwoods from the Philippines using the guarded hot-plate method. Results showed that thermal conductivity of low density, plantation species and denser tropical hardwoods ranged from 0.128 to 0.188 W/mK and 0.161 to 0.300 W/mK, respectively. Thermal conductivity was directly influenced by both density and moisture content of wood. Transverse thermal conductivity increased by 0.73% and 1.79% per percent increase in MC from 0% to 21% MC for low density (<500 kg/m3) and high density (>500 kg/m3) wood, respectively. Linear regression models fitted for thermal conductivity and ovendry density indicated a strong fit. However, there was a poor to moderate relationship between thermal conductivity and MC. The results of the present study may be of interest in the conversion of woody biomass to bioenergy or to building designers looking for natural materials to improve energy performance and efficiency of wood structures where heat transfer and temperature control are a significant economic consideration.
Download PDF
Full Article
Thermal Conductivity of Plantation Wood Species and Selected Tropical Hardwoods from the Philippines
Mario Angelo M. Mundin,a and Menandro N. Acda b,*
This study investigated the transverse thermal conductivity of low-density plantation wood species and tropical hardwoods from the Philippines using the guarded hot-plate method. Results showed that thermal conductivity of low density, plantation species and denser tropical hardwoods ranged from 0.128 to 0.188 W/mK and 0.161 to 0.300 W/mK, respectively. Thermal conductivity was directly influenced by both density and moisture content of wood. Transverse thermal conductivity increased by 0.73% and 1.79% per percent increase in MC from 0% to 21% MC for low density (<500 kg/m3) and high density (>500 kg/m3) wood, respectively. Linear regression models fitted for thermal conductivity and ovendry density indicated a strong fit. However, there was a poor to moderate relationship between thermal conductivity and MC. The results of the present study may be of interest in the conversion of woody biomass to bioenergy or to building designers looking for natural materials to improve energy performance and efficiency of wood structures where heat transfer and temperature control are a significant economic consideration.
DOI: 10.15376/biores.20.3.6877-6886
Keywords: Thermal conductivity; Energy efficiency; Sustainable building; Philippine woods; Fourier’s law
Contact information: a: Department of Science and Technology, Forest Products Research and Development Institute, College. Laguna 4030 Philippines; b: Department of Forest Products and Paper Science, University of the Philippines Los Banos, College. Laguna 4030, Philippines;
* Corresponding author: mnacda@up.edu.ph
INTRODUCTION
Thermal conductivity of wood is the property that measures the “ease” or “difficulty” for the flow of heat energy when subjected to a temperature gradient. Wood is made up of cellulose, hemicellulose, and lignin interwoven into a complex composite of high and low molecular weight polymers. It has a long history of use as fuel and building construction material. Understanding the thermal properties of wood and wood composites is essential in various applications such as fuel conversion (Ragland et al. 1991; Thunman and Leckner 2002), insulation (Rice and Shepard 2004; Kawasaki and Kawai 2006), and building construction (Kamke and Zylkowski 1989; Czajkowski et al. 2016). Thermal conductivity plays an important role in the design of structures in which heat transfer and temperature control are a significant economic consideration (Olek et al. 2003). The steady state heat conduction according to Fourier’s Law is when the heat flux is proportional to the magnitude of the temperature gradient (Siau 1984). Accordingly, thermal conductivity can be expressed as,
(1)
where q is the heat flux (W/m2), A is the cross-sectional area perpendicular to flow (m2), dx is the specimen thickness (m), dT the temperature gradient between surfaces (K), and k is thermal conductivity (W/mK). Wood is a complex and heterogeneous material with thermal conductivity varying both between and within species. Other factors affecting thermal conductivity of wood include density (Yu et al. 2011), moisture content (TenWood et al. 1988), temperature (Harada et al. 1998; Suleiman et al. 1999), grain direction (Vay et al. 2015; Flity et al. 2024), porosity, anisotropic nature (Bucar and Straze 2008; Hu et al. 2023), and chemical composition (Suleiman et al. 1999), among others.
The most established method for high precision thermal conductivity measurement of wood is the guarded hot-plate (GHP) method (Hu et al. 2023; Ebert and Vidi 2024). The wood specimen is placed under a high temperature heat source for a sufficient length of time to achieve a uniform temperature gradient (steady state) throughout the sample. The rate of heat flow is obtained based on the electric input to the heating element and thermal conductivity calculated based on Eq. 1. Other methods such as the laser flash (Harada et al. 1998), transient plane source technique (Suleiman et al. 1999), and transient hot wire method (Kol 2009) were also developed. The present study reports on the thermal conductivity of wood using the GHP method from fast-growing industrial plantation species and from selected Philippine tropical hardwoods. These wood species are commonly used for general construction and often exported to North America and Europe. Thermal conductivities of wood species grown from Southeast Asia are often lacking or not available. Results from this study could potentially be useful for modelling heat transfer processes or in the design of energy efficient and sustainable buildings using components or members of these wood species.
MATERIALS AND METHODS
Wood Specimens
Twelve (12) Philippine wood species (10 to 15 years old) from fast-growing plantation and tropical hardwoods were selected from the stock of the Forest Products Research and Development Institute, Department of Science and Technology (Table 1). These species were chosen because of their common use or to cover a wide range of densities. Five discs (50 mm ×10 mm; diameter × thickness) with no signs of decay, cracks, checks, or knots were cut and surfaced from each species (Fig. 1). All specimens were then placed in a conditioning chamber (Memmert HCP105) where temperature and relative humidity were adjusted to achieve target equilibrium moisture contents (MC) of 21% followed by 12% (dry basis). Lastly, specimens were placed in an oven set at 105 °C until constant weight (ovendry) was achieved. Specimen weight and volume were determined at each level of MC, from which wood densities were calculated using (ASTM D2395-14).
Fig. 1. Plantation species and tropical hardwoods from the Philippines used in thermal conductivity measurements
Table 1. Philippine Plantations Tree Species and Tropical Woods Used in GHP Thermal Conductivity Measurements
Thermal Conductivity Measurement
A single-specimen guarded hot plate apparatus calibrated using brass plates was used to measure the thermal conductivity of all wood specimens following ISO 8302 (1991) method with some modifications. A wood specimen of uniform thickness (50 mm x 10 mm) was placed in thermal contact between heated (323 K) and cold (303 K) metal discs (50 mm), resulting in a uniform temperature gradient after about 20 to 30 min across the transverse grain direction of the specimen (Fig. 2). To minimize lateral heat loss and erroneous heat flux reading, a cylindrical layer of cellular insulation (Styrofoam 20 mm) was wrapped around both hot and cold discs and the wood specimen (Fig. 1). The apparatus was enclosed in a glass chamber to prevent convective losses or gains from the surrounding air. The setup ensured that the heat flow was perpendicular to the specimen surface with no lateral parasitic heat loss. The temperatures of the hot and cold discs were recorded using thermocouples (Type K) attach to a data logger. The rate of heat flow was recorded based on the electric input to the heating element of the hot disc. All measurements were performed under steady-state conditions and thermal conductivity calculated according to Eq. 1. Thermal conductivity was measured for all wood specimens at 21%, 12%, and 0% MC values. Five replicate wood specimens were used for each measurement. A linear regression model was fitted between thermal conductivity and density using Statgraphics Centurion 19 (2023) software to determine the influence of wood density on thermal conductivity.
Fig. 2. Schematic diagram of the guarded hot-disc apparatus used to measure thermal conductivity of Philippine plantation wood species and selected tropical hardwoods. (TC: surface thermocouple; and MS: metering section heater).
RESULTS AND DISCUSSION
The results from transverse thermal conductivity measurements of Philippine plantation species and tropical woods using the GHP method are shown in Table 2. The GHP method is commonly used for high precision thermal conductivity measurements on porous and non-porous solid materials based on the direct application of Fourier’s law (Hu et al. 2023; Ebert and Vidi 2024). It is an absolute method requiring no calibration measurements. The GHP method was originally developed for electrical insulation, but many researchers have used this technique to measure thermal conductivity of wood (Bucar et al. 2008; Sonderegger et al. 2011; Vololonirina et al. 2014; Vay et al. 2015). The measurement, however, requires a relatively large sample and a long time to reach steady-state heat flow. Thermal conductivity measurements in this study were performed with wood MC values at 0%, 12%, and 21% to determine effect of MC on thermal conductivity. These results showed that there was a 0.73% and 1.79% increase in transverse thermal conductivity per percent increase in MC from oven-dry to 21% MC for species with density <500 kg/m3 (plantation species) and >500 kg/m3 (hardwoods), respectively (Table 2). A similar range of increase (1% to 2%) was reported by Cammerer and Achtziger (1984) with increasing MC for several wood species from Europe. A linear regression model was fitted to explain the variation in transverse thermal conductivity with MC for wood species used in this study (Figs. 3 and 4). In general, there was a significant statistical relationship between thermal conductivity and MC of wood (P-values < 0.001). However, the coefficient of determinations (R2) indicated poor to moderate relationship between the variables (Table 3). This could be due to various factors including the natural variability of wood, error in measurements, and moisture redistribution during thermal conductivity measurement, among others. TenWolde et al. (1988) reported that measurements using moist samples cause moisture redistribution resulting in transient heat flow. During redistribution the conductivity was reportedly larger than the steady state conductivity (TenWolde et al. 1988). The increase in thermal conductivity may be due to the presence of more water, which is more conductive than fibril and air, as the moisture level increases (Yu et al. 2011). Maeda et al. (2021) explained the increase in terms of the “Dufour effect” i.e., increased energy flux due to the occurrence of a mass concentration gradient (Dufour 1872). In any case, caution must be taken in the use of these relationships, as the mechanism of how MC affects thermal conductivity is still largely unclear.
The density of tropical hardwood varies widely from very light such as balsa (Ochroma sp.) to the very heavy ironwood (Xanthostemon sp.). Wood density is a fundamental property that plays an important role in wood utilization. It serves as an index of wood strength, influences dimensional stability, workability, machinability and gluability of wood. Density also affects the ability of wood to conduct heat energy. Low density wood has better insulating properties (lower thermal conductivity), while higher density transfers heat more readily. The difference in density between tropical hardwoods and low-density plantation species used in this study is shown in Table 2. Measurements of ovendry thermal conductivity using GHP method resulted in 0.128 to 0.188 W/mK and 0.161 to 0.300 W/mK for low-density, plantation species and denser hardwoods, respectively. Low-density species have lower thermal conductivity due to the presence of large proportion of voids (air space) in its structure relative to the solid wood substance. The trapped air pockets act as barriers to heat flow, making the material a good insulator. High-density wood has less air space and a greater volume of solid wood substance resulting in higher thermal conductivity (Yu et al. 2011; Vay et al. 2015; Cavus et al. 2019). The increase in thermal conductivity with density is consistent with that reported by Yu et al. (2011) using several softwood and hardwood species from China.
Analysis of variance (ANOVA) showed a significant relationship (P-value < 0.05) between the thermal conductivity and ovendry density of wood species used in this study (Fig. 5). A linear regression model fitted to describe said relationship is shown below:
Thermal conductivity (W/mK) = 0.067 + 0.00079*Density (kg/m3) (1)
The R2 and correlation coefficient were 66.01% and 0.812, respectively, indicating a moderately strong relationship between the variables. Regression models can potentially be used as a powerful tools to predict thermal conductivity of other wood species with known ovendry density and their suitability for specific applications. Further work will be done in the future to cover other wood species from the Philippines and to include other factors such as temperature, flow directions, etc. to improve the accuracy of the model.
Fig. 3. Transverse thermal conductivity of plantation species from the Philippines with varying moisture content. Each point is the average of five replicate wood specimen.
Fig. 4. Transverse thermal conductivity of tropical hardwoods from the Philippines with varying moisture content. Each point is the average of five replicate wood specimen.
Fig. 5. Relationship between transverse thermal conductivity and oven-dry density of plantation species and tropical hardwoods from the Philippines
Table 2. Transverse Thermal Conductivity of Plantation Species and Tropical Hardwoods from the Philippines with Varying Moisture Content
CONCLUSIONS
- The study investigated the transverse thermal conductivity of low-density plantation wood species and selected tropical hardwoods from the Philippines using the guarded hot-plate method.
- Results showed that ovendry thermal conductivity of low-density, plantation species and denser tropical hardwoods was about 0.128 to 0.188 W/mK and 0.161 to 0.300 W/mK, respectively. Transverse thermal conductivities increased by 0.73% and 1.79% per percent increase in MC from 0% to 21% MC for wood species with density <500 kg/m3 (plantation species) and >500 kg/m3 (hardwoods), respectively.
- Thermal conductivity was directly influenced and appeared to be positively correlated to both density and moisture content of wood. Linear regression models for thermal conductivity and MC of wood indicated a poor to moderate relationship between the variables. Oven-dry density and thermal conductivity resulted in a relatively strong fit.
- The results may be of interest in energy conversion of woody biomass
ACKNOWLEDGMENTS
The authors wish to thank the DOST-Philippine Council for Industry, Energy, and Emerging Technology Research and Development (DOST-PCIEERD) for providing partial funding support for this project (Project No. 1213133, 2014); to the DOST-Forest Products Research and Development Institute for the use of their thermal conductivity apparatus; and to Mr. Jovito Elec and Engr. Sapin of the DOST-FPRDI for their assistance during the experiment and providing wood specimens for this study.
REFERENCES CITED
ASTM D2395 (2014). “Standard test methods for density and specific gravity (relative density) of wood and wood-based materials,” ASTM International, West Conshohocken, PA.
Bucar, B., and Straze, A. (2008). “Determination of the thermal conductivity of wood by the hot plate method: The influence of morphological properties of fir wood (Abies alba Mill.) to the contact thermal resistance,” Holzforschung 62, 362-367. DOI: 10.1515/HF.2008.021
Cammerer, J., and Achtziger, J. (1984). “Einfluss des Feuchtegehaltes auf die Ẅarmeleitf̈ahigkeit von Bau- und D̈ammstoffen (Influence of moisture content on the thermal conductivity of building and insulation materials),” Bauforschungsbericht des Bundesministers f̈ur Raumordnung, Bauwesen und Sẗadtebau (Construction Research Report of the Federal Minister for Regional Planning, Building and Urban Development), Bonn, F 1988. IRB Verlag, Stuttgart. DOI: 10.24321/2454.8650.202002
Çavuş, V., Şahin, S., Esteves, B., and Ayata, U. (2019). “Determination of thermal conductivity properties in some wood species obtained from Turkey,” BioResources 14(3), 6709-6715. DOI: 10.15376/biores.14.3.6709-6715
Czajkowski, L., Olek, W., Weres, J., and Guzenda, R. (2016). “Thermal properties of wood-based panels: thermal conductivity identification with inverse modeling,” Eur. J. Wood Prod. 74, 577-584. DOI: 10.1007/s00107-016-1021-6
Dufour, L. (1872). “The diffusion thermoeffect,” Archives des Sciences Physiques et Naturelles 45, 9-12.
Ebert, H. P., and Vidi, S. (2024). “Correct use of the guarded-hot-plate method for thermal conductivity measurements on solids,” Int. J. Thermophys. 45, 20. DOI: 10.1007/s10765-023-03307-x
Flity, H., Jannot, Y., Terrei, L., Lardet, P., Schick, V., Acem, Z., and Parent, G. (2024). “Thermal conductivity parallel and perpendicular to fibers direction and heat capacity measurements of eight wood species up to 160°C,” Int. J. Thermal Sci. 195, article 108661. DOI: 10.1016/j.ijthermalsci.2023.108661
Harada, T., Hata, T., and Ishihara, S. (1998). “Thermal constants of wood during the heating process measured with the laser flash method,” J. Wood Sci. 44, 425–431. DOI: 10.1007/BF00833405
Hu, Y. P., Li, W. B., Wu, S., Wang, Y. J., Zhong, W. Z., and Zhang, H. (2023). “Experimental study of the anisotropic thermal conductivity of Spruce wood,” Int. J. Thermophys. 44, article 131. DOI: 10.1007/s10765-023-03238-7
ISO 8302 (1991). “Thermal insulation—determination of steady-state thermal resistance and related properties—guarded hot plate apparatus,” International Organization for Standardization, Geneva, Switzerland.
Kamke, F. A., and Zylkowski, S. C. (1989). “Effect of wood-based panel characteristics on thermal conductivity,” Forest Prod. J. 39, 19-24.
Kawasaki, T., and Kawai, S. (2006). “Thermal insulation properties of wood-based sandwich panel for use as structural insulated walls and floors,” J. Wood Sci. 52, 75-83. DOI: 10.1007/s10086-005-0720-0
Kol, H. (2009). “The transverse thermal conductivity coefficients of some hardwood species grown in Turkey,” Forest Prod. J. 59, 58-63. DOI: 10.13073/0015-7473-59.10.58
Maeda, K., Tsunetsugu, Y., Miyamoto, K., and Shibusawa, T. (2021). “Thermal properties of wood measured by the hot-disk method: comparison with thermal properties measured by the steady-state method,” J. Wood Sci. 67, article 20. DOI: 10.1186/s10086-021-01951-1
Manugistics Inc. (2023). Statgraphics Centurion 19, User’s Manual, Rockville, MD, USA.
Olek, W., Weres, J., and Guzenda, R. (2003). “Effects of thermal conductivity data on accuracy of modeling heat transfer in wood,” Holzforschung 57, 317-325. DOI: 10.1515/HF.2003.047
Ragland, K. W., Aerts, D. J., and Baker, A. J. (1991). “Properties of wood for combustion analysis,” Bioresour. Technol. 37, 161-168. DOI: 10.1016/0960-8524(91)90205-X
Rice, R. W., and Shepard, R. (2004). “The thermal conductivity of plantation grown white pine (Pinus strobus) and red pine (Pinus resinosa) at two moisture content levels,” Forest Prod. J. 54, 92-94.
Siau, J. F. (1984). “Thermal conductivity,” in: Transport Processes in Wood, Springer Verlag, Berlin.
Sonderegger, W., Hering, S., and Niemz, P. (2011). “Thermal behavior of Norway spruce and European beech in and between the principal anatomical directions,” Holzforschung 65, 369-375. DOI: 10.1515/hf.2011.036
Suleiman, B. M., Larfeldt, J., Leckner, B., and Gustavsson, M. (1999). “Thermal conductivity and diffusivity of wood,” Wood Sci. Technol. 33, 465-473. DOI: 10.1007/s002260050130
TenWolde, A., McNatt, J. D., and Krahn, L. (1988). Thermal Properties of Wood and Wood Panel Products for Use in Buildings, Tech. Rep. DOE/OR/21697-1
Thunman, H., and Leckner, B. (2002). “Thermal conductivity of wood – Models for different stages of combustion,” Biomass Bioenergy 23, 47-54. DOI: 10.2172/6059532, 6059532
Vay, O., Borst, K. D, Hansmann, C., and Teischinger, A. (2015). “Thermal conductivity of wood at angles to the principal anatomical directions,” Wood Sci. Technol. 14, 577-589. DOI: 10.1007/s00226-015-0716-x
Vololonirina, O., Coutand, M., and Perrin, B. (2014). “Characterization of hygrothermal properties of wood-based products – Impact of moisture content and temperature,” Constr. Build. Mater. 63, 223-233. DOI: 10.1016/j.conbuildmat.2014.04.014
Yu, Z. T., Xu, X., Fan, L. W., Hu, Y. C, and Cen, K. F. (2011). “Experimental measurements of thermal conductivity of wood species in China: Effects of density, temperature, and moisture content,” Forest Prod. J. 61, 130–135. DOI: 10.13073/0015-7473-61.2.130
Article submitted: May 8, 2025; Peer review completed: June 7, 2025; Revisions accepted: June 23, 2025; Published: June 26, 2025.
DOI: 10.15376/biores.20.3.6877-6886