Thermal properties of wood and wood composites made from wood waste

Abstract

During the processing of wood for wood-based products mechanical and thermal stresses often occur. The temperature changes affect the level of wood moisture because heat transport cannot be separated from water transport. The mechanism of conduction is the dominant process of heat transfer through wood and wood-based products, but convection and radiation are also included, mainly in the form of boundary conditions. Heat conduction takes place when a temperature gradient exists in a solid medium. It may be described by Fourier ́s Law (Gustafsson, 1991; Sobota, 2014), where λ is the thermal conductivity (W m K). The conduction of heat involves the transfer of energy within a material without any motion of the material as a whole. The velocity of the temperature equalization in a material during non-stationary processes characterizes thermal diffusivity a (m s) which has been defined in the literature (Suleiman et al., 1999; Adl-Zarrabi, 2004). The volume specific heat cρ (J m K) may be expressed as ratio thermal conductivity λ and thermal diffusivity a (Bouguerra et al., 2001; Nakaya et al., 2016). The thermal parameters of wood and wood-based products are affected by many internal and external factors such as: moisture content (Troppova et al., 2014; Glass and Zelinka, 2010), temperature (Zhou et al., 2013), density of the wood, direction of heat flow with respect to the grain (Ružiak et al., 2017; Öner et al., © 2021 Institute of Agrophysics, Polish Academy of Sciences M. BOŽIKOVÁ et al. 252 2009). The thermal properties of wood-based materials are required in applications such as fuel conversion, building construction and other fields of industry (Zi-Tao et al., 2011). The problem of thermal parameter measurements of wood-based panels has already been discussed in a previous study and new results of the property have been delivered by Sonderegger and Niemz (2012), Li et al. (2013). Steadystate methods are used for the detection of wood thermal parameters (Hrčka and Kurjatko, 2006). Transient methods were introduced by Adl-Zarrabi and Boström (2004), Tavman (1996). Avramidis and Lau (1992) which measured the thermal coefficients of wood particles using a transient heat-flow method. The TPS technique is described in detail by Gustafsson (1991) and Wechsler (1992). According Karawacki et al. (1992) the extended dynamic plane source (EDPS) method is convenient for low thermal conductivity materials (Beck and Arnold, 2003; Malinarič, 2004). It was applied to the detection of the thermophysical properties of the solid wood of coniferous trees by authors Krišťák et al. (2019). Knowledge of the thermal properties of wood is essential for determining of its future usage. Based on the presented facts, the main aim of this research was the identification of the selected thermal properties for different types of woods and wood composites made from wood waste in Slovakia using the dynamic plane source (DPS) method. The main benefit of the research were to establish the relationships between the thermal parameters for the different moisture contents of wood and wood composites – oriented strand board (OSB) detected in the tangential and radial direction. MATERIALS AND METHODS The thermal conductivity, thermal diffusivity and the volume specific heat of the wood and the products made in Slovakia were investigated. Measurements were performed on five types of wood samples: softwood – spruce (Picea abies) and black pine (Pinus nigra), hardwood – beech (Fagus silvatic) and oak (Quercus robur) and also on medium hardwood – chestnut (Aesculus hippocastanum). The relative moisture contents of the measured wood samples fell within the following range – 0-35%. The wood samples were prepared in two directions. The tangential direction is perpendicular to the grain but tangent to the growth rings and the radial direction is normal to the growth rings and perpendicular to the grain in the radial direction. For every wood type special OSB samples were taken with tangential and radial directions. For the purpose of taking OSB thermal parameter measurements, samples from of wood-waste were prepared with the majority content of the wood species having a moisture content in the range 22-26% and the final product – samples of the examined OSB had a relative moisture content ranging from 4 to 7%. The dimensions of all of the measured samples were the same (150 x 150 mm) and with a thickness of 15 mm. Experimental identification of the thermal parameters was performed under laboratory conditions with an air temperature of 20°C, an atmospheric pressure of 101.3 kPa and a relative air humidity of 42.5%. The relative moisture content ωrel of the measured samples was calculated as the ratio of the water mass to the mass of the dry sample multiplied by 100% (Glass and Zelinka, 2010). The gravimetric method was used to determine the moisture content. The mass of the wood samples was measured during the drying process using analytical laboratory scales Kern ADB (Kern, Germany) with an accuracy of 0.0001 g. A laboratory oven SLW 32 STD (Intertec Ltd., Germany) with an accuracy of 0.1°C was used for sample drying. The samples were dried with air that had a temperature of 103±2°C. A moisture analyser, MAC 210/WH (Radwag LLC, USA) was also used to compare the detected results. The thermal parameters were measured using thermal analyser Isomet 2104 (Applied Precision Ltd., Slovakia) and a surface probe with a measuring range of 0.04-0.3 W m K. The measurement procedure is based on the DPS method described by Malinarič and Dieška (2009). A mathematical description was presented in detail by Wakeham et al. (1991) and Liang (1995). RESULTS AND DISCUSSION In the first series of measurements the values of thermal conductivity, thermal diffusivity and volume specific heat in the tangential direction were determined. In the second series, the same samples were examined in the radial direction. Each point in the graphical dependencies shown in Figs 1-4 represents the arithmetic average from twenty measurements. All of the experimental results were statistically processed. The calculated relative probable errors were in the range of 0.115-0.365%. Based on the regression analysis results, the regression equations describing the relationship between the measured thermophysical parameters and the relative moisture content were identified. Thermal conductivity as a function of relative moisture content for samples of softwood, medium hardwood, and hardwood with tangential and radial direction of wood fibres can generally be described by the linear function of Eq. (1) with regression coefficients being presented in Table 1.