Effects of Thermal Conductivity Data on Accuracy of Modeling Heat Transfer in Wood

W. Olek, J. Weres, and R. Guzenda


Data sets of wood thermal properties differing in their complexity are presented and discussed. A number of numerical experiments of the heat transfer in wood are performed, and the predicted temperatures are compared to the experimental data obtained for European beech and Scots pine wood. The analysis of similarity of the heat transfer model together with the different empirical data of wood thermal properties to the results of the experiments showed that the lowest accuracy of temperature prediction was obtained for the constant data. Application of advanced models of the thermal conductivity required a large amount of input data and sometimes gave relatively low accuracy in temperature prediction. Application of the thermal conductivity models developed by the authors with the use of the Inverse Heat Transfer Problem approach produced the best temperature prediction accuracy.

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