A model for predicting thermal conductivity of porous composite materials

An effective model of thermal conductivity (TC) can provide opportunity to design thermal insulation materials with specific insulation properties and contribute to the insulation industry by decreasing costs and saving time for laboratory testing. At present, there are five basic structural models, series, parallel, maxwell-eucken (ME) 1 and 2, and effective medium theory (EMT), which could be utilized to determine the TC of a material. In this study, these five basic models were selected to check which model is most suitable for estimating TC of porous composite materials. Two different types of materials (fiber composite and 3D-printed) were also selected as porous insulation materials, and their TC was determined experimentally. After that, experimental data were compared with the estimated data obtained from five basic models. It was found that among the five basic models, ME2 and EMT models give comparatively better predictions with average percentage differences (between experimental and estimated data) of 11.10% and 9.90%, respectively. However, the prediction of these existing models is not satisfactory enough to be used for commercial purposes. Hence, a model was developed combining ME1 and ME2 models. Tested results revealed that the proposed model provides better prediction of TC of porous composite materials. The average percentage differences between proposed models and experimental data are 3.12% and 0.92% for fibrous composite and printed insulation, respectively. This indicates that the accuracy of the proposed model is sufficient to be used in industrial sectors.