A Review and Evaluation of Predictive Models for Thermal Conductivity of Sands at Full Water Content Range

The effective thermal conductivity ( λ eff ) of sands is a critical parameter required by applications in geothermal energy resources, geo-technique and geo-environment and in science disciplines. However, the availability of the reliable λ eff data is not sufficient and predictive models are usually used in practice to estimate λ eff . These predictive models may vary in complexity, flexibility, accuracy and applications. There is no universal model that can be applied to all soil types and full water content range. The choice of different models may result in distinctive estimates of λ eff . The objectives of this study were to conduct an extensive review of the thermal conductivity models of sands and evaluate their performance with a large dataset consisting of various sand types from dry to saturation. A total of 14 models to predict λ eff of sands were evaluated with a large compiled dataset consisting of 1025 measurements on 62 sands from 20 studies. The results show that the models of Chen 2008 (CS2008) and Zhang et al. 2016 (ZN2016) give the best estimates of thermal conductivity of sands, with Nash–Sutcliffe efficiency = 0.9 and RMSE = 0.3 W m −1 °C −1 . These two models are potentially applied to accurately estimate thermal conductivity of sands of different types.