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

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  • Jiaming Wang

    (College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China
    Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China)

  • Hailong He

    (College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China)

  • Miles Dyck

    (Department of Renewable Resources, University of Alberta, Edmonton T6G2H1, Edmonton, AB T6G 2E3, Canada)

  • Jialong Lv

    (College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China
    Key Laboratory of Plant Nutrition and the Agri-Environment in Northwest China (Ministry of Agriculture), Northwest A&F University, Yangling 712100, China)

Abstract

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.

Suggested Citation

  • Jiaming Wang & Hailong He & Miles Dyck & Jialong Lv, 2020. "A Review and Evaluation of Predictive Models for Thermal Conductivity of Sands at Full Water Content Range," Energies, MDPI, vol. 13(5), pages 1-15, March.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1083-:d:326936
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    References listed on IDEAS

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