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<p>Soil thermal conductivity (STC) is a crucial parameter for the optimal design and safety assessment of underground thermal engineering projects. Accurate prediction of its variation with environmental temperature is therefore significant for guiding practical engineering applications. In this study, an improved effective medium model (IEM) for temperature-dependent STC was developed. By introducing the intraphase contact thermal resistance influence factor (<i>m</i>) and the interphase contact thermal resistance correction factor (<i>p</i>), the model effectively characterizes the nonlinear temperature dependence of contact thermal resistances as well as vapor latent-heat transport. A comprehensive experimental database containing 444 datasets spanning wide ranges of temperature (0 ~ 92&#xa0;°C), water content (0 ~ 45%), and dry density (1.1 ~ 1.84&#xa0;g/cm<sup>3</sup>) was established. Based on this database, a detailed analysis was conducted to investigate the influencing factors associated with temperature-induced variations of STC. The performance of the new model was systematically compared against traditional models. The computational results indicate that the proposed model markedly outperforms conventional models, achieving an <i>R</i><sup>2</sup> of 0.898 with <i>RMSE</i> and <i>MAE</i> as low as 0.231 and 0.131, respectively. Compared with the better-performing Tarnawski and Gori models, its <i>RMSE</i> is reduced by 18.4% and 58.6%, respectively. By introducing factors <i>m</i> and <i>p</i>, the new model describes the temperature dependence of STC across varying moisture conditions more accurately, offering broader applicability and stronger potential for practical engineering use.</p>

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Predictive model for the temperature effect on soil thermal conductivity based on effective medium theory

  • 期刊论文

  • 发表日期：

    2026年3月27日

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  • Yunshan Xu,
  • Keyao Zhao,
  • Jianping Li,
  • De’an Sun

摘要

Soil thermal conductivity (STC) is a crucial parameter for the optimal design and safety assessment of underground thermal engineering projects. Accurate prediction of its variation with environmental temperature is therefore significant for guiding practical engineering applications. In this study, an improved effective medium model (IEM) for temperature-dependent STC was developed. By introducing the intraphase contact thermal resistance influence factor (m) and the interphase contact thermal resistance correction factor (p), the model effectively characterizes the nonlinear temperature dependence of contact thermal resistances as well as vapor latent-heat transport. A comprehensive experimental database containing 444 datasets spanning wide ranges of temperature (0 ~ 92 °C), water content (0 ~ 45%), and dry density (1.1 ~ 1.84 g/cm3) was established. Based on this database, a detailed analysis was conducted to investigate the influencing factors associated with temperature-induced variations of STC. The performance of the new model was systematically compared against traditional models. The computational results indicate that the proposed model markedly outperforms conventional models, achieving an R2 of 0.898 with RMSE and MAE as low as 0.231 and 0.131, respectively. Compared with the better-performing Tarnawski and Gori models, its RMSE is reduced by 18.4% and 58.6%, respectively. By introducing factors m and p, the new model describes the temperature dependence of STC across varying moisture conditions more accurately, offering broader applicability and stronger potential for practical engineering use.