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Effect of moisture content, temperature, and microstructure on the thermal conductivity of loess and its prediction model

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Abstract

The thermal conductivity of soil is an essential parameter for designing geothermal energy foundations and borehole heat exchange systems. To effectively improve the development efficiency of geothermal resources in the loess region of China, the plane heat source method was used to measure the thermal conductivity of loess samples with different water contents and temperatures, and scanning electron microscopy tests were conducted. Analyze the effects of water content, temperature, and soil microstructure on thermal conductivity. A weighted geometric mean model considering the soil temperature effect is proposed and compared with the traditional model. The experimental results reveal that soil thermal conductivity increases in stages as the temperature rises. After the temperature exceeds 30℃, the contribution of steam latent heat transfer to soil thermal conductivity gradually becomes significant. Within the temperature range of 1–60℃, the thermal conductivity increases with increasing saturation and tends to stabilize after saturation exceeds 60%; When the temperature is greater than 60℃, the thermal conductivity peaks near a saturation of 60%. As the water content increases, there is a significant difference in the thermal conductivity of undisturbed and remolded loess, which is related to the microstructure changes of the soil. The model calculation shows that the weighted geometric mean model proposed in this paper has the best prediction performance. The Leong model has good predictive performance for the thermal conductivity of loess, while the Gori and Lusen models have the lowest predictive accuracy.

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Acknowledgements

This presented work is supported by the Shanxi Provincial Science and Technology Integrated Innovation Project (No.2012KTCQ03-01).

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Correspondence to Jingjing Wang.

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Wang, J., Zheng, J., Deng, J. et al. Effect of moisture content, temperature, and microstructure on the thermal conductivity of loess and its prediction model. Bull Eng Geol Environ 83, 206 (2024). https://doi.org/10.1007/s10064-024-03705-x

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  • DOI: https://doi.org/10.1007/s10064-024-03705-x

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