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General Thermal Conductivity Function for Unsaturated Soils Considering Effects of Water Content, Temperature, and Confining Pressure

AbstractThe thermal conductivity function (TCF) is an important constitutive function establishing the thermal conductivity–water content relationship in unsaturated soils. The existing TCFs do not account for the effects of confining pressure, nor do they consider thermal induced changes in pore st...

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Bibliographic Details
Published in:Journal of geotechnical and geoenvironmental engineering 2021-11, Vol.147 (11)
Main Authors: Duc Cao, Toan, Kumar Thota, Sannith, Vahedifard, Farshid, Amirlatifi, Amin
Format: Article
Language:English
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Summary:AbstractThe thermal conductivity function (TCF) is an important constitutive function establishing the thermal conductivity–water content relationship in unsaturated soils. The existing TCFs do not account for the effects of confining pressure, nor do they consider thermal induced changes in pore structure and degree of saturation. This study presents a general TCF by considering the temperature effects on pore structure, degree of saturation, different heat transfer mechanisms (i.e., conduction, convection, and latent heat of vaporization), and the confining pressure. The TCF is linked to a temperature-dependent soil water retention curve (SWRC) model to include the impact of temperature on pore structure and degree of saturation. The proposed model applies a decay function to the degree of saturation to account for thermally induced changes in heat transfer mechanisms through conduction and convection of pore water in both liquid and vapor phases and latent heat transfer due to vaporization. A new function is introduced into the TCF to incorporate the effects of confining pressure on thermal conductivity that corresponds to the void ratio changes. The proposed TCF was validated against experimentally measured data for several different soils at zero confining pressure and one soil at various confining pressures reported in the literature. The comparison showed that the proposed TCF can capture laboratory-measured data properly, with prediction errors significantly lower than those from several alternative models.
ISSN:1090-0241
1943-5606
DOI:10.1061/(ASCE)GT.1943-5606.0002660