A predictive model for the thermal conductivity of silty clay soil based on soil porosity and saturation

被引：2
作者：
Chao Lyu
Qiang Sun
Weiqiang Zhang
Jishi Geng
机构：
[1] China University of Mining and Technology,Key Laboratory of Coalbed Methane Resources and Reservoir Formation Process, Ministry of Education
[2] China University of Mining and Technology,School of Resources and Geosciences
[3] Xi’an University of Science and Technology,Geological Research Institute for Coal Green Mining
[4] Xi’an University of Science and Technology,College of Geology and Environment
来源：
Arabian Journal of Geosciences | 2020年 / 13卷
关键词：
Soil thermal conductivity; Saturation; Porosity; Predictive model;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Soil thermal conductivity is a property that represents a soil’s capability of transferring energy and has been a common subject of study in soil science, geotechnical engineering, and geology. In this study, the quantitative effects of density, water content, saturation, and porosity on thermal conductivity of soil in Fengxian County are investigated by the field and laboratory tests. A new model for predicting soil thermal conductivity from its porosity, saturation, and quartz content is developed. In the field test, the thermal conductivity has a linear relationship with water content due to the increase in thickness of hydration film which decreases the thermal contact resistance between particles. A good logarithmic function is found for the relationship between thermal conductivity and natural density of silty clay soil in Fengxian County. In the laboratory test, there is a linear function for the relationship between thermal conductivity and density of silty clay soil. The thermal conductivity linearly increases with water content and decreases slightly when water content exceeds 17.65% due to the decreased density. The predicted thermal conductivity with the new model is compared with measured thermal conductivity from the field and laboratory tests. The root mean square error (RMSE) of the new model is 0.098 and 0.096 W m−1 K−1, respectively, which indicates that the new model provides accurate approximations of soil thermal conductivity in Fengxian County, China.
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