摘要
研究不同类型土壤导热系数变化规律及影响因素,对陆地表层水热迁移、地源热泵和土壤储热等的基础研究和生产应用有重要意义。利用热探针法对10~90℃和0~20%体积含水率的中砂和粗砂的导热系数变化规律进行试验研究,并给出低温和高温下两种砂土导热系数随含水率变化的经验公式。试验结果显示:温度和含水率的变化都对砂土的导热系数有影响,且含水率对导热系数的贡献率大于温度。在温度和含水率的共同作用下,导热系数变化显著。砂土在低温段(≤30℃)时,导热系数变化不明显,在高温段(≥60℃)时,导热系数变化显著。无论对粗砂还是中砂、低温还是高温,都存在使导热系数能达到极值点的最佳体积含水率,中砂的最佳体积含水率为0.18~0.21 m^3/m^3,粗砂的最佳体积含水率为0.16~0.17 m^3/m^3。
It is of great significance for the basic research and production application of surface heat and moisture transfer,ground source heat pump and soil heat storage to study the variation law and influencing factors of thermal conductivity of different types of soil.Hence,the thermal conductivity of medium sand and coarse sand with 10℃~90℃and 0~20%volume water content were experimentally studied by the thermal probe method,and the empirical formulas for the thermal conductivity of two types of sand with variable moisture content were given at both low temperature and high temperature.The results show that both the changes in temperature and moisture content will affect the thermal conductivity of sand,and the effect of moisture content on the thermal conductivity is greater than that of temperature.At high temperature(≥60℃),the thermal conductivity changes significantly.In conditions of coarse sand or medium sand,or low temperature or high temperature,there is an optimal volumetric water content that can make the thermal conductivity the extreme point,the optimal volumetric moisture content of medium sand is between 0.18~0.21 m^3/m^3,and the optimal volumetric moisture content of coarse sand is between 0.16~0.17 m^3/m^3.
作者
熊坤
晋华
桂金鹏
郭毅
XIONG Kun;JIN Hua;GUI Jin-peng;GUO Yi(College of Water Resources Science and Engineering,Taiyuan University of Technology,Taiyuan 030024,China;College of Water Resources and Hydro-electric Engineering,Xi’an University of Technology,Xi’an 710048,China)
出处
《科学技术与工程》
北大核心
2020年第35期14625-14630,共6页
Science Technology and Engineering
基金
国家自然科学基金(41372247)
山西省回国留学人员科研项目(2017-045)。
关键词
导热系数
高温
含水率
拟合公式
最佳体积含水率
thermal conductivity
high temperature
moisture content
regression formula
optimal volumetric moisture content