摘要
回填材料的导热系数是影响地源热泵系统性能的关键参数。在土壤中掺入石英砂、石墨、铁尾矿砂等导热性能较好的物质可以有效提高回填材料的导热性能。选用铁尾矿砂与钠基膨润土组成混合材料,制备不同掺砂率、不同干密度以及不同含水率的试样。使用TC3000E瞬态热线法导热系数仪测定试样导热系数,分析其与掺砂率、干密度、含水率、饱和度等参数的关系,并探讨铁尾矿砂-膨润土混合材料导热系数预测模型。研究表明,混合材料的导热系数随掺砂率、干密度和含水率增大而增大。不同孔隙率下,导热系数与饱和度存在线性关系,并且孔隙率与各组拟合方程的斜率呈线性关系。基于Maxwell方程对悬浮物体积分数进行修正,构建铁尾矿砂-膨润土导热系数预测模型,能够较好地预测混合材料的导热系数。
Thermal conductivity of backfill material is the key parameter affecting the performance of ground source heat pumps(GSHPs)system.Quartz sand,graphite,iron tailings and other additives with high thermal conductivity can effectively improve the thermal property of bentonite.Mixtures of iron tailing sand and sodium bentonite with different sand ratio,dry densities and water contents were compacted,and TC3000E Transient hotline Thermal Conductivity Tester was used to measure thermal conductivity of the mixtures.The experimental results were analyzed to observe the effects of sand content,dry density,water contents and degree of saturation on the thermal conductivity.In addition,the prediction model of thermal conductivity of bentonite/iron tailing sand mixtures was discussed.It is found that the thermal conductivity increases with the increase of sand content,dry densities and water content.Under different porosity,linear correlations were observed between thermal conductivity and degree of saturation,and the porosity has also a linear relationship with the slope of each fitting equation.Based on Maxwell equation,the volume fraction of suspended solids was modified,and the prediction model of thermal conductivity of bentonite/iron tailing sand mixtures was established,which can better predict the thermal conductivity of mixed materials.
作者
贾志文
陈鑫
李栋伟
JIA Zhi-wen;CHEN Xin;LI Dong-wei(School of Civil and Architectural Engineering, East China University of Technology, Nanchang 330013, China)
出处
《科学技术与工程》
北大核心
2022年第7期2814-2822,共9页
Science Technology and Engineering
基金
国家自然科学基金(42061011,41977236)
江西省自然科学基金(20192ACBL20002)。
关键词
导热系数
回填材料
铁尾矿砂-膨润土混合材料
预测模型
地源热泵
thermal conductivity
backfill material
bentonite/iron tailing sand mixtures
prediction model
ground source heat pump
