院报 ›› 2019, Vol. 36 ›› Issue (12): 144-150.DOI: 10.11988/ckyyb.20180085

• 水工结构与材料 • 上一篇    下一篇

不同温度条件下混凝土导热系数影响因素研究

曹国举, 宫经伟, 马利, 张莹, 张梦丽, 赵毓奇, 刘相金   

  1. 新疆农业大学 水利与土木工程学院,乌鲁木齐 830052
  • 收稿日期:2018-01-23 出版日期:2019-12-01 发布日期:2019-12-20
  • 通讯作者: 宫经伟(1984-),湖北随州人,男,副教授,博士,主要从事水工混凝土材料热物理性能相关方面的研究。E-mail:gongjingwei034@163.com
  • 作者简介:曹国举(1990-),河南驻马店人,男,硕士研究生,主要从事混凝土材料导热性能相关方面的研究。E-mail:1256546887@qq.com
  • 基金资助:
    国家自然科学基金项目(51641906,51541909); 国家级大学生创新训练项目(201610758028)

Influence Factors of Thermal Conductivity of Concrete under Different Temperature Conditions

CAO Guo-ju, GONG Jing-wei, MA Li, ZHANG Ying, ZHANG Meng-li, ZHAO Yu-qi, LIU Xiang-jin   

  1. College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
  • Received:2018-01-23 Online:2019-12-01 Published:2019-12-20

摘要: 为了研究混凝土在不同温度条件下的导热系数变化规律,利用单因素试验方法,以骨料体积分数、砂率、水胶比、饱和度粉煤灰掺量、矿渣掺量为因素,采用QTM-500导热仪测试混凝土在不同温度条件下(-30~20 ℃)的导热系数,并分析各影响因素对混凝土导热系数在不同温度条件下的变化规律,最终得出混凝土导热系数与各因素之间的预测方程。结果表明:混凝土导热系数与温度呈负相关性;混凝土导热系数随着骨料体积分数的增大而增大,随着砂率的增大而减小;干燥状态下,混凝土导热系数随着水胶比的增大而减小;饱和状态下,混凝土导热系数大于干燥状态下混凝土导热系数,随着温度的降低,尤其在0~-10 ℃时,混凝土导热系数骤增;混凝土导热系数随着粉煤灰、矿渣掺量的增加而减小;通过对试验结果进行多元回归,得到了混凝土导热系数与各因素之间的计算模型,该模型预测精度较高。研究结果可为混凝土结构内部温度场的精确计算、保温隔热性能以及表面裂缝的控制提供理论依据。

关键词: 混凝土, 温度, 导热系数, 影响因素, 多元回归

Abstract: The thermal conductivity of concrete was measured by QTM-500 thermal conductivity instrument at different temperatures (-30 ℃-20 ℃) with volume fraction of aggregate, sand ratio, water-binder ratio, fly ash content and slag content as variables. The prediction equation between thermal conductivity of concrete and the aforementioned factors was obtained by analyzing the changes of thermal conductivity affected by these factors at different temperatures. Results revealed that thermal conductivity of concrete was negatively correlated with temperature and sand ratio, while positively correlated with aggregate’s volume fraction; at dry state, thermal conductivity decreased with the increase of water-binder ratio, while at saturated state, thermal conductivity was greater than that under dry condition, and with the decline of temperature, especially at 0 ℃ -10 ℃, thermal conductivity increased dramatically. The thermal conductivity of concrete also reduced with the rise of fly ash and slag dosages. In addition, through multivariate regression analysis of the test results, a calculation model of high prediction accuracy between thermal conductivity of concrete and these factors was obtained. The research findings provide a more important theoretical basis for the accurate calculation of the temperature field in the concrete structure, the thermal insulation performance and the control of surface cracks.

Key words: concrete, temperature, thermal conductivity, influencing factors, multiple regression

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