周殷康, 阎长虹, 谢胜华, 郑军, 方圆, 刘鹏. 2019: 基于细观模拟的软土导热系数数值预测模型. 工程地质学报, 27(5): 1070-1077. DOI: 10.13544/j.cnki.jeg.2019078
    引用本文: 周殷康, 阎长虹, 谢胜华, 郑军, 方圆, 刘鹏. 2019: 基于细观模拟的软土导热系数数值预测模型. 工程地质学报, 27(5): 1070-1077. DOI: 10.13544/j.cnki.jeg.2019078
    ZHOU Yinkang, YAN Changhong, XIE Shenghua, ZHENG Jun, FANG Yuan, LIU Peng. 2019: A NUMERICAL MODEL FOR THERMAL CONDUCTIVITY OF SOFT SOILS BASED ON MESOSCOPIC SIMULATION. JOURNAL OF ENGINEERING GEOLOGY, 27(5): 1070-1077. DOI: 10.13544/j.cnki.jeg.2019078
    Citation: ZHOU Yinkang, YAN Changhong, XIE Shenghua, ZHENG Jun, FANG Yuan, LIU Peng. 2019: A NUMERICAL MODEL FOR THERMAL CONDUCTIVITY OF SOFT SOILS BASED ON MESOSCOPIC SIMULATION. JOURNAL OF ENGINEERING GEOLOGY, 27(5): 1070-1077. DOI: 10.13544/j.cnki.jeg.2019078

    基于细观模拟的软土导热系数数值预测模型

    A NUMERICAL MODEL FOR THERMAL CONDUCTIVITY OF SOFT SOILS BASED ON MESOSCOPIC SIMULATION

    • 摘要: 热环境控制是城市地下空间安全运行的有力保障,科学预测地下围岩的导热性能是地下空间环控系统热负荷评估的基础。软土是地下空间开发中一类常见土体,现有模型主要适合于预测中低含水率范围内土体导热系数的变化,而对于高含水率软土,合适的导热系数预测模型较少。基于细观模拟,本文提出了一种能有效预测软土导热系数的数值模型。该模型除了能够反映含水率、干密度等常规因素影响外,还可考虑矿物组成以及粒径分布等的影响。最后,通过与苏通GIL管廊工程中20个软土样的实测导热系数进行对比以验证数值模型的可靠性。首先借助激光粒度分析仪和X射线衍射分析测试了矿物组成和粒度分布,代入模型进行数字建模并通过细观导热模拟得到导热系数预测值。导热系数模拟预测值与实测值对比结果显示:模拟预测值基本在实测值±20%范围内,验证了本文模型的可靠性,表明了该模型在预测高含水率软土导热系数方面的潜力。此外,该模型还可以直观地展示土内各处局部热流的分布特征,这为深入认识土体导热行为的机理奠定了基础。本文研究可为软土以及土体导热系数的预测评价提供新的思路和方法。

       

      Abstract: Thermal environment control is a powerful guarantee for the safe operation of utility tunnel. A precise estimation for soil thermal conductivity is just the critical basis for the thermal load of environment control system in underground space. Soft soils are very common in the development of underground space, especially in highly urbanized areas. Most available studies on soil thermal conductivity focus on the range of low and intermediate water content, but there is rarely a model suitable for unsaturated soft soils with high water content. Based on mesoscopic simulation, a numerical model is proposed in the present study for unsaturated soft soils with high water content. This model can include traditional factors like water content and dry density. It also can reveal the influence of mineralogy and particle size. Finally, the numerical model is validated by the experimental data of 20 soil samples in Su-Tong GIL utility tunnel project. The mineralogy composition and particle size distribution are measured in advance from X-ray diffraction analysis and laser particle size analyzer, from which the model parameters are derived and then the effective thermal conductivity can be reached by mesoscopic simulation of heat conduction. Results show that the values of most the modelled thermal conductivity are located within the±20%ranges of experimental data, which verifies the reliability of the numerical model in the present study. In the same time, it indicates that this numerical model has a potential application in predicting the thermal conductivity of unsaturated soft soils. Besides, this model can give a direct exhibition of local heat flux in soils, which lays a foundation for a better understanding on the mechanism of soil thermal behavior. The results in the present study can provide a new strategy and/or approach to estimate soils thermal conductivity.

       

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