岩土力学 ›› 2023, Vol. 44 ›› Issue (3): 884-895.doi: 10.16285/j.rsm.2022.1321

• 基础理论与实验研究 • 上一篇    下一篇

珊瑚砂热物理参数测试与预测模型对比分析

彭赟1, 2,胡明鉴1,阿颖3,王雪晴1, 4   

  1. 1. 中国科学院武汉岩土力学研究所 岩土力学与工程国家重点实验室,湖北 武汉 430071;2. 桂林理工大学 土木与建筑工程学院,广西 桂林 541004;3. 中冶南方城市建设工程技术有限公司,湖北 武汉 430062;4. 中国科学院大学,北京 100049
  • 收稿日期:2022-07-03 接受日期:2022-08-20 出版日期:2023-03-21 发布日期:2023-03-24
  • 通讯作者: 胡明鉴,男,1974年生,博士,研究员,主要从事工程地质和水文地质方面的研究。E-mail: mjhu@whrsm.ac.cn E-mail:494188695@qq.com
  • 作者简介:彭赟,女,1997年生,硕士研究生,主要从事工程地质和水文地质方面的测试与分析研究。
  • 基金资助:
    国家自然科学基金项目(No.41572304)。

Testing of coral sand thermal physical parameters and comparative analysis of prediction models

PENG Yun1, 2, HU Ming-jian1, A Ying3, WANG Xue-qing1, 4   

  1. 1. State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China; 2. College of Civil Engineering and Architecture, Guilin University of Technology, Guilin, Guangxi 541004, China; 3. WISDRI City Construction Engineering & Research Incorporation Ltd., Wuhan, Hubei 430062, China; 4. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2022-07-03 Accepted:2022-08-20 Online:2023-03-21 Published:2023-03-24
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (41572304).

摘要: 在我国“海洋强国”建设下,南海岛礁建设顺利推进,以浅层礁坪为介质的地源热泵技术、能量桩等,实质是与礁砂介质能量交换的过程,需进一步掌握珊瑚砂导热性能的演变规律。以南海岛礁珊瑚细砂为研究对象,测定并探讨在不同干密度和含水率下对3大热物理参数的影响,并选用12种砂土热物理参数模型的预测数据与实测数据进行类比分析,提出适宜预测珊瑚细砂导热性能的经验模型。结果表明,珊瑚细砂导热系数和体积比热容、热扩散系数均与干密度呈正相关关系,导热系数和体积比热容与含水率的相关系数高于干密度,而热扩散系数与含水率呈“凸”形增长关系,与干密度的相关系数远高于含水率。基于试验实测数据进行线性回归分析,修订Cote-Konrad 模型与Gangadhara Rao 模型,显著提高模型对珊瑚细砂导热系数预测准确性;通过De Vries 模型与Xu 模型的线性修正,大幅缩小珊瑚细砂体积比热容预测值与实测值的差异,在 Dai 模型相关系数的二元拟合分析基础上,建立表征珊瑚细砂热扩散系数预测模型,为岛礁隔热、控温工程设计以及珊瑚砂热物理特性研究提供参考。

关键词: 珊瑚砂, 热物理参数, 含水率, 干密度, 预测模型

Abstract: The construction of islands and reefs in the South China Sea is progressing smoothly under the strengthening of China’s maritime development. The ground source heat pump technology and energy pile etc., which take shallow reef flat as medium, are essentially a process of energy exchange with reef sand medium, so it is necessary to further grasp the evolution law of thermal conductivity of coral sand. In this paper, coral fine sand of South China Sea reef was examined. Three thermophysical parameters including thermal conductivity, volumetric heat capacity, and thermal diffusivity, were measured, and the influence of dry density and water content on the thermophysical parameters were analyzed. The predicted data by 12 thermophysical parameter models for sand soil were compared with the measured data for analogical analysis. On this basis, an empirical model suitable for predicting the thermal conductivity of coral fine sand was developed. The results show that the thermal conductivity, volumetric heat capacity and thermal diffusivity of coral sand are positively correlated with dry density, and the correlation coefficients of thermal conductivity and volumetric heat capacity with water content are higher than that of dry density, while the correlation coefficient of thermal diffusivity with water content has a “convex” growth relationship, and the correlation coefficient with dry density is much higher than that of water content. The Cote & Konrad model and the Gangadhara Rao model were amended through the linear regression analysis of the measured data. The prediction accuracy of thermal conductivity of coral fine sand by the model was significantly improved. The difference between the predicted and measured values of the volumetric heat capacity of coral sand was significantly reduced by the linear correction of the De Vries model and the Xu model. Based on the binary fitting analysis of the correlation coefficient of Dai model, a prediction model characterizing the thermal diffusivity of coral fine sand was established to provide reference for the design of insulation and temperature control engineering of island reefs as well as the study of thermophysical properties of coral sand.

Key words: coral sand, thermophysical parameters, water content, dry density, predictive model

中图分类号: TU411
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