岩土力学 ›› 2023, Vol. 44 ›› Issue (S1): 1-11.doi: 10.16285/j.rsm.2022.1967

• 基础理论与实验研究 •    下一篇

多因素影响下黏土比热容变化规律及预测模型

雷华阳1, 2,薄钰1,马长远1,王磊1,章纬地1   

  1. 1. 天津大学 建筑工程学院,天津 300354;2. 天津大学 滨海土木工程结构与安全教育部重点实验室,天津 300354
  • 收稿日期:2022-12-17 接受日期:2023-04-19 出版日期:2023-11-16 发布日期:2023-11-16
  • 作者简介:雷华阳,女,1974年生,博士,教授,主要从事岩土工程等方面的教学与研究工作。
  • 基金资助:
    国家自然科学基金面上项目(No. 52078334)

Variation pattern and prediction model of clay specific heat capacity considering multi-factors

LEI Hua-yang1, 2, BO Yu1, MA Chang-yuan1, WANG Lei1, ZHANG Wei-di1   

  1. 1. Department of Civil Engineering, Tianjin University, Tianjin 300354, China; 2. Key Laboratory of Coast Civil Structure Safety of Ministry of Education, Tianjin University, Tianjin 300354, China
  • Received:2022-12-17 Accepted:2023-04-19 Online:2023-11-16 Published:2023-11-16
  • Supported by:
    This work was supported by the General Program of National Natural Science Foundation of China (52078334).

摘要: 在“双碳”目标背景下,土体比热容作为重要的热物理性质参数之一,在能源地下结构、地铁通风计算、地埋管线、核废料处置、冻结法施工、农耕灌溉等众多领域有着重要的意义。对不同初始干密度、初始含水率的黏土试样,在不同温度条件下开展了比热容测试分析,探讨了其变化规律及机制。试验结果表明:黏土比热容随初始干密度、初始含水率的增加而线性增加,且与温度的三次方呈正比。比热容变化机制与黏土三相比例变化、固相晶格振动、水冰相变等因素有关。建立了考虑多因素的黏土比热容预测模型,与反向传播神经网络(BP-ANN)预测模型、简化理论预测模型、其他经验预测模型的交叉验证结果显示,该模型在适用范围、预测性能等方面都具有较优的表现,可为理论计算、数值仿真、工程实践中黏土比热容的取值和计算提供可靠参考。

关键词: 黏土, 比热容, 预测模型, 多影响因素, 热物理性质

Abstract: In the context of the “carbon peaking and carbon neutrality” goals, the specific heat capacity of soil, as one of the important thermophysical parameters, plays an important role in many fields such as energy geo-structure, subway ventilation calculation, buried pipelines, nuclear waste disposal, artificial ground freezing, agricultural irrigation, etc. A specific heat capacity test was carried out on clay samples with different initial dry densities and initial water contents under different temperature conditions, and the variation patterns and mechanisms were investigated. The test results indicate that the specific heat capacity of clay increases linearly with the increase of initial dry density and initial water content, and is proportional to the third power of temperature. The mechanism of the variation of specific heat capacity is related to the variation of three-phase percentage, solid-phase lattice vibration, and water-ice phase transition. A model for predicting the specific heat capacity of clay considering multi-factors is established and cross-validated with back propagation artificial neural network (BP-ANN) model, simplified theoretical model and other empirical models. The comparison shows that the prediction model has better performance in terms of applicability and accuracy, which can provide a reliable reference for specific heat capacity determination in theoretical calculations, numerical simulations, and engineering practice.

Key words: clay, specific heat capacity, prediction model, multi-factors, thermophysical properties

中图分类号: TU 442
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