土壤导热系数预测模型评估及参数分析

刘凤云; 罗怀瑞; 万旭升; 谢飞; 蒋杰; 骆吉庆

doi:10.3724/j.gyjzG23072412

土壤导热系数预测模型评估及参数分析

doi: 10.3724/j.gyjzG23072412

1. 西南石油大学土木工程与测绘学院, 成都 610500;
2. 中国石油川庆钻探工程有限公司安全环保质量监督检测研究院, 四川广汉 618300

基金项目:

国家自然科学基金项目（42271146，42071087）；西南石油大学起航计划（2021QHZ003）。

详细信息

作者简介:
刘凤云，博士，讲师，硕士生导师，主要从事寒区岩土工程研究，liufengyun0634@163.com。

通讯作者:
万旭升，博士，教授，硕士生导师，主要从事盐胀机理及寒区工程研究，xinyanwanxxusheng@163.com。

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出版历程
- 收稿日期: 2023-07-24
- 网络出版日期: 2026-04-11
- 刊出日期: 2026-03-20

Evaluation of Thermal Conductivity Coefficient Prediction Models of Soil and Their Parameter Analysis

1. School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China;
2. Safety and Environmental Protection Quality Supervision and Testing Institute of CNPC Chuanqing Drilling Engineering Company Limited, Guanghan 618300, China

摘要

摘要: 土壤导热系数是土壤传热分析的重要热物理参数，广泛应用于涉及热效应的领域。由于试验测量土壤导热系数面临诸多困难，准确预测土壤导热系数至关重要。为此，使用土壤导热系数试验数据，评估了4种经典土壤导热系数预测模型的预测精度，分析了模型参数对导热系数预测值以及孔隙率对模型参数取值的影响。为提高预测的准确性，基于评估结果，使用表现最优的模型对不同土质的土壤导热系数进行了预测；为提高模型的适用性，建立了模型参数计算模型。结果表明：1）在不同的土壤中，Bi-Zhang-Chen模型的整体计算精度最高，其次为Côté-Konrad模型、Lu-Ren-Gong模型、Chen模型。其中，Bi-Zhang-Chen模型对砂土、黄土、粉土以及粉质黏土的计算误差较小，Côté-Konrad模型对石英砂土的计算结果更准确。2）针对同一地区的土壤，土壤孔隙率对模型参数的取值有较大的影响，尤其在黄土中表现出较强的规律性。3）根据土壤类型选择不同的预测模型能够更好地预测不同土质的土壤导热系数，且基于模型评估和参数分析建立的参数计算模型能够很好地预测砂土、黄土、粉土以及粉质黏土的导热系数。
- 土壤导热系数 /
- 模型评估 /
- 参数分析 /
- 孔隙率 /
- 参数取值
Abstract: Soil thermal conductivity is an important thermophysical parameter for soil heat transfer analysis， widely used in fields involving thermal effects. Accurate prediction of soil thermal conductivity is crucial due to numerous challenges in measuring soil thermal conductivity. In terms of that， this study utilized experimental data on soil thermal conductivity to evaluate the prediction accuracy of four classical models， then examined the impact of model parameters on the predicted values of thermal conductivity， and porosity on the value selecting of model parameters. To enhance the prediction accuracy， this research used the best-performing model to predict the soil thermal conductivity with different soil textures based on the evaluation results. A parameter calculation model was also developed to improve the model's applicability. The results indicated that： 1） the Bi-Zhang-Chen model exhibited the highest overall calculation accuracy among different soils， followed by the Côté-Konrad model， the Lu-Ren-Gong model， and the Chen model. More specifically， the Bi-Zhang-Chen model showed small calculation errors for sandy soil， loess， silty soil， and clay， while the Côté-Konrad model yielded more accurate results for quartz sand soil. 2） Soil porosity had a significant impact on model parameter values in the same region， particularly showing strong regularity in loess. 3） Selecting different prediction models based on soil types can better predict the thermal conductivity of soils with different textures. The parameter calculation model established through model evaluation and parameter analysis can effectively predict the thermal conductivity of sandy soil， loess， silty soil， and clay. This study provides theoretical references for the improvement and establishment of soil thermal conductivity models.
- thermal conductivity coefficient of soil /
- model evaluation /
- parameter analysis /
- porosity /
- parameter value

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