气候变化领域集成服务门户(CCPortal): Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network

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DOI	10.1155/2021/5555565
	Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network
	Ren, Xiuling; You, Yanhui; Yu, Qihao; Zhang, Guike; Yue, Pan; Jin, Mingyang
通讯作者	Yu, QH (通讯作者)，Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Frozen Soil Engn, Lanzhou 730000, Gansu, Peoples R China.
发表日期	2021
ISSN	1687-8434
EISSN	1687-8442
卷号	2021
英文摘要	Thermal conductivity is an important thermal parameter in engineering design in cold regions. By measuring the thermal conductivity of clay using a transient hot-wire method in the laboratory, the influential factors of the thermal conductivity of soils during the freezing process were analyzed, and a predictive model of thermal conductivity was developed with an artificial neural network (ANN) technology. The results show that the variation of thermal conductivity can be divided into three stages with decreasing temperature, positive temperature stage, transition stage, and negative temperature stage. The thermal conductivity increases sharply in the transition stage. The difference between the thermal conductivity at positive and negative temperature is small when the dry density of the soil specimens is larger than the critical dry density, while the difference is large if the dry density is less than the critical dry density. As the negative temperature decreases, the larger the moisture content of the soil specimens, the larger the increase of thermal conductivity. The effect of initial moisture content on thermal conductivity is more significant than that of dry density and temperature. The change tendency of the thermal conductivity calculated by the established ANN model is basically consistent with that of the laboratory-measured values, indicating that this model can be able to accurately predict the thermal conductivity of the soil specimens in the freezing process.
语种	英语
WOS研究方向	Materials Science
WOS类目	Materials Science, Multidisciplinary
WOS记录号	WOS:000637808100002
来源期刊	ADVANCES IN MATERIALS SCIENCE AND ENGINEERING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/253718
作者单位	[Ren, Xiuling; You, Yanhui; Yu, Qihao; Jin, Mingyang] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Frozen Soil Engn, Lanzhou 730000, Gansu, Peoples R China; [Ren, Xiuling; Jin, Mingyang] Univ Chinese Acad Sci, Beijing 100049, Peoples R China; [Zhang, Guike; Yue, Pan] Yalong River Hydropower Dev Co Ltd, Chengdu 610065, Sichuan, Peoples R China
推荐引用方式 GB/T 7714	Ren, Xiuling,You, Yanhui,Yu, Qihao,et al. Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network[J]. 中国科学院西北生态环境资源研究院,2021,2021.
APA	Ren, Xiuling,You, Yanhui,Yu, Qihao,Zhang, Guike,Yue, Pan,&Jin, Mingyang.(2021).Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network.ADVANCES IN MATERIALS SCIENCE AND ENGINEERING,2021.
MLA	Ren, Xiuling,et al."Determining the Thermal Conductivity of Clay during the Freezing Process by Artificial Neural Network".ADVANCES IN MATERIALS SCIENCE AND ENGINEERING 2021(2021).