Thermal conductivity characteristics of frozen silty clay and a new predictive model DOI

Bo Liu,

Lulu He, Congcong Li

и другие.

International Journal of Thermal Sciences, Год журнала: 2024, Номер 210, С. 109642 - 109642

Опубликована: Дек. 20, 2024

Язык: Английский

Experimental study on thermal conductivity and microscopic characterization of sandy clay in deep buried formation DOI Open Access
Cao Yi, Yansen Wang, Chuanxin Rong

и другие.

SOILS AND FOUNDATIONS, Год журнала: 2025, Номер 65(1), С. 101565 - 101565

Опубликована: Янв. 7, 2025

Язык: Английский

Процитировано

0

Mitigating frost heave of an expansive soil channel reinforced with soilbags: Insights from physical model tests DOI

Zhang Yong-gan,

Yang Lu, Sihong Liu

и другие.

Geotextiles and Geomembranes, Год журнала: 2025, Номер 53(3), С. 713 - 727

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Variations of soil thermal conductivity in the Three-River Source Region, Qinghai‒Xizang Plateau DOI Creative Commons

Jia Liu,

Dongliang Luo,

W. Lei

и другие.

Advances in Climate Change Research, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Prediction of Thermal Diffusivity of Non-Plastic Soil for the Design of Ground Heat Exchanger Using Machine Learning Approach DOI

Namit Jaiswal,

Pawan Kishor Sah, Shiv Shankar Kumar

и другие.

Indian geotechnical journal, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Performance of thermally enhanced backfill material in vertical ground heat exchangers under continuous operation in a cooling season DOI
Xinyue Liu, Guozhu Zhang,

Ruichun Wu

и другие.

Applied Thermal Engineering, Год журнала: 2024, Номер unknown, С. 124442 - 124442

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

2

Surface decoration of flexible Si3N4 nanowire membrane by hydroxyapatite micron-flake with excellent thermal insulation at 1300 °C DOI

Yeye Liu,

Leilei Zhang, Fei Zhao

и другие.

Materials Characterization, Год журнала: 2024, Номер 211, С. 113905 - 113905

Опубликована: Апрель 11, 2024

Язык: Английский

Процитировано

1

Evaluating soil thermal conductivity for buried infrastructure: Impact of water salinity, mineral composition, and moisture content on heat transfer DOI
Oladoyin Kolawole,

Saad Rehmatullah,

Vatsal Shah

и другие.

Deleted Journal, Год журнала: 2024, Номер 1(2-3), С. 100014 - 100014

Опубликована: Авг. 10, 2024

Thermal conductivity of soils is a critical soil property in geotechnics, which provides essential information about the soil's ability to conduct heat transfer. Erroneous data can be responsible for inefficient design buried infrastructure systems that rely on transfer, such as cables, piping, and geothermal systems. There lack fundamental knowledge thermal under in-situ conditions factoring type, alteration moisture content, salinity. Our research aims address how groundwater, flooding, or drought impact due moderate-to-high salinity levels; these may factors considered testing infrastructure. This study investigated influence concentrations conductivity, with potential implications areas high water table, rainfall, flooding events, well offshore wind projects. accounted variations type when soil. Twenty-three (23) experimental tests were conducted resulting 36 points recorded. The results further analyzed comparison obtained from using current industry-accepted methodology, does not account varying concentrations. suggest sand was most conductive added 15 g/L brine. Further, concentration increase (silty clay) decrease (sandy soil) at contents, could provide more informed, economical relies transfer through soils.

Язык: Английский

Процитировано

1

Numerical Simulation of Heat Transfer of Porous Rock Layers in Cold Sandy Regions DOI Creative Commons
Kaichi Qiu, Yong Huang, Fenglei Han

и другие.

Atmosphere, Год журнала: 2023, Номер 14(12), С. 1812 - 1812

Опубликована: Дек. 11, 2023

The heat transfer characteristics of porous rock layers (PRLs) have significant seasonal differences. This feature has been used to protect the permafrost subgrade under highways and railways from degeneration. However, in cold sandy environments, transformation law PRLs on account climate warming aeolian sand filling needs be solved. work developed a coupled model for soil–PRL system aimed at analyzing convective process mechanism closed PRL. Furthermore, impact cooling performance PRL different mean annual air temperatures (MAATs) −3.5, −4.5, −5.5 °C was quantified. numerical results indicated that natural convection occurred only winter, effective height layer decreased with sand-filling thickness. As thickness increased, critical temperature difference occurrence accompanied by decreases Rayleigh number, duration, intensity convection. When exceeded 80 cm, would not occur Under scenario 0.052 °C·a−1, could offset adverse raise table first 20 years. Moreover, can more regions colder MAATs. For zones, sand-control measures should taken maintain long-term study is great significance guiding embankment design road maintenance along Qinghai–Tibetan Railway.

Язык: Английский

Процитировано

1

Investigation of Temperature Variation Characteristics and a Prediction Model of Sandy Soil Thermal Conductivity in the Near-Phase-Transition Zone DOI Creative Commons
Jine Liu,

Panting Liu,

Hui He

и другие.

Applied Sciences, Год журнала: 2024, Номер 14(20), С. 9337 - 9337

Опубликована: Окт. 14, 2024

Soil thermal conductivity in the near-phase-transition zone is a key parameter affecting stability of permafrost engineering and its catastrophic processes. Therefore, accurately determining soil this specific temperature has important theoretical significance. In present work, method for testing fine sandy was proposed by measuring with transient plane heat source volumetric capacity weighing unfrozen water contents. The content sand specimens tested, corresponding empirical fitting formula established. Finally, based on results, variation trends influence laws were analyzed, prediction models multiple regression (MR) radial basis function neural network (RBFNN) also results show following: (1) average error test work reference steady-state flow only 7.25%, which validates reliability method. (2) contents range 0~−3 °C accounts over 80% entire negative range. curves exhibit similar trend, can be divided into drastic phase transition stable zone. (3) Increases mainly occur zone, where these increases account about 60% total increase region. With density content, rate gradually decreases. (4) R2, MAE, RSME RBFNN model are 0.991, 0.011, 0.021, respectively, better than those MR model.

Язык: Английский

Процитировано

0

A generalized thermal conductivity model of soil-rock mixture based on freezing characteristic curve DOI

Yindong Wang,

Jianguo Lu, Wansheng Pei

и другие.

Cold Regions Science and Technology, Год журнала: 2024, Номер 229, С. 104360 - 104360

Опубликована: Ноя. 10, 2024

Язык: Английский

Процитировано

0