Analytical models for lunar soil thermal conductivity

1975 ◽  
Author(s):  
C. TIEN ◽  
A. NAYAK
Keyword(s):  
Thermal Conductivity ◽  
Lunar Soil ◽  
Analytical Models ◽  
Soil Thermal Conductivity

scholarly journals Assessment for Thermal Conductivity of Frozen Soil Based on Nonlinear Regression and Support Vector Regression Methods

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fu-Qing Cui ◽  
Wei Zhang ◽  
Zhi-Yun Liu ◽  
Wei Wang ◽  
Jian-bing Chen ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Support Vector Regression ◽  
Nonlinear Regression ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Frozen Soil ◽  
Support Vector ◽  
Soil Thermal Conductivity ◽  
Fine Grained ◽  
Fine Grained Soil

The comprehensive understanding of the variation law of soil thermal conductivity is the prerequisite of design and construction of engineering applications in permafrost regions. Compared with the unfrozen soil, the specimen preparation and experimental procedures of frozen soil thermal conductivity testing are more complex and challengeable. In this work, considering for essentially multiphase and porous structural characteristic information reflection of unfrozen soil thermal conductivity, prediction models of frozen soil thermal conductivity using nonlinear regression and Support Vector Regression (SVR) methods have been developed. Thermal conductivity of multiple types of soil samples which are sampled from the Qinghai-Tibet Engineering Corridor (QTEC) are tested by the transient plane source (TPS) method. Correlations of thermal conductivity between unfrozen and frozen soil has been analyzed and recognized. Based on the measurement data of unfrozen soil thermal conductivity, the prediction models of frozen soil thermal conductivity for 7 typical soils in the QTEC are proposed. To further facilitate engineering applications, the prediction models of two soil categories (coarse and fine-grained soil) have also been proposed. The results demonstrate that, compared with nonideal prediction accuracy of using water content and dry density as the fitting parameter, the ternary fitting model has a higher thermal conductivity prediction accuracy for 7 types of frozen soils (more than 98% of the soil specimens’ relative error are within 20%). The SVR model can further improve the frozen soil thermal conductivity prediction accuracy and more than 98% of the soil specimens’ relative error are within 15%. For coarse and fine-grained soil categories, the above two models still have reliable prediction accuracy and determine coefficient (R2) ranges from 0.8 to 0.91, which validates the applicability for small sample soils. This study provides feasible prediction models for frozen soil thermal conductivity and guidelines of the thermal design and freeze-thaw damage prevention for engineering structures in cold regions.

PREDICTING THE EFFECT OF TEMPERATURE ON SOIL THERMAL CONDUCTIVITY

Soil Science ◽  
1994 ◽  
Vol 158 (5) ◽  
pp. 307-313 ◽  
Author(s):  
G. S. CAMPBELL ◽  
J. D. JUNGBAUER ◽  
W. R. BIDLAKE ◽  
R. D. HUNGERFORD
Keyword(s):  
Thermal Conductivity ◽  
Effect Of Temperature ◽  
Soil Thermal Conductivity

Soil thermal conductivity prediction for district heating pre-insulated pipeline in operation

Energy ◽  
2012 ◽  
Vol 44 (1) ◽  
pp. 197-210 ◽  
Author(s):  
Matjaz Perpar ◽  
Zlatko Rek ◽  
Suvad Bajric ◽  
Iztok Zun
Keyword(s):  
Thermal Conductivity ◽  
District Heating ◽  
Soil Thermal Conductivity

The Primary and Secondary Analysis of Uncertain Factors in Soil Thermal Properties for GSHP

2012 ◽  
Vol 614-615 ◽  
pp. 688-694 ◽  
Author(s):  
Yi Wang ◽  
Guo Min Shen
Keyword(s):  
Thermal Conductivity ◽  
Thermal Properties ◽  
Water Table ◽  
Unsaturated Soil ◽  
Solid Phase ◽  
Saturated Soil ◽  
Soil Thermal Conductivity ◽  
Saturation Degree ◽  
Soil Thermal Properties ◽  
Soil Solid Phase

In this paper, at first, an effective soil thermal conductivity model was established. Single factor regression analysis for 6 uncertain factors contained in the model was then conducted respectively. Finally, the primary and secondary characters of these uncertain factors were analyzed by using the orthogonal test. The analysis results show that the effective soil thermal conductivity has linear relationships with the saturation degree of unsaturated soil and the depth of water table and has power function relationships with other 4 uncertain factors; the porosity of unsaturated soil has the greatest effect on the effective soil thermal properties, followed by saturation degree of unsaturated soil, porosity of saturated soil, solid phase thermal conductivity of unsaturated soil, solid phase thermal conductivity of saturated soil and the depth of water table.

scholarly journals The Influence of Burial Depth and Soil Thermal Conductivity on Heat Transfer in Buried CO2 Pipelines for CCS: A Parametric Study

2020 ◽  
Author(s):  
Babafemi Olugunwa ◽  
Julia Race ◽  
Tahsin Tezdogan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Steady State ◽  
Thermal Resistance ◽  
Parametric Study ◽  
Flow Assurance ◽  
Burial Depth ◽  
Soil Thermal Conductivity ◽  
Dense Phase ◽  
Pipeline Transportation

Abstract Pipeline heat transfer modelling of buried pipelines is integral to the design and operation of onshore pipelines to aid the reduction of flow assurance challenges such as carbon dioxide (CO2) gas hydrate formation during pipeline transportation of dense phase CO2 in carbon capture and storage (CCS) applications. In CO2 pipelines for CCS, there are still challenges and gaps in knowledge in the pipeline transportation of supercritical CO2 due to its unique thermophysical properties as a single, dense phase liquid above its critical point. Although the design and operation of pipelines for bulk fluid transport is well established, the design stage is incomplete without the heat transfer calculations as part of the steady state hydraulic and flow assurance design stages. This paper investigates the steady state heat transfer in a buried onshore dense phase CO2 pipelines analytically using the conduction shape factor and thermal resistance method to evaluate for the heat loss from an uninsulated pipeline. A parametric study that critically analyses the effect of variation in pipeline burial depth and soil thermal conductivity on the heat transfer rate, soil thermal resistance and the overall heat transfer coefficient (OHTC) is investigated. This is done using a one-dimensional heat conduction model at constant temperature of the dense phase CO2 fluid. The results presented show that the influence of soil thermal conductivity and pipeline burial depth on the rate of heat transfer, soil thermal resistance and OHTC is dependent on the average constant ambient temperature in buried dense phase CO2 onshore pipelines. Modelling results show that there are significant effects of the ambient natural convection on the soil temperature distribution which creates a thermal influence region in the soil along the pipeline that cannot be ignored in the steady state modelling and as such should be modelled as a conjugate heat transfer problem during pipeline design.

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