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The relative importance of moisture transfer, soil freezing and snow cover on ground temperature predictions

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  • Xu, Huining
  • Spitler, Jeffrey D.

Abstract

Predicting ground temperature is an important part of the analysis of geothermal resources assessment and use. Thus, we develop and validate one-dimensional numerical model for heat and mass transfer in partially frozen soils. The model is implemented in HVACSIM Plus and used to simulate the thermal regime of soil profile. In addition to modeling heat conduction, model variations also includes moisture transfer, snow accumulation and melting, and soil freezing and thawing. The results are compared against experimental measurements of ground temperature for three locations in Montana, USA. The differences between simulated depth temperature with and without snow cover and freezing and thawing of soil reveal that ground temperatures are predominantly influenced by these two factors. Considering moisture transfer slightly improves temperature predictions, although it increases computational time by one order of magnitude. To balance computational efficiency with prediction accuracy, we propose an equivalent moisture content of 40–60% saturation in predicting ground temperature.

Suggested Citation

  • Xu, Huining & Spitler, Jeffrey D., 2014. "The relative importance of moisture transfer, soil freezing and snow cover on ground temperature predictions," Renewable Energy, Elsevier, vol. 72(C), pages 1-11.
    • Handle: RePEc:eee:renene:v:72:y:2014:i:c:p:1-11
    DOI: 10.1016/j.renene.2014.06.044
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    References listed on IDEAS

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    1. Jaakko Putkonen, 2003. "Determination of frozen soil thermal properties by heated needle probe," Permafrost and Periglacial Processes, John Wiley & Sons, vol. 14(4), pages 343-347, October.
    2. Zarrella, Angelo & De Carli, Michele, 2013. "Heat transfer analysis of short helical borehole heat exchangers," Applied Energy, Elsevier, vol. 102(C), pages 1477-1491.
    3. Kim, Jiyoung & Jang, Jea Chul & Kang, Eun Chul & Chang, Ki Chang & Lee, Euy Joon & Kim, Yongchan, 2013. "Verification study of a GSHP system Manufacturer data based modeling," Renewable Energy, Elsevier, vol. 54(C), pages 55-62.
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    Citations

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    Cited by:

    1. Shi, Hao & Xu, Huining & Tan, Yiqiu & Li, Qiang & Yi, Wei, 2022. "Multi-objective optimization of operation strategy in snow melting system for airfield runway using genetic algorithm: A case study in Beijing Daxing International Airport," Renewable Energy, Elsevier, vol. 201(P2), pages 100-116.
    2. Xiong, Zeyu & Fisher, Daniel E. & Spitler, Jeffrey D., 2015. "Development and validation of a Slinky™ ground heat exchanger model," Applied Energy, Elsevier, vol. 141(C), pages 57-69.
    3. Xu, Huining & Shi, Hao & Tan, Yiqiu & Ye, Qing & Liu, Xiujie, 2022. "Modeling and assessment of operation economic benefits for hydronic snow melting pavement system," Applied Energy, Elsevier, vol. 326(C).
    4. Fanxiang Meng & Renjie Hou & Tianxiao Li & Qiang Fu, 2020. "Variability of Soil Water Heat and Energy Transfer Under Different Cover Conditions in a Seasonally Frozen Soil Area," Sustainability, MDPI, vol. 12(5), pages 1-14, February.
    5. Naylor, Shawn & Ellett, Kevin M. & Gustin, Andrew R., 2015. "Spatiotemporal variability of ground thermal properties in glacial sediments and implications for horizontal ground heat exchanger design," Renewable Energy, Elsevier, vol. 81(C), pages 21-30.
    6. Bertermann, D. & Klug, H. & Morper-Busch, L., 2015. "A pan-European planning basis for estimating the very shallow geothermal energy potentials," Renewable Energy, Elsevier, vol. 75(C), pages 335-347.

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