Evaluation of effective thermal conductivity of unsaturated granular materials using random network model
- Authors
- Lee, Chulho; Zhuang, Li; Lee, Dongseop; Lee, Seokjae; Lee, In-Mo; Choi, Hangseok
- Issue Date
- 5월-2017
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Unsaturated condition; Granular material; Effective thermal conductivity; DEM; Network model
- Citation
- GEOTHERMICS, v.67, pp.76 - 85
- Indexed
- SCIE
SCOPUS
- Journal Title
- GEOTHERMICS
- Volume
- 67
- Start Page
- 76
- End Page
- 85
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/83544
- DOI
- 10.1016/j.geothermics.2017.01.007
- ISSN
- 0375-6505
- Abstract
- The effective thermal conductivity of granular materials is widely used in numerous geothermal engineering applications, such as the ground source heat pump (GSHP) system. However, for unsaturated granular materials, it is difficult to predict the thermal conductivity because of the interaction between solid and fluid in media. In this study, the effective thermal conductivity of unsaturated granular materials was measured, reviewed and analysed using a macroscopic pore structure network Model with a randomly packed particles. The network model was verified by measured data (soil water characteristics curve, thermal conductivity and etc.) of three different glass beads and also Jumunjin sand (standard sand of South Korea). Upon the series of laboratory experiments, some modification to the existing network model were introduced, such as the use of soil water characteristic curve (SWCC) applied to modelling the thermal conductivity of granular materials. In addition, an empirical correlation between the fraction of the mean radius (chi) and the thermal conductivity at a given saturated condition was developed through comparison with the test results. In the range of lower degree of saturation (5%-20%), the modified network model shows relatively higher thermal conductivity than the laboratory measurements. However, for the higher degree of saturation (>40%), it shows a similar tendency to the laboratory measurements. (C) 2017 Elsevier Ltd. All rights reserved.
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Collections - College of Engineering > School of Civil, Environmental and Architectural Engineering > 1. Journal Articles
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