3.9 Article

Estimating apparent thermal diffusivity of soil using field temperature time series

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/17486025.2015.1006266

关键词

soil thermal properties; thermal diffusivity; temperature time series; heat conduction model; numerical method

资金

  1. Australian Research Council
  2. ARC project [LP 100200441]
  3. City West Water Limited
  4. Jemena
  5. Envestra Limited
  6. Water Corporation
  7. Ipswich Water
  8. South East Water Limited
  9. Queen's University (Canada)

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Reliable estimates of soil thermal properties such as heat capacity, thermal conductivity, and diffusivity are important in analysis of heat transmission through soils in applications such as shallow geothermal applications, buried electrical conduits, and in general heat/fluid flow analyses. A number of analytical, numerical and experimental methods are available to determine the soil thermal properties. In this paper, the analytical and numerical methods developed on the basis of one-dimensional heat conduction equation are used to estimate the apparent thermal diffusivity of soil. Three of the four analytical methods, Amplitude, Phase, and Arctangent provide explicit equations for the apparent thermal diffusivity. Two methods, Harmonic and Numerical, make use of large number of temperature measurements to implicitly solve for the apparent thermal diffusivity. The temperature time series data monitored at different depths in two field sites in Melbourne, Australia for more than 2 year period were used to estimate the apparent thermal diffusivity of soil down to 2 m depth. The apparent thermal diffusivity was calculated using all five methods and compared with laboratory experimental results. The effectiveness of each method in predicting the thermal diffusivity was compared and observed discrepancies were discussed. Finally, the observed soil temperature data for a 12 month period are used to model the temperature variation in the ground analytically using Harmonic method and the model prediction for the following 12 month was compared independently with the field measurements. The analytical model prediction is found to be in good agreement with the field monitored data.

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