Prediction of undisturbed ground temperature using analytical and numerical modeling. Part II: Methodology for developing a world-wide dataset

Lu Xing*, Jeffrey D. Spitler

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Analyses of building heating and cooling load calculations and design of ground heat exchangers often require the undisturbed ground temperatures as inputs. In a companion article (Xing and Spitler 2017), a two-harmonic analytical model which is used for the estimations of undisturbed ground temperatures for engineering applications has been developed. This model relies on a second-order harmonic relationship and five weather-related constants—annual average ground temperature, two temperature amplitudes, and two phase lags to predict the ground temperatures. These parameters are estimated using temperature results calculated from the numerical method developed by Xing and Spitler (2017). The two-harmonic model is validated using measured ground temperature data at 19 sites in the United States; these sites are located in three different climates—arid climates, warm climates, and snow climates. The model is convenient and provides with good accuracy. It relies on inputs such as soil diffusivity, vegetation density, and snow depth to estimate the ground temperatures; these inputs vary from site to site or vary with time. In order to generate typical year ground temperatures for thousands of sites over a worldwide range, the method described in Xing and Spitler (2017) needs some automated procedures to estimate these inputs for each site. These procedures are developed and described in this article. The two-harmonic model estimated typical year ground temperatures was compared to the experimental results at the 19 sites in the United States to validate the automated procedures. The validated procedures and model are applied for estimating typical year ground temperatures over a worldwide range for engineering application (Xing et al. 2017).

Original languageEnglish
Pages (from-to)809-825
Number of pages17
JournalScience and Technology for the Built Environment
Volume23
Issue number5
Early online date31 Jan 2017
DOIs
Publication statusPublished - 4 Jul 2017
Externally publishedYes

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