Prediction of soil temperatures for shallow geothermal applications in Turkey

Yener, Deniz; Özgener, Önder; Özgener, Leyla

doi:10.1016/j.rser.2016.11.065

Cited by 31 publications

(11 citation statements)

References 53 publications

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“…contained in large cylindrical container with thermal insulation and covered with round glass. Measurements on these samples were also conducted in other regions in Turkey (Yener et al, 2017). Yener et al (2017) In Rampur District, Nepal, Poudel et al (2012) observed a maximum soil temperature of 31 °C measured at a depth of 10 cm.…”

Section: Accepted Manuscriptmentioning

confidence: 98%

“…Measurements on these samples were also conducted in other regions in Turkey (Yener et al, 2017). Yener et al (2017) In Rampur District, Nepal, Poudel et al (2012) observed a maximum soil temperature of 31 °C measured at a depth of 10 cm. The authors observed an increase in soil temperature in winter and a decrease at depths lower than 10 cm in summer season, concluding that solar radiation has a large influence over ground upper layers, while geothermal energy increased the soil temperature at larger depths in the winter season.…”

Section: Accepted Manuscriptmentioning

confidence: 98%

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Predicting the thermal behaviour of sands considering its moisture content and grain size with applications to geothermal heat pump installations

Rodríguez

Morillón-Gálvez

Aldama-Ávalos

et al. 2019

Energy and Buildings

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This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Highlights  An experimental thermal study of five different types of sands has been conducted  Fine-grained sands attain higher maximum temperature than coarse-grained sands  Sub-angular and rounded grains with 0-25% moisture could enhance GHPS performance  Derivation of a sand temperature model considering grain size, shape and moisture content  Potential implementation of the derived model in building simulation tools is discussed

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Section: Accepted Manuscriptmentioning

confidence: 98%

Section: Accepted Manuscriptmentioning

confidence: 98%

Predicting the thermal behaviour of sands considering its moisture content and grain size with applications to geothermal heat pump installations

Rodríguez

Morillón-Gálvez

Aldama-Ávalos

et al. 2019

Energy and Buildings

View full text Add to dashboard Cite

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“…Furthermore, the residual effects of dissimilar management on the temporal variability and covariance structure of the soil temperature was reported by Awe et al (2015) [11], and An et al (2016) [12] used the amplitude, phase-shift, conduction-convection, and harmonic methods to estimate the thermal diffusivity under different climatic conditions in the subsurface layers. Yener et al (2017) investigated the soil temperatures at different depths in several regions of Turkey. They used a sinusoidal prediction model for the soil temperatures based on the depth and time to describe the annual soil temperature variations in different regions of Turkey [13].…”

Section: Introductionmentioning

confidence: 99%

“…Yener et al (2017) investigated the soil temperatures at different depths in several regions of Turkey. They used a sinusoidal prediction model for the soil temperatures based on the depth and time to describe the annual soil temperature variations in different regions of Turkey [13].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Thermal Diffusivity for Greenhouse Soil Temperature Simulation

2020

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In greenhouse energy balance models, the soil thermal parameters are important for evaluating the heat transfer between the greenhouse air and the soil. In this study, the soil thermal diffusivity was estimated from greenhouse soil temperature data using the amplitude, phase-shift, arctangent, logarithmic, and min-max methods. The results showed that the amplitude method and the min-max method performed well in estimating the soil thermal diffusivity. The obtained soil thermal diffusivity was input into a sinusoidal model to determine the greenhouse soil temperature at different soil depths. For greenhouse applications, the daily average soil temperature at different depths was predicted according to the temperature at the surface and the annual mean soil temperature. The model was validated using soil temperature data from summer and winter, when the greenhouse was cooled and heated, respectively.

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“…Numerous studies are under way to predict ground temperature in various ways to utilize geothermal heat. Yener et al [6] developed a model that uses a sine function with the amplitude of annual and daily average outdoor temperature and the amplitude of underground depths, and they predicted ground temperature in Turkey. Furthermore, they suggested a correlation among the ground temperature amplitudes by depth, the constant value between amplitude and annual average outdoor temperature, and the daily outdoor temperature amplitude.…”

Section: Introductionmentioning

confidence: 99%

Development of a Simplified Regression Equation for Predicting Underground Temperature Distributions in Korea

Cho

Ihm

2018

Energies

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The Korea Meteorological Administration (KMA) measures outdoor temperature and ground surface temperature at 95 observation points, but monthly ground temperatures by depth, which are important for using geothermal heat, are only provided for nine points. Since the ground temperature is known in the vicinity of only nine observation points, it is very difficult to predict underground temperature in the field. This study develops a simplified regression equation for predicting underground temperature distributions, compares the prediction results with the experimental data of Korea’s representative areas and the data measured in this study, and examines the validity of the developed regression equation. The regression equation for predicting temperature amplitudes at ground depths of 1.0, 3.0, and 5.0 m was derived using the amplitude ratio of outdoor temperature and surface temperature provided by KMA at nine points in Korea from 2006 to 2015. The coefficient of determination was as high as 0.93 (95% confidence level). In addition, the field-measured ground temperature distribution at a depth of 3 m was in good agreement with the predicted ground temperature distribution in Changwon districts for the whole of 2017.

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Prediction of soil temperatures for shallow geothermal applications in Turkey

Cited by 31 publications

References 53 publications

Predicting the thermal behaviour of sands considering its moisture content and grain size with applications to geothermal heat pump installations

Predicting the thermal behaviour of sands considering its moisture content and grain size with applications to geothermal heat pump installations

Estimation of Thermal Diffusivity for Greenhouse Soil Temperature Simulation

Development of a Simplified Regression Equation for Predicting Underground Temperature Distributions in Korea

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