Thermal response test for shallow geothermal applications: a probabilistic analysis approach

Tinti, Francesco; Rossion, Bruno; Focaccia, Sara

doi:10.1186/s40517-015-0025-5

Cited by 7 publications

(4 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thermal properties of GHE are generally determined by interpreting the recorded data synthesis based on different models (Tinti et al 2015). In the present work, heat transfer rate of the energy piles is determined by the recorded parameters such as outlet-inlet fluid temperature and fluid flow rate.…”

Section: Analysis Of Thermal Exchange Ratesmentioning

confidence: 99%

Comparison of ground temperature response of energy pile and borehole heat exchanger during thermal response tests

et al. 2016

View full text Add to dashboard Cite

Thermal migration of ground heat exchanger (GHE) in subsurface is crucially important to the efficiency and sustainability of ground source heat pump systems. In order to investigate heat transfer efficiency of GHE, ground temperature response during system operation should be analyzed. In this paper, two types of GHEs operate under heating operating condition are simulated by thermal response test. A set of parameters including fluid temperature, borehole wall and ground temperature are monitored with duration of 148 h. The analysis of thermal performance shows that the energy pile has specific thermal rates of 147 W/m which is 230% higher than that of borehole heat exchanger with 56 W/m. Furthermore, heat flux per unit area of the contacting area at borehole wall (q, W/m 2 ) is analyzed. The monitored temperature development at the borehole wall for both types of GHEs can be perfectly explained by q. The finding of this study indicates that the parameter is useful in estimating ground thermal accumulation of GHEs. The larger the q is, the higher the possible of ground thermal accumulation and unstable performance of GHEs would be.

show abstract

Section: Analysis Of Thermal Exchange Ratesmentioning

confidence: 99%

Comparison of ground temperature response of energy pile and borehole heat exchanger during thermal response tests

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Table 2 summarizes the main characteristics of the TRT experiments included in our present analysis. The duration of the tests performed is variable, ranging from 9 to 31 days, and, nevertheless, longer than the typical 72 h used by commercial TRTs mobile devices, in compliance with the recommendations included in the current standards, such as the IEA-ECES Annex 21 Final Report, see [62]. To prepare data for comparison with models, the dataset is divided into two parts, before and after the start of heat injection.…”

Section: Heat Injection Fluctuation Control Scheme and Description Ofmentioning

confidence: 99%

How Reliable Are Standard Thermal Response Tests? An Assessment Based on Long-Term Thermal Response Tests Under Different Operational Conditions

et al. 2018

View full text Add to dashboard Cite

In this contribution, we analyze the results of a number of thermal response test (TRT) experiments performed during several years at the same location at our university campus in Valencia (Spain), a permeable saturated soil area with possible groundwater flow conditions. A combination of different heat injection rates, TRT operation times of up to 32 days, and various methods for parameter estimation of ground thermal properties have been applied to study their influence on the result and accuracy of TRTs. Our main objective has been to experimentally quantify the influence of groundwater flow heat advection using moving infinite and finite line-source theories, as well as to analyze the influence of factors such as test duration, sensor accuracy, and external thermal influences. We have shown that the traditionally used infinite and finite line-source models, as well as the moving line-source models, can accurately represent experimental temperature evolution, but that there are many caveats regarding the significance parameters extracted and its reproducibility and stability. These features can be improved if data from the first test days are disregarded for the analysis, obtaining a much faster convergence to the definitive soil parameter estimates, including the effective Péclet number that represents groundwater flow in our particular case.

show abstract

“…Using the intercept, a similar procedure allows calculation of the mutually dependent ground volumetric heat capacity c g and borehole thermal resistance R b (Marcotte and Pasquier 2008). The authors recently introduced geostatistical analysis of TRT data starting from the ILS theory (Bruno et al 2011(Bruno et al , 2013Focaccia et al 2013;Tinti et al 2015). They pointed out the limits of ILS basic assumptions, which do not consider: the vectorial nature of the regionalized variable "equivalent thermal conductivity", the meaning of "equivalent thermal conductivity", the continuous change of support during the test period.…”

Section: Thermal Response Test Data Analysis: Introductionmentioning

confidence: 99%

Estimating Thermal Response Test Coefficients: Choosing Coordinate Space of The Random Function

2015

Self Cite

View full text Add to dashboard Cite

In shallow geothermal systems, the main equivalent underground thermal properties are commonly calculated with a thermal response test (TRT). This is a borehole heat exchanger production test where the temperature of a heat transfer fluid is recorded over time at constant power heat injection/extraction. The equivalent thermal parameters (thermal conductivity, heat capacity) are simply deduced from temperature data regression analysis that theoretically is a logarithmic function in the time domain, or else a linear function in the log-time domain. By interpreting the recorded temperatures as a regionalized variable whose drift is the regression function, in both cases the formal problem is a linear estimation of the mean. If the autocorrelation function (variogram, covariance) of residuals is known, coefficient variance can be directly deduced. Coefficient estimates are independent of the drift form adopted, and the residuals are the same in the same points. The random function is different in the time domain, however, and in the log-time domain. In fact, residual The work was presented to GeoEnv 2014 Conference on Geostatistics for Environmental Applications, held in Paris, 9-11/07/2014.

show abstract

Thermal response test for shallow geothermal applications: a probabilistic analysis approach

Cited by 7 publications

References 27 publications

Comparison of ground temperature response of energy pile and borehole heat exchanger during thermal response tests

Comparison of ground temperature response of energy pile and borehole heat exchanger during thermal response tests

How Reliable Are Standard Thermal Response Tests? An Assessment Based on Long-Term Thermal Response Tests Under Different Operational Conditions

Estimating Thermal Response Test Coefficients: Choosing Coordinate Space of The Random Function

Contact Info

Product

Resources

About