Abstract

Ground source heat pumps (GSHPs) have been widely applied worldwide in recent years because of their high efficiency and environmental friendliness. An accurate estimation of the thermal conductivity of rock and soil layers is important in the design of GSHP systems. The distributed thermal response test (DTRT) method incorporates the standard test with a pair of fiber optic-distributed temperature sensors in the U-tube to accurately calculate the layered thermal conductivity of the rock/soil. In this work, in situ layered thermal conductivity was initially obtained by DTRT for four boreholes in the study region. A series of laboratory tests was also conducted on the rock samples obtained from drilling. Then, an artificial neural network (ANN) model was developed to predict the layered thermal conductivity on the basis of the DTRT results. The primary modeling factors were water content, density, and porosity. The results showed that the ANN models can predict the layered thermal conductivity with an absolute error of less than 0.1 W/(m·K). Finally, the trained ANN models were used to predict the layered thermal conductivity for another study region, in which only the effective thermal conductivity was measured with the thermal response test (TRT). To verify the accuracy of the prediction, the product of pipe depth and layered thermal conductivity was suggested to represent heat transfer capacity. The results showed that the discrepancies between the TRT and ANN models were 5.43% and 6.37% for two boreholes, respectively. The results prove that the proposed method can be used to determine layered thermal conductivity.

Highlights

  • Increasing energy consumption, the burning of fossil fuels, has resulted in global air pollution and environmental degradation, and geothermal sources have attracted increasingly more attention as a renewable resource [1,2,3]

  • The results showed that the thermal conductivity varies with the layer conditions, and the conditions, and the measured layered thermal conductivity by distributed thermal response test (DTRT) is greater than that by the measured layered thermal conductivity by DTRT is greater than that by the laboratory

  • All inputs and outputs are normalized to the interval (0, 1) to ensure that no special factor is dominant over the others

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Summary

Introduction

Increasing energy consumption, the burning of fossil fuels, has resulted in global air pollution and environmental degradation, and geothermal sources have attracted increasingly more attention as a renewable resource [1,2,3]. Laboratory experiments test the thermal parameters of rock and soil samples collected at the test soil samples collected at the test site using a steady- or non-steady-state heat flow method. The TRT method for GHE was first parameters cannot be directly applied to the GSHP design. Standard constant records inletfluid and outlet fluid temperature variations during the test obtains comprehensive in situ borehole thermal parameters by analyzing the temperature data. The standard TRT obtains comprehensive in situ borehole thermal parameters by analyzing based the on temperature the line heatdata source model [17].line. It is widely used in the actual based on the heat source model [17]. The theschematic fluid fromdiagram the surface to theisunderground in real time

A mathematical model for the of layered in Figure
Formation Characteristic of the Test Area
Comprehensive
Project Overview of CY01 Study Region
Schematic
Temperature
Artificial Neural Network
Modeling
Results of ANN Models of Layered Thermal Conductivity
10. Results
Project of test
Project Application
Conclusions
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