Reference data set for injection and extraction cycle of a borehole thermal energy storage field: A numerical and experimental study
Bibliographic record
Abstract
Borehole thermal energy storage systems are utilized across the globe to capture solar or residual thermal energy and store the heat seasonally. Although many borehole thermal energy storage facilities exist and operate, there are few facilities that are equipped to provide data and be used for research purposes. This paper provides an extensive experimental dataset of the operation of a borehole thermal energy storage field. The operating conditions include a constant temperature heat injection cycle followed by a hold period and a stepped-constant temperature heat extraction cycle. The experiment was initiated on November 23, 2021, and concluded on January 18, 2023. It involved a total of 340 GJ of heat injection and 192 GJ of heat extracted. Measurements of soil temperature and fluid temperature are shown, along with mass flow rates and the calculated thermal power. A COMSOL Multiphysics model with simplifying assumptions was used to demonstrate the modelling capability of the code. The results show that the COMSOL model of the borehole field was able to capture the thermal response of heat injection and extraction cycles to within 4.5 % of the experimental results. • Experimental dataset of operational borehole thermal energy storage facility • Radial and axial soil temperatures, fluid temperature, and flow rate measurements • Validation of a simplified 3D numerical model • Thermal power comparison of experimental and numerical results
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".