Experimental Characterization of a Low-Temperature Borehole Thermal Energy Storage System
Bibliographic record
Abstract
Abstract The effectiveness of borehole thermal storage and the performance of ground source heat pump systems (GSHP) are highly dependent on the soil lithology. In this study, the operation and thermal energy storage potential of two 150 m deep borehole heat exchangers at a test site in Calgary, Canada, is experimentally investigated. The boreholes, with distinct soil lithologies, groundwater flow and thermal properties, were analyzed to assess their influence on solar thermal storage and GSHP performance on the site. A solar collector array of 4.04 m2 per 150 m borehole with a tilt angle of 45° to the south was used. Results reveal that solar thermal recharging augmented the ground temperature, with solar loop outlet temperatures consistently exceeding the undisturbed ground temperature and increasing with the amount of energy injected. The maximum solar loop outlet temperature, recorded in July, was 1.7°C to 2.6°C above the starting month outlet temperature. Results also show that, despite the reduced solar input in November, the previously stored energy enabled the heat pump to operate at higher average temperatures than the undisturbed ground temperature. Ongoing measurements will further quantify the heat pump’s performance improvements and storage efficiency, providing valuable insights into integrating solar thermal storage with GSHP systems for sustainable building energy solutions in cold climates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".