Effective Thermal Conductivity and Borehole Thermal Resistance in Selected Borehole Heat Exchangers for the Same Geology
Bibliographic record
Abstract
Investigating the constructions of borehole heat exchangers with high efficiency (unit heat transfer between the heat carrier and ground) is important. One of the means to improve efficiency is the use of the most efficient construction of the borehole heat exchanger. The paper describes research on borehole heat exchangers’ thermal efficiency, which is mainly characterized by parameters obtained from a thermal response test: effective thermal conductivity and borehole thermal resistivity. The borehole heat exchangers of the Laboratory of Geoenergetics in Poland were studied. Based on thermal response test interpretation and empirical equations, one of which is proprietary, the heat transfer is calculated independent of the duration of the thermal response test. Other conditions for using borehole heat exchangers in downtowns are discussed. The research aims to determine the best borehole heat exchanger design from five basic possibilities studied. A lack of unequivocal statements regarding this matter in the literature was observed. The influence of the interpretation method on the research results is determined. A single U-tube system filled with gravel is shown to be the most advantageous design by a very small margin. The applied interpretation methods, however, confirm the hitherto ambiguity in the selection of the best construction. The maximum heat carrier temperature at the end of thermal response tests was 32 °C for a geological profile mostly made up of clay (low thermal conductivity) and 23 °C for Carpathian flysch (sandstones and shales, with a higher value of conductivity).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".