Design and Simulation of a Portable Apparatus for in-situ Thermal Response Test (TRT)
Bibliographic record
Abstract
Energy consumption for air conditioning structures is quite significant, particularly in hot (or cold) dominated climates.Ground source heat pumps (GSHP) represent a clean technology that relies on stable shallow geothermal energy for air conditioning.Geothermal energy is renewable and reliable with no carbon emissions.A full analysis of the ground thermal characteristics of the targeted site is required to assess the feasibility of the GSHP system.The study focuses on modeling and constructing a portable, smallscale thermal response test that can be used to obtain in-situ ground data, essential for the GSHP system design.The parameters extracted will be obtained through numerical simulations and verified experimentally.The parameters obtained from the numerical simulations (namely the undisturbed ground temperature, ground thermal conductivity, and borehole thermal resistivity) are to be verified experimentally in a later study.The experimentation, which involved simulating the use of the TRT device for seven days, showed that a greater flow rate led to a higher mean fluid temperature and that lower flow rates resulted in a greater temperature difference between the outlet and inlet.However, the actual values of the soil parameters are yet to be measured experimentally using this TRT device.Instead, they were adapted from literature and used in the simulations.The obtained results provide a robust foundation for running the experiment once the TRT device is connected to a Borehole Heat Exchanger (BHE).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".