Estimation of In-Situ Heat Capacity and Thermal Diffusivity from Undisturbed Ground Temperature Profile Measured in Ground Heat Exchangers.
Bibliographic record
Abstract
Undisturbed ground temperature (UGT), thermal conductivity (TC) and heat capacity (HC) are essential parameters for the design of borehole heat exchanger (BHE) and borehole thermal energy storage systems. However, field methods to assess the thermal state and properties of the sub-surface are costly and time consuming. Moreover, HC is often not evaluated but arbitrarily selected from literature considering the geological materials intercepted by boreholes. Therefore, this work aims at proposing a field heat tracing method to infer the thermal diffusivity (TD) and HC with assumption of natural transient heat conduction in the subsurface. Empirical equations were developed to reproduce a UGT profile measured along a BHE. Experimental coefficients are found with a non-linear least square solver optimization and used to calculate the damping depth and TD. Subsequently, the TD is used to evaluate HC considering TC obtained from a thermal response test (TRT). Results from this proposed heat tracing method were verified and validated against a set of TRT results and oscillatory TRT analysis using a field dual probe concept to infer HC. The example here described highlights the advantages and novelty of this fast and simple field method relying only on a single UGT profile measured before a TRT.
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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 | 0.001 |
| 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".