Time-Lapse 3D Electric Tomography for Short-time Monitoring of an Experimental Heat Storage System
Bibliographic record
Abstract
A borehole thermal energy storage living lab was built nearby Torino (Northern Italy). The aim of this living lab is to test the ability of the alluvial deposits of the north-western Po Plain to store the thermal energy collected by solar panels. Monitoring the temperature distribution induced in the underground and the effectiveness of the heat storage in this climatic context is not an easy task. For this purpose, different temperature evolution strategies are compared in this paper: Local temperature measurements, numerical simulations and geophysical surveys. These different approaches were compared during a single day of operation of the living lab. The results of this comparison allowed to underline the effectiveness of time-lapse 3D electric resistivity tomography as a non-invasive and cost-effective qualitative heat monitoring tool. This was obtained even in a test site with unfavorable thermo-hydrogeological conditions and high-level anthropic noise. Moreover, the present study demonstrated that, if properly calibrated with local temperature values, time-lapse 3D electric resistivity tomography also provides a quantitative estimation of the underground temperature.
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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 | 0.000 | 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) | 0.001 | 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".