The First Italian Experience of Ground Thermal Energy Storage: an Integrated Approach for Design and Monitoring, from Laboratory to Field Scale
Bibliographic record
Abstract
The ground thermal energy storage (GTES) is a useful application able to provide the H&C and DHW demand of commercial or residential buildings. Several examples in Canada and Northern Europe demonstrated the reliability and convenience of these systems in terms of both energy and economic savings, even though a remarkable initial investment is required. Owing to these conspicuous costs, an accurate preliminary study should be undertaken in order to correctly design the plant and achieve good efficiency of the system. Moreover, when the plant is operative, the monitoring of the thermal plume induced in the undisturbed ground should be a priority. The surrounding litho, hydro and biosphere are indeed influenced by the plant’s activity and a trustworthy supervision of the temperature field is advisable both for the environmental safety and for controlling the system’s efficiency. For these purposes, an integrated approach for design and monitoring GTES systems was tested first at laboratory scale and then applied to a field scale living lab, located nearby Torino (Northern Italy). The proposed methodology consists in lab analogical modeling of the heat propagation, geophysical measurements exploiting the existing relationship between temperature and electrical resistivity and numerical simulations of the studied phenomena with an open-source software (OpenGeoSys). The joint effort of temperature monitoring and numerical simulation at both lab and site scale, combined with direct measurements of the thermal properties, can be a useful tool for highlighting the best design solution for a GTES system. Moreover electrical resistivity surveys, calibrated at lab scale and then conducted at field scale, can be very useful in imaging the Thermal Affected Zone generated by the plant. The adopted approach showed a good potential towards reliable design and accurate monitoring activity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".