Application of Borehole Thermal Energy Storage in Waste Heat Recovery from Diesel Generators in Remote Cold Climate Locations
Bibliographic record
Abstract
Remote communities that have limited or no access to the power grid commonly employ diesel generators for communal electricity provision. Nearly 65% of the overall thermal energy input of diesel generators is wasted through exhaust and other mechanical components such as water-jackets, intercoolers, aftercoolers, and friction. If recovered, this waste heat could help address the energy demands of such communities. A viable solution would be to recover this heat and use it for direct heating applications, as conversion to mechanical power comes with significant efficiency losses. Despite a few examples of waste heat recovery from water-jackets during winter, this valuable thermal energy is often discarded into the atmosphere during the summer season. However, seasonal thermal energy storage techniques can mitigate this issue with reliable performance. Storing the recovered heat from diesel generators during low heat demand periods and reusing it when the demand peaks can be a promising alternative. At this point, seasonal thermal storage in shallow geothermal reserves can be an economically feasible method. This paper proposes the novel concept of coupling the heat recovery unit of diesel generators to a borehole seasonal thermal storage system to store discarded heat during summer and provide upgraded heat when required during the winter season on a cold, remote Canadian community. The performance of the proposed ground-coupled thermal storage system is investigated by developing a Computational Fluid Dynamics and Heat Transfer model.
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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 | 0.001 |
| 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".