Performance Assessment of Horizontal Ground Heat Exchangers under a Greenhouse in Quebec, Canada
Bibliographic record
Abstract
Among the various approaches to agriculture, urban greenhouse farming has gained attention for its ability to address food security and disruptions to global food supply chains. However, the increasing impact of climate change and global warming necessitates sustainable methods for heating and cooling these greenhouses. In this study, we focused on the potential of slinky-coil horizontal ground heat exchangers (HGHEs) to meet the energy demands of urban greenhouses, assuming they are installed beneath the greenhouse to optimize space utilization. Climate data, an energy consumption profile for a greenhouse being designed in La Pocatière (Québec, Canada) and in-situ ground thermal properties assessments were used to build numerical models using FEFLOW and to evaluate the performance of the HGHEs simulated. Four scenarios were simulated and compared to a base case, considering the greenhouse’s maintenance of a constant temperature above an HGHE limited to the greenhouse’s dimensions. Our findings reveal that a minimum of 7.1% and 26.5% of the total heating and cooling loads of a small greenhouse (133 m2 area) can be covered by HGHEs installed at a 1.5 m depth when there is no greenhouse above. When installed under a greenhouse with a constant inside temperature of 21 °C, the coverage for heating loads increases to 22.8%, while cooling loads decrease to 24.2%. Sensitivity analysis demonstrates that the constant temperature in the greenhouse reduces the system’s reliance on surface temperature fluctuations for both heating and cooling, albeit with reduced efficiency for cooling.
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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".