Numerical Evaluation of the Benefits Provided by the Ground Thermal Inertia to Urban Greenhouses
Bibliographic record
Abstract
Communities operating urban greenhouses need affordable solutions to reduce their heating consumption. The objective of this study was to compare the ability of different simple ground-based solutions to reduce the heating energy consumption of relatively small urban greenhouses operated all year round in a cold climate. An urban greenhouse located in Montreal (Canada) and its thermal interactions with the ground were modeled with the TRNSYS 18 software. The following greenhouse scenarios were simulated: partially insulating the walls, partially burying the greenhouse below the ground level, reducing the inside setpoint temperature, and using an air–soil heat exchanger (ASHE) or a ground-coupled heat pump (GCHP). The heat exchangers for the last two cases were assumed to be located underneath the greenhouse to minimize footprint. The results showed that reducing the setpoint temperature by 10 °C and burying the greenhouse 2 m below the surface has the most impact on fuel consumption (−33% to −53%), while geothermal systems with a limited footprint (ASHE and GCHP) can reduce the fuel consumption by 21–35% and 18–27%, respectively, depending on the soil thermal conductivity and ground heat injection during summer. The scenarios do not provide the same benefits and have different implications on solar radiation availability, growth temperature, electrical consumption, and operation that must be considered when selecting a proper solution.
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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 | 0.001 | 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 | 0.001 | 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".