Comparative Analysis of Occupant Thermal Comfort, Energy Consumption, and CO<sub>2</sub> Emissions for an Educational Building in Cold Climate: A Case Study in Canada
Bibliographic record
Abstract
Abstract Global climate change and global warming capture the attention of planners seeking more sustainable buildings to reduce dependence on fossil fuels and minimize energy consumption. Consequently, architects have developed buildings over the years and applied more sustainable strategies to cope with the environment, either in the shape of the building, the design of openings, or the use of more sustainable materials. These strategies provide more thermal comfort for long-term users. As a result, it is necessary to know the exact effect of using these strategies on thermal performance and energy consumption inside buildings. Therefore, researchers have developed many energy simulation tools and programs to provide a clear view of the nature of the building’s thermal performance and energy consumption based on data inputs about local weather situations of the building. Thus, we must know the ability of the software to model different design strategies and be sure that the results are valid. This paper aims to make an environmental simulation of an educational building in Montreal, Canada, using Design-Builder simulation and compare it with the as-built equivalent thermal zones applying different glazing materials, which is the main element of the building facade to enhance the thermal comfort with the lowest energy consumption and CO 2 emissions. This paper shows that using double glass low E 6/6mm Air gap is better for the case study building in cold climate weather that increases thermal comfort for the users, reduces energy consumption by 18.63%, and also reduces CO 2 emissions by 18.57% per year.
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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".