Assessing the Impact of Reflective Building Envelopes on School Indoor Thermal Autonomy and Energy Efficiency in Montreal: Historical and Future Climate Perspectives
Bibliographic record
Abstract
This study investigates the impact of high-performance polyvinylidene fluoride-co-hexafluoropropylene (P(VDF-HFP)HP), a reflective material, on the energy performance and Indoor Thermal Autonomy (ITA) of a primary school building in Montreal under historical and future climate scenarios. Energy simulations, conducted using Rhino-Grasshopper, analyze heating and cooling demands for an ANSI/ASHRAE/IES Standard 90.1 school prototype designed according to the 8th edition of the National Building Code of Canada (NBC), reflecting construction practices the 1980’s. The results reveal that reflective materials slightly increase heating demand due to reduced passive solar heat gains during winter but significantly lower cooling demand by minimizing solar heat absorption. In a heating-dominated climate like Montreal, this trade-off leads to a net reduction in total energy use under future climate scenarios. As the warming climate lessens heating requirements, the substantial decrease in cooling demand contributes to overall energy savings. Reflective materials thus prove particularly advantageous in warmer future climates, where the cooling energy savings outweigh the heating penalty, improving overall building energy performance. In addition, reflective materials enhance ITA, albeit marginally, with a maximum increase of 3%, improving indoor comfort under both historical and future climate conditions. These findings highlight the potential of passive building envelope enhancements to contribute to energy efficiency and climate resilience. By promoting sustainable solutions, reflective materials align with the United Nations Sustainable Development Goal 13 (Climate Action).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".