Phase change materials to improve the energy savings of wood building envelopes in Quebec
Bibliographic record
Abstract
A large amount of energy is used to heat and cool buildings in the construction industry. Moreover, wood frame buildings’ relatively low thermal mass limits energy efficiency and thermal comfort. Thermal energy storage via latent heat can effectively increase the thermal inertia of the building envelope, minimising the indoor temperature fluctuations and improving the occupant thermal comfort. This paper evaluated the energy efficiency and thermal comfort of an air-conditioned wood frame building by using biobased phase change materials (PCM) as the middle layer of a building envelope. Numerical simulations were conducted to investigate the effect of different factors (PCM melting point, surface area, thickness, and position) by adding a PCM layer into building walls to reduce annual heating and cooling energy consumption. The results of the numerical simulations showed that a phase change material layer can effectively decrease the energy demand of buildings, especially in cold areas. Based on the conditions investigated, the optimum solution can reduce the cooling, heating and annual energy consumption by 47%, 34% and 38%, respectively, compared to a reference building without a PCM layer. Moreover, an economic and environmental study of buildings containing biobased PCM is presented.
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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 | 0.000 |
| 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) | 0.004 | 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".