Resilience of Canadian homes and small buildings to the effects of climate change - Risk of deterioration due to condensation within wall assemblies
Bibliographic record
Abstract
The objective of this study was to assess the potential effects of climate change on the moisture performance and durability of typical Canadian wood-frame walls using hygrothermal simulations, with a particular attention to the risk of condensation. To reduce the risk of condensation, the National Building Code of Canada (NBCC) recommends a maximum air leakage rate of 0.10L/sm2 at 75 Pa in buildings with interior relative humidity not greater than 55%. This leakage rate was evaluated in five cities across Canada for a wood-frame wall having brick cladding, with and without outdoor insulation and both walls meeting the minimum insulation requirements given in NBCC. It is found that the risk of condensation will be reduced in the future in all 5 cities analysed. The reduction in the risk of condensation is slightly higher for the wall with no exterior insulation than for the wall with exterior insulation. This reduction in the risk of condensation means that the limit of 0.10L/(sm2) for building having a warm side relative humidity of less than 55% may be reconsidered in the future. There may however be some risks associated with the increase in rain in some cities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".