Effects of Climate Change on the Moisture Performance of Tallwood Building Envelope
Bibliographic record
Abstract
The objective of this study was to assess the potential effects of climate change on the moisture performance and durability of massive timber walls on the basis of results derived from hygrothermal simulations. One-dimensional simulations were run using DELPHIN 5.9.4 for 31 consecutive years of the 15 realizations of the modeled historical (1986–2016) and future (2062–2092) climates of five cities located across Canada. For all cities, water penetration in the wall assembly was assumed to be 1% wind-driven rain, and the air changes per hour in the drainage cavity was assumed to be 10. The mold growth index on the outer layer of the cross-laminated timber panel was used to compare the moisture performance for the historical and future periods. The simulation results showed that the risk of mold growth would increase in all the cities considered. However, the relative change varied from city to city. In the cities of Ottawa, Calgary and Winnipeg, the relative change in the mold growth index was higher than in the cities of Vancouver and St. John’s. For Vancouver and St. John’s, and under the assumptions used for these simulations, the risk was already higher under the historical period. This means that the mass timber walls in these two cities could not withstand a water penetration rate of 1% wind-driven rain, as used in the simulations, with a drainage cavity of 19 mm and an air changes per hour value of 10. Additional wall designs will be explored in respect to the moisture performance, and the results of these studies will be reported in a future publication.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".