Effects of selected wall orientation on the moisture performance of building envelope
Bibliographic record
Abstract
Hygrothermal simulations are necessary to permit analyzing moisture performance when designing wall assemblies. To limit the number of simulations, simulations are performed on a limited number of wall orientations, usually the orientation that potentially leads to the worst moisture response, which is assumed to be the one receiving the highest amount of wind-driven rain (WDR). The objective of this work was to verify this assumption considering different wall assemblies and climate conditions. Four cardinal orientations (North, East, South and West) and the wall orientation receiving the highest amount of annual WDR, hereafter called default orientation. The study was conducted for four different wood-frame wall systems that differ by their claddings assembly: brick veneer, fiberboard, stucco, and vinyl. Eleven Canadian cities belonging to different climate zones were considered: Calgary (AB), Charlottetown (PE), Halifax (NS), Moncton (NB), Montreal (QC), Ottawa (ON), Saskatoon (SK), St. John’s (NL), Toronto (ON), Vancouver (BC) and Winnipeg (MB). Three scenarios were investigated. In the first case, it was assumed that there is no rain deposition on the exterior surface of the cladding (no WDR) and as consequence no rain infiltration (no moisture source). The second scenario assumed rain deposition on the exterior surface of the cladding, but no rain infiltration. The final scenario assumes rain deposition on the exterior surface of the cladding and rain infiltration through the deficiencies in the cladding. For this last scenario, the amount of rain that penetrates through openings and reaches the sheathing membrane was assumed to be 1% of the WDR as suggested by the ASHRAE Standard 160. The analyses were performed using the wettest year in each city selected among the 31-year historical climate data based on Moisture Index (MI) ranking. For the performance analysis, four different performance indicators were evaluated: Maximum Moisture Content (MC) value in the OSB, Average MC in the OSB, Maximum Mould Index (MoI) value in the outer layer of OSB and Average MoI value in the outer layer of OSB. The mould index values were negligible for the cases where there was no WDR and only WDR. Therefore, the mould index analysis was limited only for the third scenarios wherein the water infiltration was assumed. The results obtained with the four performance indicators were similar. Therefore, only the results obtained for the maximum moisture accumulated in the OSB were analyzed. For the scenario assuming no WDR and no moisture source, it was observed that, irrespective of the orientation, cladding and city, it is the north direction that leads to the worst moisture performance. For the second scenario assuming WDR but no water infiltration and for that assuming WDR and moisture source, it was found that the default orientation leads to highest moisture accumulation in most the cities while in the remaining cities, the maximum moisture accumulation occurred in other orientations than the default one. The critical case was Montreal where the moisture accumulated in OSB using default orientation (North) was significantly different than the maximum values obtained in the East direction. Overall, the results showed that, for the wall assemblies and cities considered in this study, the North orientation is the one that leads to the worst moisture performance when the wall is well protected against rain deposition. In the scenarios where there is rain deposition on the wall or water infiltration, the orientation receiving the highest amount of annual WDR generally leads to the worst moisture response. However, using only the total amount of WDR may not be sufficient for all the cities and an analysis of hourly distribution of WDR will be required before selecting the orientation for undertaking hygrothermal simulations
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".