Characterization and Hygrothermal Impact of Water Resistive Barriers on Mould Growth in Wood-Frame Wall Assemblies
Bibliographic record
Abstract
Water-resistive barriers (WRBs) are vital components in building envelope systems, particularly in wood-frame buildings, where moisture-induced decay is a major durability concern. This study presents a detailed experimental characterization of three WRB membranes, quantifying key transport properties including vapor permeability, liquid diffusivity, moisture storage, and saturation content using high-precision gravimetric methods. The resulting moisture-dependent functions were integrated into hygrothermal simulations using DELPHIN, and mould growth risk was assessed via the VTT model under varying wall configurations and climates. Results show that while material properties such as vapor permeability and liquid diffusivity significantly influence moisture behavior, they alone do not guarantee moisture control. Wall design and climate conditions also play a critical role. In cold-wet conditions, some assemblies exceeded the ASHRAE 160 mould index threshold of 3.0, indicating risk of visible mould growth. These findings underscore the need for comprehensive evaluation of WRB performance, incorporating both material characterization and system-level context to support durable, mould-resistant buildings.
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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 | 0.000 | 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".