Determination of hygric properties of selected building envelope materials
Bibliographic record
Abstract
The escalating impacts of climate change have heightened precipitation and humidity level variations, intensifying the susceptibility of building envelope materials to moisture ingress. Such moisture-related issues pose significant threats to both short and long-term building lifetimes, including the emergence of mold growth risks. In response to this critical concern, an experimental study was undertaken to comprehensively assess the hygric properties of selected building materials, with a primary focus on three sheathing membranes (Spun-bonded PO film, Self-adhesive film, 60-min building paper) and two types of exterior sheathing (Type X Glass-Mat Sheathing and Regular Glass-Mat Sheathing). The investigation aimed to evaluate crucial material characteristics such as moisture diffusivity, water absorption coefficient, vapor permeability, water permeability resistance, hydrophobicity and density. Both gravimetric and non-gravimetric approaches were employed in a series of experiments to ensure a thorough analysis. The liquid diffusivity, a critical parameter for hygrothermal simulation, was determined by establishing moisture profiles across the sampling using Single-Sided Nuclear Magnetic Resonance (SS-NMR) as a magnetic tool. The results obtained through these experiments provide the data of hygric properties of the materials which are essential for assessing the moisture erformance of building envelope. The data generated, particularly the moisture diffusivity values determined by SS-NMR, serve as crucial inputs for future hygrothermal simulations, enabling more accurate predictions and informed decision-making in building design and construction. This report contributes to the ongoing efforts in developing resilient building materials capable of withstanding the challenges posed by climate-induced moisture variations.
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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 | 0.001 | 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".