Hygrothermal Performance of Drywall Reinforced with Kraft-Paper Honeycomb in the Canadian Context
Bibliographic record
Abstract
Drywall board-based structures, a competent and cost-effective method of providing flexible partitioning assemblies in commercial and residential houses, are now widely used as walls or ceilings. However, the gypsum-based drywall that has been used in construction is not water-resistant and can create problems such as mold growth and structural defects. The aim of this study is 1) to develop a new sandwich panel with better physical and mechanical properties using locally sourced materials 2) to investigate the long-term hygrothermal performance of the new sandwich panel through using a numerical simulation. The sandwich panel is composed of two different thicknesses of kraft-paper honeycomb core bonded to two cementitious panels with silicone-based adhesive. The experimental results show that the sandwich panel with a thicker core has lower thermal conductivity and higher flexural strength compared to the gypsum-based drywall. The heat and moisture performance of two wall structures were performed using the WUFI Pro simulation program. The results of the modeling analysis present that wall assembly with gypsum-based drywall has higher water content than multilayer sandwich panel. In addition, the multilayer sandwich panel shows a 4.6% lower annual heat flow compared to the reference wall.
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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 | 0.000 | 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".