Hygrothermal Performance Evaluation of Multi-functional Panels for Building Envelope in Various Climate Conditions
Bibliographic record
Abstract
There is an increasing concern worldwide to discover ways to mitigate greenhouse gas emissions. Researchers are working in various industry sectors to discover environmentally-friendly solutions to produce goods and services. In the building sector, research focuses on the use of energy-efficient solutions for building design, construction, and operation. The research presented in this thesis investigates and evaluates the long-term hygrothermal performance of multi-functional panels (MFPs) in various wall assembly configurations to improve energy efficiency for residential buildings under varying climatic conditions. The MFPs are used as an additional layer attached to the exterior side of conventional wood-frame wall assemblies. The MFPs under investigation combine two layers of wood sheathing with other elements, such as wood fibre and Extruded Polystyrene (XPS) insulation, as additional external layers to conventional light wood-frame wall assemblies in order to improve the overall energy efficiency of conventional wall assemblies. Field monitoring data was collected for two years, was analyzed, and comparisons between the two MFPs and a conventional wall assembly were made. For a complete analysis, the evaluation was conducted using real-life scenarios in test huts situated in two different climates in Canada: Vancouver, British Columbia, with a coastal humid climate; and Edmonton, Alberta, with an extremely cold climate in winter. This study will provide a field hygrothermal investigation for the application of wood fibre insulation—an environmentally-friendly and recyclable material—for the North American housing market.
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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 | 0.000 |
| 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".