Field evaluation of thermal and moisture response of highly insulated wood-frame walls
Bibliographic record
Abstract
Over the years, the energy efficiency of the North American housing stock has significantly improved mainly due to higher insulation levels, more efficient windows and, more importantly, adoption of various energy efficiency measures by building codes. The increased insulation levels of building envelopes for homes leads to a multitude of opportunities as well as challenges. A major opportunity is to reduce heat losses and thereby significantly reducing the space heating loads. However, there are many challenges that necessitate changes in the current construction process, durability of products, and more importantly, the effect of higher insulation levels on the overall moisture performance and expected long-term performance of the building envelope. A major barrier to the uptake of highly insulated homes is the lack of proven evidence of reliable thermal and moisture performance of these homes as might be achieved in various climates of Canada. Following a survey of current construction practices, a set of six wall assemblies with different types of exterior insulation systems were chosen for field monitoring study undertaken in two separate Phases over a two year period in a test facility located in Ottawa, Canada. These wall assemblies ranged from total insulation value of RSI-4.8 to RSI 7.9 (R-27 to R-45). Full scale testing included year-round performance monitoring. These wall specimens were installed in a side-by-side test bay and were subjected to local climate conditions of Ottawa, Canada; on the interior of the specimens conditions were nominally maintained at 20°C and 50% RH. This paper provides results of field trials of the six wall assemblies in terms of their hygrothermal performance and risk for condensation over a two year period of operation.
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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".