Assessment of building retrofit options using hygrothermal analysis tool
Bibliographic record
Abstract
As the stock of buildings in our society ages, it is expected that there will be an increase in building envelope rehabilitation work. Such activities represent an ideal opportunity to modify the existing wall system to improve building envelope durability and energy efficiency. This could be done by addition of insulation and sealing air leakage paths. However, there is very little information available on how to assess the moisture and energy (i.e. thermal) performance of retrofitted building envelope assemblies and select the optimum retrofit options that will maximize the long-term moisture performance and the energy efficiency of the retrofitted building envelopes together. This paper presents the findings from a study that has used a two-dimensional hygrothermal simulation tool, hygIRC-2D, to assess moisture and energy performance of retrofitted masonry walls used in high-rise construction for both residential and commercial types of buildings at various Canadian locations. The results from the simulations indicate that, if heat, air and moisture transport properties of the materials and the airflow characteristics of the systems can be defined properly a hygrothermal simulation tool can be used to evaluate the moisture and thermal (i.e. energy) performance of various wall systems and associated retrofit options.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".