Investigation of Influencing Factors on Air Leakage of Canadian Dwellings
Bibliographic record
Abstract
Air leakage is one of the main influencing factors in buildings’ thermal performance. The adverse effects of poor air leakage include higher energy costs, consumption in space heating and cooling, poor thermal comfort, corrosion, and the growth of molds due to air leakage induced condensation. The main objective of this study is to investigate the characteristics of air leakages of Canadian homes related to construction methods, age, size and climatic zones. The air leakage test results of 226,000 dwellings in three provinces of Canada were analyzed. Statistical analysis was utilized to compare the mean of air leakage with respect to different factors. Generally, the air leakage decreased by 40% in the period from 1960 until 2018, which has shown a remarkable effect of new construction techniques on air leakage. Investigations also indicated that the average air leakage rate of homes constructed by using the onsite technique is approximately 25% to 60% higher than those prefabricated in modular or panels, varying with respect to the workmanship and construction quality control. This study concluded that the prefabricated construction techniques could decrease the air leakage rate significantly, which will have a remarkable effect on buildings’ thermal performance as well as home’s heating and cooling costs. The findings contribute to estimating the effects of influencing factors on air leakage, also it is useful in performance simulations, HAVC sizing and energy management. And recommend the use of the prefabricated in modular or panel’s construction method to achieve better and acceptable air leakage performance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".