Analysis of alternative ventilation strategies for existing multi-family buildings using CONTAM simulation software
Bibliographic record
Abstract
In many existing high-rise multi-family buildings, a pressurized corridor ventilation system is used to meet outdoor air ventilation requirements. However, this system often has poor performance, leading to under- or over- ventilation in different parts of a building. This study examines three ventilation strategies including: the base case, which is a traditional pressurized corridor ventilation system, a direct-to-suite ducted ventilation system, and a suite-based HRV ventilation system. A building model was constructed in CONTAM using features of a typical post-war multi-family building in Toronto, Canada. All three strategies were simulated using CONTAM under both summer and winter conditions. The resulting outdoor airflow delivery rates to the suites and corridor pressure differentials were compared to assess the effectiveness of each strategy. The results show that the suite-based HRV strategy is able to provide adequate ventilation airflow to individual suites in both summer and winter. In the traditional pressurized corridor system and the direct-to-suite ducting system, the airflows delivered to the suites located at the top of the building are higher than those delivered to the suites located at the bottom of the building. This uneven airflow distribution is more pronounced in winter when stack effect impacts the ventilation system more significantly.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".