Performance of displacement ventilation in Canadian schools: field studies
Bibliographic record
Abstract
Displacement ventilation systems take a fundamentally different approach to space conditioning than the systems found in the majority of commercial buildings, which currently use a fully mixed and dilution approach to ventilation. Displacement ventilation (DV) is an alternate air distribution method for commercial spaces, in particular schools. Previous research has shown that this type of system works well for regions where buildings require year-round cooling, however there are a growing number of buildings using this approach in Canada, where buildings require heating during winter months. A series of field studies in existing Canadian schools were carried out during the heating season over the last three years. This paper presents results from field studies conducted in schools designed for displacement ventilation with a perimeter radiant heating system. We measured several aspects of the performance of a DV systems installed in schools located in different parts of the country. The results show that the measured contaminant removal effectiveness was higher than that provided in previous studies for heating mode. In addition, key predictors of thermal comfort are also generally within limits set by ASHRAE standards. The results of these field studies provide some evidence of thermal comfort and IAQ-related benefits of DV in cold climate. However, before general conclusions are drawn, the benefits need to be confirmed in other studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".