Factors Affecting Ventilation and Acoustical Quality in a Sustainably-Designed and in Conventional Buildings — A Pilot Study
Bibliographic record
Abstract
This paper discusses a pilot study involving direct monitoring of airflow and acoustical quality in a sustainably-designed and in conventional buildings. The objectives were to measure these environmental aspects, determine the factors affecting them and the relationships between them and key building-design concepts, and consider the implications of the results for ventilation-system design. Selected rooms in buildings with natural and mechanical ventilation, without and with acoustical treatment, were monitored. Measurements were made of airflow rates and acoustical quality. Correlations between these environmental aspects, the types of building and ventilation system, and the building window status were investigated. In rooms with natural ventilation, noise levels were lower; however, the rooms had lower airflow rates. Rooms with mechanical ventilation had higher airflow rates, but noise levels were higher; HVAC noise was a problem if the system was not well designed. In naturally-ventilated buildings, airflow rates and noise levels were low with windows closed, but opening the windows to increase the airflow rate resulted in higher noise levels. The results of the study suggest that the acceptability of indoor environments in buildings depends on the degree of compliance of the design and its implementation with standards and design guidelines, whether the original design is ‘sustainable’ or not.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".