ABSTRACT POSITIVE PRESSURE VENTILATION FOR HIGH-RISE BUILDING
Bibliographic record
Abstract
blowing air into the structure. When appropriate openings or vents are used in the structure, the airflow produced by the fan exhausts contaminants to the outside. Fire departments have used PPV as a means to ventilate contaminated atmospheres after initial knockdown and extinguishment of a fire. In Ontario, the use of positive pressure ventilation is still relatively new. However, its use as a tool to improve conditions is being explored by a number of fire departments, including the Ottawa Fire Department. In 1998, a joint project with Canada Mortgage and Housing Corporation, Ottawa Fire Department, Tempest Technology Corporation, the Co-operators Insurance and National Research Council Canada (NRC), was initiated to investigate the use of PPV to vent smoke from high-rise buildings. NRC's ten-storey facility was used for the investigations. In the initial phase of the project, baseline tests were conducted to determine the airflow through an open exterior stair shaft door and pressures in the stair shaft produced by the fans under non-fire conditions. A second series of baseline tests were conducted using propane burners to simulate conditions (temperature and CO 2 concentrations) produced by a fire. These tests were used to investigate the effect of various parameters, including vent area on the effectiveness of the PPV system. Subsequently, the PPV system was used to vent smoke produced by fires involving typical residential furniture (sofas and beds). In addition, a limited number of tests were conducted with sprinklered heptane pan fires to investigate the effectiveness of the system in venting cool smoke. ii TABLE OF CONTENTS ABSTRACT ......................................................................................................................i TABLE OF...
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".