Performance investigation of emergency ventilation strategies in a new section of a road tunnel
Bibliographic record
Abstract
The National Research Council of Canada (NRC) conducted a study to evaluate the effectiveness of the current emergency ventilation system (EVS) to control smoke and hot gases originating from fires in a new section of a road tunnel in Montréal, Canada. The project uses the Computational Fluid Dynamics (CFD) technique for simulating smoke movement behaviour. Data from full-scale tests were used to verify the CFD model. The study provided recommendations to improve the effectiveness of the EVS. The study findings indicated that the effectiveness of the EVS was significantly affected by large pressure losses in the ventilation fans plenum and by the obstruction of large concrete beams to airflow. To improve the effectiveness of the ventilation fans, the study recommended the introduction of a ducting system to control airflow losses and to better direct airflow in such a way as to avoid impacting on the beams. With the high ceiling in this section of the tunnel, the possibility of collecting and storing smoke and hot gases at high elevations was investigated by operating the EVS in exhaust mode.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".