Bibliographic record
Abstract
In modern transit systems, maintaining air quality, environmental control, and Fire Life Safety within the underground portion of the system is an important component of the overall design and its compliance with the established life safety and comfort guidelines and standards. Typical, Heating, Ventilation, and Air Conditioning (HVAC) systems do not have sufficient capacity to control the heat and smoke from a large train fire at the station platform. Therefore, emergency ventilation and smoke control of the tunnels is combined with that in the underground stations. These emergency ventilation systems (EVS’s) require a large space and are often housed inside the stations that serve the underground portion of the transit system. Since underground portions of transit systems are often in dense urban areas, real estate and construction costs present a challenge to the system designers and minimizing the space requirements of the EVS becomes of paramount importance. An introduction to the principles of tunnel ventilation is presented and application of these principles in the underground portion of the Réseau Express Métropolitain (REM) in the new Montreal Airport Tunnel is discussed. The presentation includes the theoretical background, design criteria, regulatory requirements, analysis methods, and advanced numerical techniques used in developing the design of the tunnel ventilation system (TVS) and their specific application in the underground portion of the REM project. The proposed TVS design is presented, and results of the analysis are discussed.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".