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Record W4368365358 · doi:10.1201/9781003348030-373

Tunnels and underground stations ventilation system

2023· book-chapter· en· W4368365358 on OpenAlexaboutno aff
A. Haghighat, N. Shahcheraghi

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsVentilation (architecture)Environmental scienceMarine engineeringArchitectural engineeringCivil engineeringMining engineeringEngineeringMeteorologyGeography

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.272
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.186
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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