CFD simulation of the fire dynamic for a section of a tunnel in the event of a fire
Bibliographic record
Abstract
The objective of this research is to evaluate the in-place emergency ventilation strategies of the L. H.-La Fontaine tunnel. This paper investigates the fire dynamics in one section of the 1.8 km long tunnel. CFD simulations of several fire scenarios were carried out, to gain insight into the effect of several parameters on the fire growth, thermal conditions and species concentrations in the tunnel in the event of fire. A section of the tunnel was simulated to optimize the cost of computations. In the first part of the study, a sensitivity analysis was performed to determine the effect of the computational grid size and length of the investigated section of the tunnel. The results of this analysis were used to determine the appropriate grid distribution and section length for the parametric study. Results from the sensitivity study showed that the grid size influenced both the computing time and the predictions of the temperature and smoke. Moreover the analysis showed that a 300 m long section of the tunnel was appropriate to investigate the ventilation scenarios. A parametric study was conducted to investigate the effect of different ventilation configurations on fire-induced flows and thermal conditions in the tunnel section. This study indicated that when the side upper supply vents are open, higher temperatures and CO2 concentrations are observed in the evacuation path. In the roadway area, a smoke backlayering phenomenon was observed which may delay the removal of combustion gases and heat. It was concluded that the opening of the upper supply vents delayed smoke removal and, consequently, increased hazardous situations in both the traffic and escape paths.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".