CFD fire simulation of the Swissair Flight 111 in-flight fire – Part II: Fire spread analysis
Bibliographic record
Abstract
Abstract In 1998, Swissair Flight 111 (SR111) developed an in-flight fire shortly after take-off which resulted in the loss of the aircraft, a McDonnell Douglas MD-11, and all passengers and crew. The Transportation Safety Board (TSB) of Canada, Fire and Explosion Group launched a four year investigation into the incident in an attempt to understand the cause and subsequent mechanisms which lead to the rapid spread of the in-flight fire. As part of this investigation, the SMARTFIRE Computational Fluid Dynamics (CFD) software was used to predict the ‘possible’ development of the fire and associated smoke movement. In this paper the CFD fire simulations are presented and model predictions compared with key findings from the investigation. The model predictions are shown to be consistent with a number of the investigation findings associated with the early stages of the fire development. The analysis makes use of simulated pre-fire airflow conditions within the MD-11 cockpit and above ceiling region presented in an earlier publication (Part I) which was published in The Aeronautical Journal in January 2006.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".