Modeling and analysis of a catastrophic oil spill and vapor cloud explosion in a confined space upon oil pipeline leaking
Bibliographic record
Abstract
Abstract Oil spill-induced vapor cloud explosions in a confined space can cause catastrophic consequences. In this work, investigation was conducted on the catastrophic pipeline leak, oil spill, and the resulting vapor cloud explosion accident occurring in China in 2013 by modeling analysis, field surveys, and numerical simulations. The total amount of the spilled oil was up to 2044.4 m3 due to improper disposal. The long residence time of the oil remaining in a confined space permitted the formation of explosive mixtures and caused the vapor cloud explosion. A numerical model was developed to estimate the consequence of the explosion based on volatilization testing results. The results show that the death-leading zone and the glass-breaking zone could be 18 m and 92 m, respectively, which are consistent with the field investigation. The severity of the explosion is related to the amount of the oil spill, properties of oil, and volatilization time. It is recommended that a comprehensive risk assessment be conducted to analyze the possible consequences upon oil spilling into a confined space. Prompt collection and ventilation measures should be taken immediately after the spill occurs to reduce the time for oil volatilization and prevent the mixture from reaching its explosive limit.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".