Interaction of gas bubbles and oil droplets in subsea oil and gas blowouts – a new development of VDROP-J model.
Bibliographic record
Abstract
Abstract (2017-194) The presence of methane bubbles in the oil and gas blowout could greatly reduce the oil droplet sizes. Bubbles tend to introduce energy into the system and separate oil droplets from each other. The interaction of oil droplets and gas bubbles in the near field of a blowout was investigated numerically using the VDROP-J model, whose droplet size distribution (DSD) was thoroughly calibrated. For this purpose, a new numerical scheme has been developed in VDROP-J to account for the interaction of gas bubbles and oil droplets in the blowout, giving simultaneous simulation of bubble and droplet size distribution along the discharged plume. Validation shows improvement of the model compared with the one without considering the gas bubble and oil droplet interactions. Effects of gas volume fraction on the droplet formation are also investigated. This new development will enhance the knowledge in subsea oil and gas blowouts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".