The effects of droplet size distribution and wave characteristics on the vertical dispersion of spilled oil due to regular non-breaking waves
Why this work is in the frame
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Bibliographic record
Abstract
Oil pollution in marine environments is a contributing factor that disrupts the ecosystem balance and causes extensive damage. In this study, numerical simulation is chosen to study the transport and fate of spilled oil. The dispersion of oil in the water column is investigated using a Eulerian-Lagrangian numerical software model named OpenFOAM. The solver is developed to simulate the discrete phase (oil particles) in the continuous phase (water). The dispersion of oil in the water column due to wave-induced currents is studied considering particles of various size distributions. The best oil droplet size distribution is chosen according to the statistical parameters. In addition, the effect of various parameters such as the wave steepness, the wave period, the volume of the spilled oil, and the horizontal and vertical position of the sampling point on the distribution of oil concentration at depth is investigated. The results of the dispersed oil concentration for 20 cc and 30 cc spill volumes are compared with the experimental data cited in the literature and also presented for various hydrodynamic scenarios. The results of this study show the dependency of selected parameters on the variation of maximum oil concentration in the water column. A relationship is proposed and validated to calculate the maximum volume of dispersed oil based on the results of numerical simulation. The maximum volume of dispersed oil can be predicted by the proposed relationship with an accuracy of up to 40%.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it