CORRELATING WAVE TANK DISPERSANT EFFECTIVENESS TESTS WITH AT-SEA TRIALS
Bibliographic record
Abstract
ABSTRACT Two important questions facing oil spill responders, planners, and researchers are:What is the limiting viscosity of oil for dispersant use; andHow well do results from dispersant effectiveness tests performed in laboratory apparatus and experimental wave tanks reflect dispersant performance at sea? In order to begin addressing these questions, a series of at-sea dispersant effectiveness trials were completed in the UK in the summer of 2003 to estimate the viscosity of spilled fuel oils that limits dispersant effectiveness under conditions of moderate sea states (Beaufort Sea states 2 to 4) (Lewis 2004). Two well-characterized marine fuel oils (IFO 180 and IFO 380) with viscosities of 2000 and 7000 cP were spilled, sprayed with dispersants, and dispersant effectiveness was assessed. Several types of dispersants and a range of dispersant dosages were tested. These tests are currently being repeated using a variety of laboratory and meso-scale dispersant effectiveness apparatus to determine how well the results of these various test methods correlate with dispersant performance at sea. Dispersant effectiveness tests in the SL Ross wave tank, using the identical oils and dispersants from the UK offshore trial, were the focus of this study. The goal of the work was to determine if the dispersant effectiveness test results from this tank are similar to results measured in the offshore. The tank testing indicated that the IFO 180 oil (viscosity of 2000 cP at the test temperature of 16 °C) is readily dispersible with Corexit 9500 and Superdispersant 25 when applied at dispersant-to-oil ratios (DORs) exceeding 1:75 for Corexit 9500 and 1:50 for Superdispesant 25. The IFO 380 fuel oil (viscosity of 7000 cP at the test temperature of 16°C) was 53% dispersed when treated with Corexit 9500 at a DOR of 1.30. The IFO 380 oil can be dispersed, but larger quantities of dispersant must be applied to achieve significant results. The tank test dispersant effectiveness results measured for the Corexit 9500 dispersant were similar to the UK field test trends for the IFO 180 oil and were somewhat higher than the field results for the IFO 380 oil. The tank test results for Superdispersant 25 were slightly higher than the field trial trends for the IFO 180 oil and slightly lower for the IFO 380 oil. The limited data available for the Agma DR379 dispersant suggests that the tank test results were similar to the offshore trial results for the IFO 180 oil and lower for the IFO 380 oil. In general, the SL Ross tank test results matched the trends in the offshore results reasonably well. Variations in sea states and DORs during the sea trials, insufficient data points for direct comparison and the lack of resolution in the 4-point visual assessment system do not permit a more definitive comparison of the results of the test programs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".