Fire Resistant Booms Tested in Flames at Ohmsett
Bibliographic record
Abstract
ABSTRACT An enhanced propane underwater bubbler system designed to allow the testing of fire-resistant booms in flames was installed at Ohmsett in the fall of 1998 by the Minerals Management Service (MMS) and the US Navy Supervisor of Salvage and Diving (SUPSALV). The test is based on a screening protocol for testing fire resistant booms in waves and flames developed for MMS and the Canadian Coast Guard (CCG). The cornerstone of the test is an underwater bubbler system to create air-enhanced propane flames that produce an average total heat flux to the surface of a candidate containment system in the range of 110 to 130 kW/m2 and flame temperatures near the containment device on the order of 900°C. The candidate boom is stretched over the center of the bubbler, parallel to the long dimensions of the test tank, and tensioned to realistic towing forces. The fire exposure portion of the test involves three cycles of one hour of exposure to air-enhanced propane flames in waves, followed by a one-hour cool-down period in waves alone, and conforms to ASTM F 2152-01. Since the air-enhanced propane system was developed, 11 fire resistant boom systems have been tested. These include: three refractory fabric booms, one stainless steel boom, three water-cooled blanket prototypes, three reflective/insulating blanket prototypes, and one water-cooled boom. This paper summarizes the test methods used and the results.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".