Testing of Coatings for Offshore Service
Bibliographic record
Abstract
Abstract A test protocol was developed to provide an assessment of the effects of various film defects as well as to perform post-exposure qualitative and quantitative evaluations on eight different coatings systems. A variety of film defects were created; linear scribe, X-scribe, impact, and a welded U-channel. After exposure, the analysis consisted of visual evaluations (blister, rust, scribe creepage), as well as EIS, moisture permeability, and FTIR. The exposures were performed in an accelerated corrosion cycle (NACE TM0404/0304), as well as exterior exposure in 3 environments; Near-Ocean in both northerly and subtropical latitudes (Newfoundland and Florida) as well as light industrial (Cleveland, Ohio). The coatings were applied over a variety of surfaces preparations as well. It was found that EIS used in conjunction with accelerated cyclic exposure can predict a coating’s behavior in exterior. Angular surfaces (U-channel) was found to provide good visual information not observed in flat panels. Film thickness only seems to play a role if particularly high, but a thin film of highly UV resistant fluoropolymer may significantly retard corrosion.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".