Bibliographic record
Abstract
Abstract The shaft grounding systems used on board HMC ships have substantially reduced the shaft-to-hull resistance and, thus, improved the performance of the shipboard impressed current cathodic protection (ICCP) system. Under some circumstances, however, the shaft grounding systems have been left on while the ICCP system was turned off. This led to the accelerated corrosion of the exposed steel ship hull on paint holidays because of the substantial difference of the electric potentials between the steel ship hull and the nickel-aluminum bronze propellers. The extent of the increased corrosion rate of the steel ship hull depends on a variety of conditions including the locations and areas of the paint holidays on the ship hull, the overall paint degradation, and seawater domain where the ship is located. A boundary element code, named CPBEM, developed at Defence R&D Canada – Atlantic was used to numerically simulate the galvanic corrosion of the steel hull under the afore-mentioned various conditions. A box model was also used to demonstrate the effect of fluid domain on galvanic corrosion current and solution resistance. The modelling results have shown that the paint damage area significantly affects the galvanic corrosion rate, while the effect of the paint damage location on the galvanic corrosion rate is not significant when the ship is in an open sea. The little solution resistance encountered in the area away from the anodes and the cathode is attributed to the much larger cross sectional area for the galvanic current path in the large volume of seawater. The potential contours and galvanic corrosion current at various degrees of the paint degradation were also demonstrated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".