Simulating Polarization Behavior of Propeller Materials in the Physical Scale Modelling of Shipboard Impressed Current Cathodic Protection
Bibliographic record
Abstract
Abstract Physical scale modelling (PSM) is a methodology in which a large structure subject to cathodic protection is physically modelled by maintaining a linear relationship between the model size and the conductivity of the electrolyte. In this way, the resistance path for current flow through the electrolyte for the model is maintained similar to that for the full-scale structure. PSM has been used in some NATO countries to evaluate and design shipboard impressed current cathodic protection (ICCP) systems. One issue that is not well resolved in the use of PSM is the altered polarization behavior of propeller materials in diluted seawater with reduced conductivity, as a result of the change in the conditioning film on these materials. Another issue is that the polarization behavior under flow conditions is not well represented in PSM. These issues affect the accurate modelling of shipboard ICCP systems. A discrete area current control (DACC) technique has been developed to address these two issues. This current control technique is capable of simulating the polarization behavior of propeller materials obtained in undiluted seawater under various conditions. This paper describes the functional details of the DACC technique, and demonstrates the application of the DACC technique for the simulation of the polarization behavior of propeller materials. Other applications of the DACC technique in PSM studies are also discussed.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".