Comparison of Impressed Current Cathodic Protection Numerical Modeling Results with Physical Scale Modeling Data
Bibliographic record
Abstract
Physical scale modeling (PSM) is an experimental technology that has been used to evaluate and design shipboard impressed current cathodic protection (ICCP) systems by various researchers and designers. PSM is also a preferred tool for validating ICCP numerical modeling results, owing to the well-controlled conditions in PSM experiments. However, one issue in using PSM for the validation of numerical modeling results is the lack of information on the actual polarization behavior of the cathodes on a model hull during PSM experiments. Consequently, the polarization curve data used as boundary conditions in numerical modeling trials is usually different from the polarization behavior of the cathodes in PSM experiments. This difference can result in a discrepancy between the numerical modeling and the PSM results, which is difficult to separate from other numerical errors. A discrete area current control (DACC) technique was developed in a previous ICCP PSM study to simulate the polarization behavior of a propeller material under various conditions. The present study extended the DACC technique to simulate the polarization curve behavior of four discrete cathodes representing one nickel aluminum bronze (NAB) propeller and three discrete steel patches. This study also demonstrated that use of the DACC technique can ensure that both PSM and numerical modeling studies use identical polarization curve relationships as boundary conditions. The technique facilitates the use of the PSM results for comparison with numerical modeling results. The comparison study showed good agreement between the PSM results and numerical modeling results, in both simulated static and dynamic flow conditions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".