(Invited) Investigating Galvanic Corrosion at a through-Coating Defect on Cu-Coated Carbon Steel Using X-Ray Micro Computed Tomography (μ-CT)
Bibliographic record
Abstract
The Nuclear Waste Management Organization (NWMO) is preparing to implement the safe long-term disposal of Canada’s used nuclear fuel in robust, corrosion-resistant used fuel containers (UFC). The current UFC design employs a strong carbon steel vessel, coated with copper for corrosion protection. This project explores corrosion processes that could happen on the surface of a container with a through-coating defect that exposes a small area of the underlying carbon steel, in contact with the copper coating, which corrosion scientists would consider a risk for galvanic (dissimilar metal) corrosion. High resolution ex situ and operando observations of Cu-coated carbon steel specimens with an artificial defect penetrating the copper to the steel, exposed to saline solutions with and without dissolved oxygen, have been made using X-ray micro computed tomography (μ-CT) to reveal the three-dimensional form of the corrosion damage and follow its progression with time (as shown for example in Figure 1). These measurements have shown that the form of the corrosion damage is dependent on both the type of additive manufacturing procedure used to create the Cu coating (electrodeposition or cold spray deposition) and the quality of the Cu/steel interface. In the presence of oxygen, the volume of corrosion damage increases linearly with time, independent of the type of coating, but with a rate dependent on the availability of oxygen. In the absence of oxygen, the corrosion rate is low and decreases with time. Post-experiment characterization of corrosion products by Raman spectroscopy indicated the presence of akageneite (β-FeOOH) and lepidocrocite (γ-FeOOH), depending on the solution conditions within the corroding defect. Figure 1
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".