Dynamic Change in Throwing Power for the Cu-to-Carbon Steel Galvanic Couple in the Presence of Bentonite
Bibliographic record
Abstract
In galvanic corrosion, the maximum distance from the periphery of the cathode to the anode is often defined as the throwing power. It dictates the surface area of the cathode involved in the galvanic corrosion and is also related to the extent of the accelerated anodic reaction. Therefore, its estimation is of great interest and importance in engineering applications, such as fastener and panel assembly [1], metal coatings [2], buried metallic structures [3], etc. Throwing power may be estimated experimentally by measuring the solution potential variation in close proximity to the electrode surface (E s ) or through modelling, such as finite element analysis (FEA), provided the boundary conditions (polarization characteristics) are correctly determined. In this work, we investigated the throwing power for the Cu-to-carbon steel galvanic couple in the presence of bentonite clay, a scenario that could arise in the vicinity of a through-coating defect in the Canadian-designed nuclear waste container. Using a homemade micro-reference electrode array coupled to a Multichannel Microelectrode Analyzer (MMA), E s was measured simultaneously in 10 locations as a function of time in 0.1 M NaCl solution with and without bentonite clay, Fig. 1. Transient potential peaks were found when bentonite clay was added to the solution and are attributed to the increased galvanic activities driven by the reduction of air-formed Cu oxides. We further investigated this phenomenon using FEA. Boundary conditions were established experimentally under circumstances reflecting the actual surface states, i.e., with or without Cu oxides. Simulations were conducted considering secondary current distribution, using the appropriate boundary conditions. The obtained results match well with the experimental measurements, including the peak and the stable E s . Additionally, the dynamic change of the throwing power due to the evolution of the surface state was investigated through simulation and discussed. Reference [1] R.S. Marshall, A. Goff, C. Sprinkle, A. Britos, R.G. Kelly, Estimating the Throwing Power of SS316 when Coupled with AA7075 Through Finite Element Modeling, Corrosion, 76 (2020) 476-484. [2] J.R. Scully, F. Presuel-Moreno, M. Goldman, R.G. Kelly, N. Tailleart, User-Selectable Barrier, Sacrificial Anode, and Active Corrosion Inhibiting Properties of Al-Co-Ce Alloys for Coating Applications, Corrosion, 64 (2008) 210-229. [3] L. Liu, J. Li, M. Peng, W. Li, B. Lei, G. Meng, Macro-galvanic corrosion of tower grounding device consisting of graphite and Zn-coated steel in a simulated soil environment, Engineering Failure Analysis, 135 (2022) 106136. Figure 1
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".