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Record W2513875234 · doi:10.1149/ma2016-02/13/1335

Combined Numerical and Experimental Approach to Study the Effect of External SS316 Cathode on the Localized Corrosion in AA7050-T7451 Galvanically Coupled with SS316 Under Atmospheric Conditions

2016· article· en· W2513875234 on OpenAlexaboutno aff
Chao Liu, Robert G. Kelly

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsnot available
Fundersnot available
KeywordsCrevice corrosionCorrosionGalvanic cellMaterials scienceCathodeAlloyMetallurgyGalvanic corrosionElectrolyteComposite materialChemistryElectrode

Abstract

fetched live from OpenAlex

Connections between dissimilar metal alloys (e.g., aluminum (Al) alloy components and stainless steel (SS) fasteners) are frequently encountered in airframes exposed to an atmospheric marine environment. This exposure results in the formation of thin layer of electrolyte containing chloride species on the materials surface. The thin film electrolyte can wick into the tight crevice formed between the Al alloy component and the SS fastener when breakdown of corrosion protection coating happens. As a result, an electrochemical cell is established due to this galvanic coupling, and localized corrosion is likely aggravated in the crevice that forms. This corrosion damage can serve as a preferential site for fatigue crack formation, leading to failure of Al alloy components during operation. Developing mechanistic understanding of metal-environment interactions can provide guidelines for current protection system evaluation, as well as develop corrosion mitigation strategy during materials design stage. There are several influential environmental factors affecting atmospheric corrosion, including relative humidity (RH), water layer thickness (WL), concentration of dissolved species in the solution, temperature, etc. [2]. For localized corrosion due to galvanic coupling under atmospheric condition, it has been shown that the effect of external cathode outside the crevice formed in the galvanic coupling controls the extent of localized corrosion inside the crevice [3-4]. In the literature there is a limited amount of corrosion modeling work which focuses on atmospheric corrosion, and in those few cases that do exist, the electrochemical kinetics used in the modeling framework are mainly based on full immersion conditions, which might lose key features under atmospheric conditions. Hence atmospheric corrosion modeling work with accurate electrochemical kinetics is greatly needed to better understand the effects of the key external factors on electrochemical distributions that developed in the corrosion system involving a realistic thin film/galvanic couple configuration. In this work, a combined numerical and experimental approach is being applied to study potential and current density distributions as a function of two important variables for external cathode of SS316: water layer thickness on the external cathode as well as the size of external cathode. For the experimental work, a sintered Ag/AgCl electrode serving as a combined reference electrode (RE) and counter electrode (CE) [5] is implemented to characterize thin film electrochemical kinetics of AA7050-T7451 and SS316. A series of thin film electrolyte with thicknesses from 10m to 2000 m were used to study the effect of WL on electrochemical kinetics of testing materials as a function of scan rate and electrolyte concentration. An example of cathodic kinetics for SS316 in terms of WL is shown in Figure 1. In addition, the evolution of th ecrevice solution chemistry of AA7050 is mimicked by dissolving the alloy galvanostatically in the thin film cell before determining the anodic kinetics of AA7050 in that solution. The electrochemical kinetics of tested materials serve as boundary conditions in the modeling framework. For the computational work, the finite element method (FEM) [6] is applied to study both the effect of external cathode size and water layer thickness on potential and current density distributions along the AA7050 inside the crevice. Comparisons of potential/current density distributions with different external cathode sizes as well as water layer thicknesses under corresponding boundary conditions are used to illustrate the effects of atmospheric variables on localized corrosion damage along the crevice. Acknowledgement This work has been supported by the Office of Naval Research (ONR) Grant N00014-14-1-0012. Mr. William Nickerson, Technical Officer at Office of Naval Research is gratefully acknowledged. Reference [1] N. E. Co, and J. T. Burns, In Corrosion Research in Progress Symposium , pp. 47–51, NACE, Vancouver, Canada (2016). [2] H. Simillion, O. Dolgikh, H. Terryn, J. Deconinck, Corros. Revs., 32, 73-100 (2014). [3] Z. Y. Chen, F. Cui, and R. G. Kelly, J. Electrochem. Soc., 155, C360- C368 (2008). [4] Z. Y. Chen, and R. G. Kelly, J. Electrochem. Soc.,, 157, C69-C78 (2010). [5] P. Khullar, J. V. Badilla, and R. G. Kelly, ECS Electrochem. Lett., 4, C31-C33 (2015). [6] C. Liu, and R. G. Kelly, Electrochem. Soc. Interface, 23, 47-51 (2014). Figure 1

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.245
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes1
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