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Record W4393987706 · doi:10.1002/maco.202414367

Effect of gap size on flange face corrosion

2024· article· en· W4393987706 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterials and Corrosion · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlangeFace (sociological concept)CorrosionMaterials scienceMetallurgyComposite materialPhilosophy

Abstract

fetched live from OpenAlex

Abstract Bolted flanged joints play a critical role in offshore wind turbine tower structures, serving as integral components that connect various sections of the tower. This research study employs electrochemical techniques to investigate the effect of gap dimensions, which determine the crevice gap thickness and crevice depth, on corrosion behavior of 321 stainless steel flange sample plates in a 3.5 wt% NaCl solution at 50°C. Gaskets are used in this study to create gaps between two flange surfaces. A novel fixture is utilized to simulate the applied stress on the gasket, fluid flow within the fixture, and the geometric aspects of the gasket and flange. The findings reveal that increasing the gap thickness from 1.58 to 6.35 mm results in a rise in the general corrosion rate of the flange surface from 0.09 to 1.03 mm y −1 , and crevice corrosion initiation time increases from 0.23 to 3.12 h. Furthermore, reducing the crevice depth ( d ) from 7.49 to 0 mm leads to a decrease in the general corrosion rate from 0.09 mm y −1 to 0.04 µm y −1 , and cases with d = 3.81 and d = 0 mm show no observable crevice corrosion after potentiostatic tests.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.248
Teacher spread0.241 · 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