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Record W2071853757 · doi:10.1139/l05-088

Corrosion of concrete reinforcement and electrochemical factors in concrete patch repair

2006· article· en· W2071853757 on OpenAlexaffvenue
Jieying Zhang, Noel P. Mailvaganam

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCorrosionMacrocellMaterials scienceMicrocellCathodic protectionReinforcementComposite materialForensic engineeringElectrochemistryEngineeringChemistryElectrode

Abstract

fetched live from OpenAlex

Corrosion of concrete reinforcement at a patch repair is a complex problem, and current knowledge of its mechanism is quite limited. This review examined the correlation between two corrosion mechanisms, macrocell and microcell corrosion, from fundamental electrochemical principles. It was found that both mechanisms could play significant roles in inducing corrosion damage, contrary to the prevailing opinion that macrocell corrosion is the main deterioration mechanism in patch repair. This has practical implications that need to be considered for an effective and durable repair. A review of the studies done to date also enabled the identification of the key factors in patch repair controlling the corrosion characteristics. Corrosion could occur at different locations in the vicinity of the patch — substrate, interface, or patch area — depending on the respective electrochemical environments induced by the repair material properties and treatments, as well as the in-service exposure and mechanical loading. The review indicates that much of the needed research should focus on identification of corrosion mechanisms to effect successful patch repair in reinforced concrete structures.Key words: patch repair, substrate, corrosion, macrocell corrosion, microcell corrosion.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.758

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 head0.005
GPT teacher head0.172
Teacher spread0.167 · 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 teacher head, 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".

Quick stats

Citations26
Published2006
Admission routes2
Has abstractyes

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