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On the subtilities of rebar corrosion behaviour in cracked concrete

2025· article· en· W4408309037 on OpenAlexafffund
Gang Li, Moh Boulfiza, Richard W. Evitts

Bibliographic record

VenueCement and Concrete Composites · 2025
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRebarCorrosionMaterials scienceForensic engineeringComposite materialStructural engineeringMetallurgyEngineering

Abstract

fetched live from OpenAlex

This study presents a comprehensive mechanistic corrosion model to simulate rebar corrosion in non-uniform corrosive microenvironments caused by cracking and exposure conditions. The proposed model comprehensively investigates all possible corrosion mechanisms in cracked concrete, addressing an experimental phenomenon that has perplexed experts for decades. In particular, it aims to elucidate the marked difference in corrosion behaviour observed in the presence of thin versus wide cracks. This study demonstrates that self-healing is the sole mechanism differentiating the corrosion behavior of thin and wide cracks, a finding enabled by advanced numerical modeling and experimental validation. Achieving this required a sophisticated physics-based model capable of capturing the major features of reinforcement corrosion in cracked concrete. The ability to selectively activate or deactivate specific mechanisms in the model provides a unique lens to isolate their contributions, which is often impractical in experimental setups. The findings of this study provide valuable insights into the concept of a “critical crack width”, below which reinforcement corrosion is unlikely to pose a significant concern.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.555

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 head0.009
GPT teacher head0.214
Teacher spread0.205 · 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

Citations10
Published2025
Admission routes2
Has abstractyes

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