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Framework for Durability-Based Design for Concrete-Steel Bond against Corrosion

2008· article· en· W1964750532 on OpenAlexafffund
Lamya Amleh, Saeed Mirza

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsToronto Metropolitan UniversityMcGill University
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsDurabilityRebarCorrosionConcrete coverMaterials scienceSteel barStructural engineeringBond strengthBondReinforced concreteComposite materialEngineeringAdhesiveLayer (electronics)

Abstract

fetched live from OpenAlex

The current understanding of the mechanics of bond resistance at the interface between concrete and plain and deformed steel bars is reviewed briefly along with the influence of corrosion on the phenomenon. Some of the available research on analytical models in both corroded and uncorroded steel bars is also reviewed. The influence of some of the significant parameters influencing the behavior of corroded bars, such as the concrete strength, crack width, extent of rebar corrosion (measured by mass loss), concrete cover thickness, bar diameter, and the loss of rebar lugs is reviewed. In addition, a preliminary framework is presented for design of reinforced concrete for durability against deterioration of bond due to steel rebar corrosion. A framework for design of structural concrete for durability against deterioration of bond at the steel-concrete interface due to corrosion of rebars is proposed. The technical note also stresses the need for more research on the above and other parameters influencing the deterioration of bond due to corrosion, before establishing a reliable design method using a semiprobabilistic approach in the design of structural concrete for other phenomena.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.401
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.033
GPT teacher head0.247
Teacher spread0.214 · 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.

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

Citations7
Published2008
Admission routes2
Has abstractyes

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