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Bond Behavior of Corroded Steel Reinforcement in Concrete Wrapped with Carbon Fiber Reinforced Polymer Sheets

2003· article· en· W2051618887 on OpenAlexaff
Khaled Soudki, Ted Sherwood

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceCorrosionComposite materialBond strengthConcrete coverUltimate tensile strengthSteel barReinforcementCementBondFibre-reinforced plasticAdhesiveLayer (electronics)

Abstract

fetched live from OpenAlex

This paper examines the ability of carbon fiber reinforced polymer (CFRP) wrapping to enhance the bond of corroded reinforcing steel bars in concrete. Thirty-two bond pullout specimens were considered. Test variables included the clear concrete cover (15, 30, and 60 mm or 0.6, 1.2, and 2.4 in.), degree of corrosion (0, 1, 5, 7, and 10% mass loss), and presence or absence of transverse CFRP wrapping. The specimens consisted of a concrete prism measuring 150×150×200mm(6×6×8in.) with a No. 10 M reinforcing bar placed in the corner of the prism. The specimens were constructed with 3% Cl- by weight of cement premixed in the concrete to depassify the tensile reinforcing steel. The specimens were placed in a constant high-humidity environment, and corrosion was induced by means of an impressed current. Following corrosion, the specimens were tested by bar pullout to determine the bond strength versus slip of the reinforcing bars. The bond strength of the reinforcing bars in the concrete prisms increased at a small level of corrosion, but decreased as the degree of corrosion increased. The failure mode typically was bond splitting in unwrapped specimens. Strengthened specimens exhibited an increased bond strength and failure by bar pullout due to the confining effects of the CFRP strengthening.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.201
Teacher spread0.193 · 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".

Quick stats

Citations50
Published2003
Admission routes1
Has abstractyes

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