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Carbon-Fiber-Reinforced Polymer Repair to Extend Service Life of Corroded Reinforced Concrete Beams

2005· article· en· W2153416675 on OpenAlexaff
Tamer El‐Maaddawy, Khaled Soudki

Bibliographic record

VenueJournal of Composites for Construction · 2005
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceCorrosionComposite materialDeflection (physics)Beam (structure)Carbon fiber reinforced polymerFibre-reinforced plasticService lifeReinforced concreteReinforcementBendingStructural engineeringFlexural strength

Abstract

fetched live from OpenAlex

This paper presents the results of an experimental study designed to investigate the viability of using externally bonded carbon-fiber-reinforced polymer (CFRP) laminates to extend the service life of corroded reinforced concrete (RC) beams. A total of 14 beams, 152×254×3,200mm each, were tested. Three beams were not corroded; two of them were strengthened by CFRP laminates, while one specimen was kept as a virgin. The remaining 11 beams were subjected to different levels of corrosion damage up to a 31% steel mass loss using an impressed current technique. Six of the corroded beams were repaired with CFRP laminates, whereas the remaining five beams were not repaired. Eventually, all specimens were tested to failure under four-point bending. Corrosion of the steel reinforcement significantly reduced the load-carrying capacity of RC beams. At all levels of corrosion damage, CFRP repair increased the ultimate strengths of the corroded beams to levels higher than the strength of the virgin beam but significantly reduced the deflection capacity.

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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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

Citations93
Published2005
Admission routes1
Has abstractyes

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