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Control of Corrosion-Induced Damage in Reinforced Concrete Beams Using Carbon Fiber-Reinforced Polymer Laminates

2005· article· en· W2103806215 on OpenAlexaff
Moataz Badawi, Khaled Soudki

Bibliographic record

VenueJournal of Composites for Construction · 2005
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsUniversity of Waterloo
FundersSaudi Arabian Cultural Bureau
KeywordsCorrosionMaterials scienceComposite materialCrackingFibre-reinforced plasticBeam (structure)Reinforced concreteShear (geology)PolymerSpan (engineering)Carbon fiber reinforced polymerCarbon steelStructural engineering

Abstract

fetched live from OpenAlex

This paper presents the results of an experimental study conducted to investigate the effect of carbon fiber-reinforced polymer (CFRP) confinement on the cracking damage induced by impressed current-accelerated corrosion of reinforced concrete beams. The beams were 254mm deep by 152mm wide by 3,200mm long. Two different corrosion configurations, namely uniform and shear-span corrosion, were investigated in eight specimens at three different degrees of corrosion (5, 10, and 15% theoretical mass loss). Uniform corrosion along the whole length of the beams (3,000mm) and shear-span corrosion (900mm from each beam end) were considered. The different degrees of corrosion were induced using an accelerated corrosion technique with an impressed current. Based on the results, it was concluded that CFRP laminate confinement reduces corrosion expansion by up to 70% and slows the rate of corrosion through decreasing the corrosion mass loss by up to 35%.

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 score0.001

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)0.0000.000

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 head0.225
Teacher spread0.216 · 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

Citations82
Published2005
Admission routes1
Has abstractyes

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