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Record W2071499791 · doi:10.1139/l03-055

Fibre-reinforced polymer composite bars for the concrete deck slab of Wotton Bridge

2003· article· en· W2071499791 on OpenAlexvenueaboutno aff
Ehab El-Salakawy, Brahim Benmokrane, G Desgagné

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsnot available
Fundersnot available
KeywordsServiceability (structure)Fibre-reinforced plasticDeckSlabStructural engineeringGirderBridge (graph theory)Span (engineering)Beam bridgeBridge deckGeotechnical engineeringEngineeringForensic engineeringMaterials science

Abstract

fetched live from OpenAlex

A new concrete bridge in the Municipality of Wotton, Quebec, Canada, was constructed using fibre-reinforced polymer (FRP) bars as reinforcement for the deck slab. The new bridge is a girder type with four main girders simply supported over a span of 30.60 m. One half of the concrete deck slab was reinforced with carbon and glass FRP bars, and the other half with conventional steel bars. The design of the reinforced concrete deck slab was made according to sections 8 and 16 of the new Canadian Highway Bridge Design Code. The bridge was well instrumented at critical locations for long-term internal temperature and strain data collection using fibre optic sensors. The construction of the bridge was completed and the bridge opened for traffic in October 2001. The bridge was then tested for service performance using standard truckloads. Design, construction details, and the results of the field test and 1 year of remote monitoring are discussed. Under the same real service and environmental conditions, very similar behaviour was obtained from the FRP (glass and carbon) and steel bars.Key words: concrete bridges, deck slabs, FRP bars, field test, fibre optic sensors, remote monitoring, serviceability.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.573
Threshold uncertainty score0.722

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 head0.008
GPT teacher head0.189
Teacher spread0.181 · 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 designSimulation or modeling
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

Citations67
Published2003
Admission routes2
Has abstractyes

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