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Record W2026519630 · doi:10.1139/l08-009

Evaluation of the new <i>Canadian highway bridge design code</i> shear provisions for concrete beams with fiber-reinforced polymer reinforcement

2008· article· en· W2026519630 on OpenAlexafffundvenueabout
Ahmed K. El-Sayed, Brahim Benmokrane

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFibre-reinforced plasticStructural engineeringReinforcementShear (geology)Reinforced concreteBridge (graph theory)Materials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

The Canadian highway bridge design code (CHBDC) contains provisions for designing concrete members with fiber-reinforced polymer (FRP) reinforcement. In the second edition of the code, new shear design procedures for FRP-reinforced sections are provided. These procedures are consistent with those for steel-reinforced members in the code, in consideration of some modifications that account for the substantial differences between FRP and steel reinforcement. The shear approach adopted in the CHBDC follows the traditional approach of V c + V s for shear design. This paper presents an evaluation of this approach by comparing it with experimental shear strengths of available test data on beams longitudinally reinforced with FRP bars and with or without FRP stirrups. In addition, the CHBDC approach was compared with the FRP shear design provisions currently in effect in North America using the available test results. The comparison shows that the CHBDC method significantly underestimates the shear strength of FRP-reinforced concrete beams. A proposed modification to this method is presented and verified against available test results.

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)0.000
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 score0.569
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.025
GPT teacher head0.215
Teacher spread0.190 · 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

Citations28
Published2008
Admission routes4
Has abstractyes

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