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Record W4223469120 · doi:10.1002/suco.202100730

Assessing beam shear behavior with distributed longitudinal strains

2022· article· en· W4223469120 on OpenAlexafffundabout
Jack J. Poldon, Evan C. Bentz, Neil A. Hoult

Bibliographic record

VenueStructural Concrete · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of TorontoHudbay Minerals (Canada)Queen's University
FundersCanada Foundation for InnovationTransport CanadaGovernment of Ontario
KeywordsCrackingStructural engineeringReinforcementShear (geology)StaticsBeam (structure)StiffnessShrinkageMaterials scienceYoung's modulusGeotechnical engineeringComposite materialGeologyEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The demand on the longitudinal reinforcement due to shear has been traditionally based on statics but has rarely been measured. Empirical assumptions needed for the concrete stiffness and the variability of reinforcement strain due to cracking and disturbed regions complicate these measurements, and make the use of conventional strain gauges impractical. This paper investigates the use of distributed measurements from a large reinforced concrete beam test to study the effects of disturbed regions, forces at a crack, shrinkage, and the in situ modulus of elasticity of concrete. The increased demand due to shear on the longitudinal reinforcement was observed, and the Canadian code was shown to provide an accurate upper bound to the measured strain at service loads. The measured longitudinal strains were also used to estimate the average angle of principal compressive stress, and it was observed to decrease with applied load, reaching values as low as 14° near failure.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.259
Teacher spread0.239 · 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

Citations17
Published2022
Admission routes3
Has abstractyes

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