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Influence of Steel Fibers and Headed Bars on the Serviceability of High-Strength Concrete Corbels

2012· article· en· W1993906694 on OpenAlexaff
Jun-Mo Yang, Joo-Ha Lee, Young‐Soo Yoon, William D. Cook, Denis Mitchell

Bibliographic record

VenueJournal of Structural Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsMcGill University
Fundersnot available
KeywordsServiceability (structure)Materials scienceReinforcementStructural engineeringComposite materialWeldingStiffnessDuctility (Earth science)DurabilityTension (geology)Ultimate tensile strengthEngineering

Abstract

fetched live from OpenAlex

Vertical loading tests are reported for six double-sided, high-strength concrete corbel specimens. The primary variables of the investigation were the percentage of steel fibers and the anchorage method of the main tension tie. The test results indicated that performance in terms of load-carrying capacities, stiffness, ductility, and crack width was improved, as the steel fibers were added and the percentage of steel fibers was increased. The corbel specimens with headed bars used as the main tension-tie reinforcement showed superior load-carrying capacities, stiffness, and ductility compared with the corbel specimens in which the main tension ties were anchored by welding to the transverse bars. From the test results, it is expected that the load-carrying capacities, serviceability, and durability of high-strength concrete corbels would be improved by using steel fibers and headed bars. Experimental results presented were also compared with various prediction models.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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

Citations22
Published2012
Admission routes1
Has abstractyes

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