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Record W2094885666 · doi:10.7734/coseik.2014.27.4.305

Comparison and Evaluation of Current Strut-and-Tie Design Provisions for Reinforced Concrete Deep Beams

2014· article· en· W2094885666 on OpenAlexaboutno aff
김 진우, Kim Jin Woo, 홍 성걸, Sung‐Gul Hong, 이 영학, Lee Young Hak, 김 희철, 김 대진, Kim Dae-Jin

Bibliographic record

VenueJournal of the Computational Structural Engineering Institute of Korea · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsTrussStructural engineeringReinforced concreteBeam (structure)Shear (geology)Shear strength (soil)EngineeringComputer scienceGeologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The current American Concrete Institute(ACI), Canadian Standard Associate(CSA) and CEB-FIP Model Code 2010 provisions on the shear strength of a simply supported deep beam suggest that deep beams should be designed using the strut-and-tie model. Although this is a useful methodology to design members in disturbed regions, the quality of the design is highly dependent on the truss model that designers create. However, Hong et al. derived the shear strength equations of reinforced concrete deep beams. This thesis investigates the validity of the current ACI, CSA and CEB-FIP code provisions on the shear strength of simply supported reinforced concrete deep beams by comparing them with the shear strength equations proposed by Hong et al. The comparison shows that all of these code provisions provide reasonable estimates on the shear strength of concrete deep beam members and the selection of an internal truss model plays an important role on the estimation of shear strength.

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)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.296
Teacher spread0.260 · 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 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Computational Structural Engineering Institute of KoreaSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207