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Record W2888008617 · doi:10.14710/mkts.v24i1.17303

Pemodelan dan Analisis Perilaku Balok Beton Bertulang yang Berbeda Diameter Akibat Variasi Tata Letak Tulangannya

2018· article· en· W2888008617 on OpenAlexaboutno aff
Yohanes Laka Suku

Bibliographic record

VenueMEDIA KOMUNIKASI TEKNIK SIPIL · 2018
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsReinforcementStructural engineeringStirrupBeam (structure)Reinforced concreteDeflection (physics)StiffnessMaterials scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Analysis of the effect of the layout of reinforcement in reinforced concrete beams with different diameters to understand behavior and layout position of reinforcement produces the maximum of load capacity and ductility. Modeling and analysis using ANSYS program, the experimental test beam type OA1 and A1 from the University of Toronto (Vichio & Shim, 2004) was used as a benchmark and models which varies in layout of reinforcement. The number of models analyzed is a total of fourteen models consisting of seven models without stirrups and seven with stirrups. Beam behavior observed in the form of load capacity, deflection, ductility, stiffness and crack patterns. Results showed that: the layout of reinforcement affects the behavior of reinforced concrete beam; on the same width of reinforcedment, one layer reinforcement has greater load capacity and rigidity but smaller ductility than two layers; the layout of reinforcement in general does not affect the pattern of cracks; the collapse of the beam without stirrups is caused by the diagonal tension and the beam with stirrups by shear and rupture due to the press; the layout of reinforcement produces the largest load capacity and ductility of the largest is model OA1 and OA1,4 on the beams without stirrups and models A1 and A1,5 on beam with stirrups.

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 categoriesMeta-epidemiology (narrow)
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 score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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.

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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueMEDIA KOMUNIKASI TEKNIK SIPILSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207