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Record W4404009289 · doi:10.1061/jccof2.cceng-4786

Seismic Performance Assessment of GFRP-RC Circular Columns under High Torsion Combined with Bending and Shear Cyclic Loading

2024· article· en· W4404009289 on OpenAlexaff
Yasser M. Selmy, Amr E. Abdallah, Ehab El-Salakawy

Bibliographic record

VenueJournal of Composites for Construction · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMaterials scienceFibre-reinforced plasticTorsion (gastropod)Structural engineeringComposite materialShear (geology)BendingReinforced concreteEngineering

Abstract

fetched live from OpenAlex

This study presents the results of an investigation into the seismic performance of six large-scale concrete circular columns reinforced with glass fiber–reinforced polymer (GFRP) reinforcement. Among these columns, one underwent concentric reversed cyclic lateral loading, causing bending and shear, while the remaining five columns experienced eccentric cyclic lateral loading, causing additional torsional stresses. The test variables included the torsion-to-bending moment ratio, transverse and longitudinal reinforcement ratios, and concrete compressive strength. The test results indicated that the concurrent cyclic torsion and lateral drift reversals significantly altered the behavior of concrete members in terms of mode of failure, lateral load resistance, drift capacity, and energy dissipation. It was found that adequately confined columns exhibited a notable reduction in concrete core deterioration, thereby preventing the decline in both bending and torsional strength. Furthermore, the paper examined the validity of the North American design provisions predicting the torsional strength of GFRP-reinforced concrete members subjected to combined seismic loading. Amendments to the GFRP tensile stress limits specified in these provisions were introduced, yielding better and safer predictions for the torque capacity of the tested columns.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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 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

Citations6
Published2024
Admission routes1
Has abstractyes

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