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Record W2148980496 · doi:10.1139/l08-040

Cyclic performance of frames with prestressed steel–concrete composite beams

2008· article· en· W2148980496 on OpenAlexvenueno aff
Weichen Xue, Kun Li, Renguang Zheng, Liang Li

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStructural engineeringComposite numberBeam (structure)StiffnessMaterials scienceDissipationDeformation (meteorology)Ductility (Earth science)Composite materialEngineeringCreepPhysics

Abstract

fetched live from OpenAlex

This paper presents a study of the cyclic performance of moment-resisting frames with prestressed steel–concrete composite beams subjected to cyclic displacement reversals. The failure patterns, failure mechanism, hysteretic model, ductility, energy dissipation capacity, stiffness degradation, and deformation-restoring capacity of two composite frames are discussed. Larger slip could be observed along the beam span of the frame with the common composite beam in comparison with the prestressed composite beam. A four-linear hysteretic model with descending branches and two pinching pivot points is proposed for the two composite frames. Tests show that both the test frames failed in a beam side-sway mechanism within the plane of the frame, and the frame with the prestressed composite beam develops relatively high deformation restoring capacity. The applied prestressing in the composite beam has a small contribution to cyclic behavior of the composite frame. Studies also show that more energy is dissipated by the frame with the prestressed composite beam than that with the common composite beam.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.730

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 head0.005
GPT teacher head0.153
Teacher spread0.148 · 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 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

Citations1
Published2008
Admission routes1
Has abstractyes

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