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Record W4200354639 · doi:10.1201/9781003076131-23

Reinforced Concrete Columns Confined by FRP Grids

2021· book-chapter· en· W4200354639 on OpenAlexaff
Murat Saatçioğlu

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFibre-reinforced plasticStructural engineeringReinforced concreteMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Experimental investigation was carried out to verify the use of fiber reinforced polymer (FRP) grids as transverse reinforcement. The emphasis was placed on concrete confinement and seismic performance. Large-scale column specimens were tested under simulated seismic loading. The column reinforcement cages consisted of ordinary steel reinforcement as longitudinal bars and fiber reinforced polymer grids as transverse reinforcement. Grid spacing, grid pattern and the volumetric ratio of grid reinforcement, as well as the level of axial load were considered as test parameters. The results indicate improved deformability of columns when confined by properly designed grids. The grids provided easy cage assembly, savings in materials, and improved performance, while eliminating the congestion of column cage. Columns reinforced with fiber reinforced polymer grids developed at least 3% drift when current design practice was followed in terms of the amount and spacing of transverse reinforcement.

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)0.000
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 score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.010
GPT teacher head0.197
Teacher spread0.188 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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