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Record W4379054163 · doi:10.5267/j.esm.2023.5.003

Experimental analysis of spliced joint connections in GFRP short column

2023· article· en· W4379054163 on OpenAlexvenueno aff
M. J. Srujan, Seelam Srikanth

Bibliographic record

VenueEngineering Solid Mechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsFlangeFibre-reinforced plasticStructural engineeringJoint (building)StiffnessMaterials scienceColumn (typography)Bearing capacityConnection (principal bundle)Compressive strengthBearing (navigation)Composite materialEngineeringComputer science

Abstract

fetched live from OpenAlex

This paper describes an experimental program developed to investigate non-bearing spliced composite short column connections made of Glass Fiber Reinforced Polymer (GFRP) that are subjected to axial loading. This study provides aspects such as the load-bearing capacity of the connection, failure modes, load distribution in the connection, displacement in the joint, stiffness, and compressive strength. The design of the joint in this study that connects two 350mm GFRP H-sections to form a short column connection is based on euro codes BS EN 1990 and BS EN 1991, which are used to design steel splicing connections for beams and columns. Four design specifications models are made depending on the positioning of the cover plates in the inner flange, outer flange, and web region of the H-sections to examine the requirement of a specific cover plate, and the H-sections are bolted to each other using M8 8.8 grade steel bolts. The samples tested in this study indicated a dominant failure in the flange region, with model-4 providing 92.83% compressive strength when compared to an uncut GFRP short column.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.251
Teacher spread0.233 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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Same venueEngineering Solid MechanicsSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207