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Record W4386126688 · doi:10.32920/24026694.v1

GFRP Bars Anchorage Resistance in a GFRP-Reinforced Concrete Bridge Barrier

2023· preprint· en· W4386126688 on OpenAlexafffundabout
Michael Rostami, Khaled Sennah, Saman Hedjazi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsToronto Metropolitan University
FundersPultrall
KeywordsFibre-reinforced plasticStructural engineeringDeckBridge deckBridge (graph theory)Bending momentEngineeringFinite element methodJoint (building)BendingBent molecular geometryMaterials science

Abstract

fetched live from OpenAlex

<p>In the present paper, experimental and numerical investigations were conducted on concrete bridge barriers utilizing glass fiber reinforced polymer (GFRP) bars with a hook at their ends. Implementation of these hooked bars instead of the bent bars or headed-end bars in the bridge barriers presented in the Canadian Highway Bridge Design Code (CHBDC) was investigated on American Association for State Highway and Transportation Officials (AASHTO) test level 5 (TL-5) concrete bridge barriers. This research aimed to reach a cost effective and safe anchorage method for GFRP bars at the barrier–deck junction, compared to the conventional bend bars or headed-end bars. Therefore, an experimental program was developed and performed to qualify the use of the recently-developed, small radius hooked bars at the barrier–deck junction. The experimental findings were compared with the design factored applied transverse load specified in CHBDC for the design of the barrier–deck junction as well as factored applied bending moment obtained at the barrier–deck junction using a recently-conducted finite-element modeling. Satisfactory behavior for the developed hooked GFRP bars as well as their anchorage resistance was established and a reasonable factor of safety in design of barrier–deck joint was achieved.</p>

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.249
Teacher spread0.226 · 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 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

Citations0
Published2023
Admission routes3
Has abstractyes

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