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Fatigue life and behaviour of ribbed GFRP reinforced concrete beams

2024· article· en· W4396242924 on OpenAlexaff
Islam Elsayed Nagy, Alireza Asadian, Khaled Galal

Bibliographic record

VenueEngineering Structures · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsConcordia University
Fundersnot available
KeywordsFibre-reinforced plasticStructural engineeringReinforced concreteMaterials scienceComposite materialForensic engineeringEngineering

Abstract

fetched live from OpenAlex

Despite the growing adoption of glass-fibre reinforced polymer (GFRP) as an alternative to steel reinforcement, there is limited research addressing the fatigue performance of GFRP bars in reinforced concrete structures. Existing literature presents contradictory experimental data and conclusions regarding the fatigue behaviour of GFRP rebars embedded in concrete. This study investigates the fatigue life of ribbed GFRP bars embedded in concrete beams through an experimental program, considering factors such as concrete strength and fatigue stress levels. Additionally, it introduces a testing protocol utilizing a displacement-controlled scheme to conduct fatigue testing, addressing many issues associated with force-controlled fatigue testing. Furthermore, the paper discusses cracking behaviour, deflection, and slippage, providing insights into the interaction between GFRP rebars and concrete under fatigue loading. The results of this study demonstrated that ribbed GFRP bars can withstand 2 million cycles of fatigue loading at a 40% stress ratio. The obtained fatigue life exceeds findings in existing literature, emphasizing the impact of stress ratio and bar surface profile on fatigue performance.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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

Citations16
Published2024
Admission routes1
Has abstractyes

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