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Flexural strengthening of one-way reinforced concrete slabs using near surface-mounted BFRP bars

2024· article· en· W4390959494 on OpenAlexaff
Omar Aljidda, Wael Alnahhal

Bibliographic record

VenueEngineering Structures · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversité Laval
FundersQatar National LibraryQingdao University of Science and TechnologyQatar University
KeywordsFlexural strengthReinforcementMaterials scienceComposite materialDuctility (Earth science)CrackingYield (engineering)Structural engineeringEpoxyBeam (structure)CreepEngineering

Abstract

fetched live from OpenAlex

This study examines the flexural behavior of reinforced concrete (RC) one-way slabs strengthened with near-surface mounted (NSM) basalt fiber-reinforced polymer (BFRP) bars. Ten RC slabs were subjected to four-point loading until failure. Various parameters including the steel reinforcement ratio (0.48and 0.95%), the NSM-BFRP reinforcement ratio (0.17, 0.25, and 0.35%), and two types of epoxy adhesives (Sikadur-30 and NSM-Gel) were investigated. The experimental results demonstrated the remarkable efficacy of the NSM-BFRP bars in enhancing the flexural performance of the strengthened slabs, especially those with lower steel reinforcement ratios. Compared to the control slabs, the ultimate loads were increased by 51‐123% and 21‐44% for slabs with 0.48 and 0.95% steel reinforcement ratios, respectively, while the ductility indices were increased by 10‐53% and 29‐79%. The type of the epoxy adhesive used had minimal impact on the flexural behavior of the strengthened slabs. Failure primarily occurred due to steel yielding followed by the rupture of the NSM-BFRP bars or by concrete crushing, depending on the reinforcement ratio provided. The cracking, yield, and ultimate loads of the strengthened slabs were predicted using the formulations of ACI 440.2R [3] guideline. Good agreement between the predicted and the experimental results were obtained, with ACI formulations being on the conservative side.

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 score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
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)0.0000.000

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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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