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Record W4409799803 · doi:10.11159/icsect25.178

Numerical Simulation of the Pullout Behavior of Steel Fiber Composite Bars (SFCB) Embedded in Concrete

2025· article· en· W4409799803 on OpenAlexvenueno aff
Haya A. Zuaiter, Doha ElMaoued, Mohammad AlHamaydeh, Mohamed Elkafrawy

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
FundersAmerican University of Sharjah
KeywordsMaterials scienceComposite numberComposite materialFiberStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Steel fiber composite bars (SFCB) are a promising alternative to steel and fiber-reinforced polymer (FRP) reinforcement due to their high elastic modulus and tensile strength, impressive ductility, and outstanding corrosion resistance.This research investigates the impact of increasing the diameter of the inner steel bar of a glass SFCB on the bond stress between the bar and the surrounding concrete.Abaqus finite element software simulates the pullout behavior between glass SFCB and normal-strength concrete.Results of the FE models were compared with experimental results in terms of crack patterns and bond stresses.The FE model results correlated well with the experimental results having a 0.54% error in the ultimate bond stress and a 0.67% error in the corresponding slip.A parametric study is conducted in which the diameter of the inner steel core is increased while all other material properties and boundary conditions remain constant.The composite material's behavior is analyzed accounting for the interactions between the steel bar, glass FRP (GFRP) cover, and surrounding concrete.Notably, increasing the diameter of the inner steel bar from 8.6 mm to 12.6 mm increases the bond stress from 20.7 MPa to 25.1 MPa and increases the ultimate slip from 1.17 mm to 1.57 mm.The increase in ultimate slip is due to the rise in bond stress which in turn is due to a decrease in the radial confinement stress between the SFCB and the surrounding concrete.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.696

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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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.

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
Published2025
Admission routes1
Has abstractyes

Explore more

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