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Record W4414051619 · doi:10.1016/j.istruc.2025.110136

Strengthening reinforced concrete columns using near-surface-mounted steel wire reinforcement: Experimental and numerical investigation

2025· article· en· W4414051619 on OpenAlexaff
Ahmed Hamoda, Ramy I. Shahin, Mizan Ahmed, Aref A. Abadel, Khaled Sennah, Hussam Alghamdi

Bibliographic record

VenueStructures · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsToronto Metropolitan University
FundersKing Saud UniversityKafrelsheikh University
KeywordsRetrofittingReinforcementBrittlenessReinforced concreteDiagonalDurability

Abstract

fetched live from OpenAlex

Strengthening of reinforced concrete (RC) columns may be required to facilitate additional load-carrying capacity or for retrofitting purposes. However, traditional strengthening techniques, such as FRP confinement is prone to brittle failure and exhibits durability issues whereas steel/concrete jacketing increases column cross-section and weight. This study explores an innovative strengthening method for RC columns using near-surface-mounted (NSM) high-strength steel wires to enhance confinement. Experimental tests were conducted on eight RC columns under axial compression, evaluating various reinforcement configurations, namely horizontal wires, combined horizontal-diagonal wires, and embedded-end anchorage. The results showed the load capacity of the columns increased by 38–65 %, and energy absorption by 175–404 %. Columns strengthened with combined horizontal and diagonal reinforcement showed better structural performance than other configurations. Numerical simulations are also carried out using Abaqus and validated against the experimental findings.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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