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Record W4412899740 · doi:10.3934/matersci.2025030

Flexural capacity of stainless-steel reinforced-concrete elements

2025· article· en· W4412899740 on OpenAlexaff
Mokhtar A. Khalifa, Maged A. Youssef, Mohamed Monir Ajjan Alhadid

Bibliographic record

VenueAIMS Materials Science · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsFlexural strengthMaterials scienceStructural engineeringComposite materialReinforced concreteEngineering

Abstract

fetched live from OpenAlex

Stainless steel (SS) is increasingly utilized in construction due to its robust strength and exceptional corrosion resistance. However, the lack of a defined yield point for SS introduces challenges in accurately calculating the moment of resistance for SS-reinforced concrete (RC) sections. To tackle this issue, a combined experimental-numerical study was conducted to pinpoint the stress in SS rebars that correlates with the moment of resistance of SS RC sections. This study tested four beams and four columns using two types of stainless steel: Austenitic (316 LN) and Duplex (2205). Following the experimental phase, a sectional analysis model was developed, validated through experimentation, and employed in a detailed parametric study. This research led to the creation of formulas that enable engineers to predict the moment of resistance for SS RC sections more precisely than current methods allow.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.236
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 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

Citations2
Published2025
Admission routes1
Has abstractyes

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