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Record W4410006295 · doi:10.1007/s44290-025-00244-6

Comparative study of structural behavior of CFRP tubes and traditional steel for pile and column applications compliance with international codes

2025· article· en· W4410006295 on OpenAlexaboutno aff
Mahmoud El Gendy, Ibrahim El Arabi, A. El-Barbary, Mohamed Ahmed Reda Hamed

Bibliographic record

VenueDiscover Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsColumn (typography)PileCompliance (psychology)Structural engineeringMaterials scienceEngineeringForensic engineeringPsychology

Abstract

fetched live from OpenAlex

Abstract Carbon Fiber-Reinforced Polymers (CFRPs) are highly valued in structural engineering due to their exceptional strength-to-weight ratio, durability, and corrosion resistance. While the design of reinforced concrete is governed by specific building codes, CFRPs have unique design considerations. This study delves into a comparative analysis of eight prominent building codes: ACI318 (American Concrete Institute), EC2 (Eurocode 2), ECP (Egyptian Code of Practice), BS8110 (British Standard), IS456 (Indian Standard), CP65 (Singapore Standard), CSA A23.3 (Canadian Standard), and HK CP (Hong Kong Code of Practice). The focus is on circular CFRP sections under bending and axial loads, which are more complex than rectangular sections. By comparing design requirements for general properties, bending, and column provisions, this paper aims to identify significant differences in design procedures. A software tool was developed to support analysis, and its results align closely with previous studies, available well-known programs, and interaction diagrams from various codes. Key factors influencing the capacity of CFRP structural elements, such as tube thickness and concrete strength, were investigated. The validated developed software is unique in analyzing columns and laterally loaded piles using the aforementioned building codes. The interaction diagrams generated by the program based on EC2, ECP, BS8110, and HK CP showed a high degree of similarity to those available in the design aids and charts, with the Mean Absolute Percentage Error (MAPE) values of less than 5%, indicating the software's accuracy in determining the ultimate load-carrying capacity of circular sections.

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)0.002
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
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.264
Teacher spread0.241 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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