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Record W4413515138 · doi:10.1139/cjce-2024-0599

Fatigue performance of externally post-tensioned steel–concrete composite girders

2025· article· en· W4413515138 on OpenAlexvenueno aff
Fahad Alsharari, Ayman El‐Zohairy, Hani Salim

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGirderStructural engineeringComposite numberMaterials scienceEngineeringForensic engineeringComposite material

Abstract

fetched live from OpenAlex

Understanding the fatigue behavior of retrofitted beams in bridge structures is vital. The effects of pre-fatigue conditions on the efficacy of retrofitting tend to be overlooked. In this paper, five specimens were experimentally tested under fatigue. The effects of external retrofitting on the cyclic crack patterns on the concrete flanges, cyclic incremental deformations, and strains were investigated with various pre-fatigue conditions. The pre-fatigue conditions included exposure to outdoor environmental changes, plastic deformations, and prior cyclic loading. The results showed that external PT enhanced the performance of the individual components of the composite specimens, which improved the overall fatigue performance of the strengthened specimens. However, the strengthened specimens experienced longitudinal fatigue cracks in the concrete flanges because of post-tensioning. The pre-damage conditions due to prior cyclic loading and environmental changes caused greater damage in concrete around the studs relative to the plastically pre-deformed strengthened specimen and led to more incremental deformations and strains.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.000
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 head0.005
GPT teacher head0.177
Teacher spread0.172 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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