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Record W3009878231 · doi:10.1016/j.jestch.2020.02.006

State-of-the-art of prefabricated FRP composite jackets for structural repair

2020· article· en· W3009878231 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEngineering Science and Technology an International Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsQueen's University
FundersAustralian GovernmentUniversity of South AlabamaWest Virginia University
KeywordsFibre-reinforced plasticDurabilityComposite numberBridge (graph theory)Structural engineeringPileEngineeringConstruction engineeringComputer scienceMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Fibre reinforced polymer (FRP) composites have attracted significant attention in repairing existing and deteriorating structures since the traditional rehabilitation techniques have several limitations in terms of durability, self-weight and complex installation process. Prefabricated FRP composite jackets are the preferred solution in repairing bridge piles located both underwater and above the waterline as they can be easily placed around the damaged pile to form a robust single-piece repair system. The structural continuity of the jacket in such a repair system is critical for effectively utilising its maximum strength. This study presents an extensive review of the current practices and new opportunities for using prefabricated composite jackets for structural repair. Important design considerations to effectively utilise prefabricated FRP composite jackets in repairing structures are presented and analysed. The review also identifies the challenges and highlights the future directions of research to increase the acceptance and use of emerging composite repair systems.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.268

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 science0.0010.000
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 head0.008
GPT teacher head0.237
Teacher spread0.229 · 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