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Fatigue Retrofitting of Welded Steel Cover Plates using Pre-Stressed Carbon Fibre Reinforced Polymer Strips

2011· article· en· W2335735789 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

VenueStructural Engineering International · 2011
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRetrofittingWeldingFibre-reinforced plasticStructural engineeringSTRIPSMaterials scienceConcrete coverReinforced concreteComposite materialCarbon fiber reinforced polymerCover (algebra)EngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Past research on the use of carbon fibre reinforced polymer (CFRP) strips for the fatigue retrofitting of steel structures has shown that these materials have considerable potential for this application. Several investigations have found that this approach can be significantly improved by first pre-stressing the strips. To further explore this possibility, a study was recently undertaken with the objectives of: (a) fatigue testing steel beams with welded cover plates strengthened using pre-stressed CFRP strips and (b) employing analytical models to predict the resulting fatigue life increase. This paper summarises the main findings of this study. Specifically, it is shown that a significant fatigue life increase can be achieved with the application of pre-stressed CFRP strips to welded details, such as cover plates. This increase will be modest, however, if the introduced stress is less than the residual stress already present as a result of the welding process. The test results are predicted by a fracture mechanics model, wherein the stresses in the weld are determined by finite element analysis.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.020
GPT teacher head0.230
Teacher spread0.210 · 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