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Record W1995099559 · doi:10.1061/9780784413357.035

Fatigue Retrofitting of Web Stiffeners in Steel Bridges Using Pultruded FRP Sections

2014· article· en· W1995099559 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueStructures Congress 2014 · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Waterloo
FundersMinistère des Transports
KeywordsRetrofittingFibre-reinforced plasticStructural engineeringDeckPultrusionFinite element methodWeldingMaterials scienceStress (linguistics)GirderComposite materialEngineering

Abstract

fetched live from OpenAlex

A new retrofit method for the distortion-induced fatigue problem in steel bridges by using adhesively-bonded FRP angles is developed in this paper. This retrofit method is relatively cheap and easy to use and does not require deck removal or any other modification to the steel girder. The FRP retrofitted specimens are found to have significantly longer fatigue lives than as-welded specimens and specimens repaired by means of two other conventional repair methods. The hot-spot stress method is used to quantify the effectiveness of the proposed retrofit method. A coarse finite element (FE) analysis is used to predict the effectiveness of the proposed retrofit methods in terms of the reduction in the hot spot stress value, and analytically calculated hot-spot stresses are validated with directly measured values. The effects of a number of the varied geometrical and mechanical parameters on the efficiency of the proposed retrofit are then studied using an FE analysis and recommendations are made to improve the efficiency of this FRP-based retrofit method.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
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 head0.019
GPT teacher head0.256
Teacher spread0.238 · 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