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Record W4379536916 · doi:10.1111/ffe.14064

Fretting fatigue tests and microstructure analysis of bridge stay cable wires

2023· article· en· W4379536916 on OpenAlexaff
Ali Chehrazi, Wanhua Liang, Nazmul Huda, Scott Walbridge

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFrettingStructural engineeringMicrostructureBridge (graph theory)GalvanizationMaterials scienceSaddleEngineeringComposite material

Abstract

fetched live from OpenAlex

Abstract Saddle systems are a popular method for supporting the cables at the pylons of cable‐stayed bridges. Fretting fatigue failure of bridge stay cables is a major design consideration for saddle systems. Current design provisions require large‐scale tests of these anchoring systems. However, such tests are costly and time‐consuming. With this in mind, the current paper presents a small‐scale fretting fatigue setup to evaluate the fretting fatigue behavior of bridge stay cable wires at saddle supports. In this paper, fretting tests are conducted on bare and galvanized wires. Hourglass samples are then used to evaluate the material properties and plain fatigue performance of the studied wires. Finally, the microstructure of the wires is evaluated, and the influence of defects on the fretting fatigue life of the wires is discussed.

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 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 score0.479
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.247
Teacher spread0.231 · 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 teacher head, not a consensus.

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

Citations10
Published2023
Admission routes1
Has abstractyes

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