MétaCan
Menu
Back to cohort
Record W2575986453 · doi:10.1504/ijstructe.2017.081670

Assessment of damper performance in controlling cable vibrations using a reliability-based framework

2017· article· en· W2575986453 on OpenAlex
Seyed Ali Mohammadi, Shaohong Cheng, Faouzi Ghrib

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

VenueInternational Journal of Structural Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsDamperStructural engineeringReliability (semiconductor)VibrationEngineeringReliability engineeringComputer scienceAcousticsPhysics

Abstract

fetched live from OpenAlex

Owing to their long flexible nature and low intrinsic damping, bridge stay cables are prone to various types of wind-induced vibrations, among which the rain-wind-induced vibration is most frequently observed on site. External dampers are widely used to control such unfavourable cable oscillations and their effectiveness in suppressing large-amplitude cable vibrations was addressed in many studies using deterministic approaches. However, the mechanical and/or physical properties of cables and the attached dampers could not only deviate from their respective nominal design values at a given design point, but also vary considerably during the lifetime of a cable-stayed bridge and thus affect damper efficiency. Hence, for a realistic damper performance assessment, these uncertainties should be taken into account. The objective of this paper is to present a time-variant reliability-based framework model to assess how uncertainties in the structural parameters of a cable-damper system would influence the time specific reliability performance of an external damper yielded from the current design practice.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.582

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 head0.011
GPT teacher head0.288
Teacher spread0.277 · 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