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Record W2561402704 · doi:10.1115/1.4035455

Rational Damping Arrangement Design for Transmission Lines Vibrations: Analytical and Experimental Analysis

2016· article· en· W2561402704 on OpenAlexaff
Oumar Barry, Rose Long, D. C. D. Oguamanam

Bibliographic record

VenueJournal of Dynamic Systems Measurement and Control · 2016
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsDamperElectric power transmissionVibrationStructural engineeringCounterweightConductorDamping torqueOverhead (engineering)TowerVibration controlEngineeringTransmission towerTransmission (telecommunications)Tuned mass damperControl theory (sociology)Damping ratioPhysicsComputer scienceVoltageAcousticsElectrical engineeringMaterials scienceControl (management)

Abstract

fetched live from OpenAlex

The control of overhead transmission lines vibrations is achieved by Stockbridge dampers. However, the effectiveness of the damper is significantly dependent on its location on the conductor. This paper studies the arrangement of Stockbridge dampers on power lines vibrations using both analytical and experimental approaches. An explicit expression of the loop length is presented for the first time. This expression is used to determine the optimal damper location based on a rational approach. The effectiveness of the proposed approach is validated numerically and experimentally. The results show very good agreement and indicate that Stockbridge dampers are more effective for asymmetrical damping arrangement with the bigger counterweight oriented toward the tower.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.242
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations7
Published2016
Admission routes1
Has abstractyes

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