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Record W2152976396 · doi:10.1109/tpwrd.2013.2291363

Prediction of Aeolian Vibration on Transmission-Line Conductors Using a Nonlinear Time History Model—Part II: Conductor and Damper Model

2014· article· en· W2152976396 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

VenueIEEE Transactions on Power Delivery · 2014
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsDamperConductorTransmission lineStructural engineeringVibrationElectric power transmissionElectrical conductorNonlinear systemEngineeringStiffnessSpan (engineering)Control theory (sociology)AcousticsPhysicsComputer scienceElectrical engineeringMaterials science

Abstract

fetched live from OpenAlex

Various numerical tools have been developed to predict the level of aeolian vibrations for a damped span of transmission-line conductors. In part I of this study, nonlinear time history models of two types of transmission-line dampers were developed. In this paper, a model for the complete conductor-damper system is presented. When combined with empirical equations for wind power input and conductor self-damping using the Energy Balance Principle, the direct integration time history model proposed allows the prediction of the vibration amplitudes expected on a damped span. The amplitudes predicted by the model compare well to experimental data sets available in the literature. Since the damper is modelled from its mechanical properties of geometry, mass, stiffness, and damping, the optimization of a conductor-damper system can be done easily with this model, without additional experimental tests. A sensitivity analysis is conducted to demonstrate the capabilities of the model.

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: none
Teacher disagreement score0.728
Threshold uncertainty score0.950

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 head0.027
GPT teacher head0.206
Teacher spread0.179 · 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