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Record W2144255837 · doi:10.1049/iet-gtd:20080033

Numerical investigations of a new thermal de-icing method for overhead conductors based on high current impulses

2008· article· en· W2144255837 on OpenAlexafffund
Zs. Péter, C. Volat, M. Farzaneh, László I. Kiss

Bibliographic record

VenueIET Generation Transmission & Distribution · 2008
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaHydro-QuébecUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConductorIcingElectrical conductorJoule heatingMechanicsImpulse (physics)Current (fluid)ThermalMaterials scienceElectrical engineeringEngineeringMeteorologyPhysicsComposite materialClassical mechanics

Abstract

fetched live from OpenAlex

The theoretical background of a thermal de-icing method for overhead bare conductors subjected to ice accumulation is presented. The proposed thermal method is based on Joule effect but uses current impulses superposed onto the AC nominal current of the conductor whose perimeter is half-covered by a semi-elliptic ice sleeve. The purpose is to study the influence of environmental parameters on the shedding time obtained. For theoretical investigations, a specific numerical model using finite elements, finite volumes and explicit finite differences was developed. Several numerical simulations were carried out in order to study the influence of characteristic environmental parameters such as air speed, air temperature and ice thickness on ice shedding time, number of required current impulses as well as temperature distribution along the ice/conductor composite. The results obtained showed that the use of current impulses allows the confinement of the Joule effect heat to the ice/conductor interface. By decreasing the current impulse duration or increasing the current impulse magnitude, a more efficient heat confinement can be obtained at the ice/conductor interface. Also, the results showed than this method is not sensitive to wind speed and that shedding time is decreased with thicker ice sleeves.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.633

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 head0.047
GPT teacher head0.291
Teacher spread0.243 · 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.

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

Citations27
Published2008
Admission routes2
Has abstractyes

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