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Record W2000971684 · doi:10.1088/0953-2048/25/1/014001

Assessment of alternative design schemes to reduce the edge losses in HTS power transmission cables made of coated conductors

2011· article· en· W2000971684 on OpenAlexaff
Majid Siahrang, Frédéric Sirois, Doan N. Nguyen, S.P. Ashworth

Bibliographic record

VenueSuperconductor Science and Technology · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceElectrical conductorEnhanced Data Rates for GSM EvolutionPower (physics)Power transmissionSuperconductivityTransmission (telecommunications)Work (physics)Layer (electronics)Reduction (mathematics)Magnetic fieldEngineering physicsNuclear engineeringComputer scienceComposite materialMechanical engineeringCondensed matter physicsTelecommunicationsPhysicsEngineering

Abstract

fetched live from OpenAlex

In this paper, we investigate the effectiveness of alternative designs to reduce the AC losses of high temperature superconducting (HTS) power transmission cables. The idea behind these designs is to undermine the edge effect, which is one of the main factors contributing to AC losses in HTS power cables made of coated tapes. The edge effect, which arises from the presence of gaps between the tapes, results in large normal components of magnetic field near the edges of the tapes and in turns leads to a current distribution with higher density near the edges. To perform our investigation we use a numerical technique developed in our previous work which allows us to consider the helical configuration of the tapes. Through numerical simulations we assess the effectiveness of two overlapped designs, i.e. a cyclic overlapped design and an anticyclic overlapped design, in reduction of AC losses in single layer HTS power cables made of coated tapes. Simulation results show that AC losses can be reduced by about 70% as compared with a typical single layer cable.

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)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.290
Teacher spread0.250 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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