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Record W1507621161 · doi:10.1109/wpt.2015.7140176

A planar positioning-free magnetically-coupled resonant wireless power transfer

2015· article· en· W1507621161 on OpenAlexafffund
Farid Jolani, Yiqiang Yu, Zhizhang Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsWireless power transferResonatorPlanar arrayPlanarTransmitterMaximum power transfer theoremElectromagnetic coilAcousticsElectrical engineeringPower (physics)PhysicsElectronic engineeringMaterials scienceOptoelectronicsEngineeringComputer scienceOptics

Abstract

fetched live from OpenAlex

A novel magnetically-coupled resonant wireless power transfer (MCR-WPT) system using an array of printed spiral coil (PSC) resonators is presented to expand the receiving area. The resonator array is excited with a single planar driving loop to yield uniform magnetic field distribution at the receiver plane. First, the performance of a conventional transmitter coil array consisting of one transmitting resonator and multiple repeaters without frequency tracking is investigated. Then the performance of the proposed PSC resonator array with novel feed strategy is demonstrated. The results show the proposed MCR-WPT array system is able to provide consistent transfer efficiency when the receiver is axially misaligned with the transmitter. The measurement results are compared with the conventional planar MCR-WPT array and reveal that that with the proposed design, the transfer efficiency of the planar MCR-WPT system can be increased from 2.1% to 65.8% in the misalignment region.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.193
Teacher spread0.182 · 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 designBench or experimental
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

Citations19
Published2015
Admission routes2
Has abstractyes

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