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Record W3012344989 · doi:10.1109/wow45936.2019.9030620

Quarter Wavelength Surface Structures for Improved Operation in Unipolar Capacitive Power Transfer

2019· article· en· W3012344989 on OpenAlexaboutno aff
Donald Chaney, Charles A. Robinson, C. W. Van Neste

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Capacitive sensingWavelengthMaterials scienceTransfer (computing)Power (physics)Maximum power transfer theoremElectrical engineeringOptoelectronicsOpticsComputer sciencePhysicsEngineering

Abstract

fetched live from OpenAlex

Unipolar capacitive power transfer is a unique technique that enables power transmission over single conducting surfaces. The counter electrode is generally an earth ground that is physically isolated from users. This improves safety and alleviates many short-circuiting issues that a bipolar (two plate) capacitive system might encounter. Recent work has shown that by designing the unipolar capacitive receiver to operate in a standing wave resonance mode, surface voltages can be significantly lower with greater power transfer capacity and efficiency. One major challenge to this approach is the influence of surrounding objects which detune the receiver when in close proximity - ceasing power transfer to the receiver's attached load. Here we present a method to mitigate the detuning effect by incorporating a network of quarter wave structures under the power transfer surface. The quarter wave structures create a “wave-shaped” electric field distribution that is confined to a 0.3 m distance surrounding the surface. This greatly reduces the open-ended field emissions while lessening the detuning effect of the receiver from nearby objects. The efficiency and power transfer of the system is analyzed based on the operation of a 10 W LED filament lamp. The effects on the output parameters of the power supply in conjunction with the delivered power as the receiver is spatially varied is explored.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.751

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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 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

Citations3
Published2019
Admission routes1
Has abstractyes

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