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Record W2289065975 · doi:10.1109/nemo.2015.7415040

Closed-form optimization of multi-transmitter wireless power transfer systems

2015· article· en· W2289065975 on OpenAlexaff
Hans-Dieter Lang, Alon Ludwig, Costas D. Sarris

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransmitterWireless power transferComputer scienceNetwork topologyWirelessConvex optimizationMaximum power transfer theoremTopology (electrical circuits)Quadratic equationPower (physics)Regular polygonMathematical optimizationElectronic engineeringMathematicsElectrical engineeringChannel (broadcasting)EngineeringTelecommunicationsComputer networkPhysics

Abstract

fetched live from OpenAlex

While the physical limitations of single-transmitter wireless power transfer (WPT) systems are well-known, systems with multiple transmitters prove difficult to optimize, in order to find their maximum achievable performance. The optimization process leading to a convex quadratic program is outlined and closed-form expressions solving that problem analytically are reviewed. Comparison of results obtained from these formulations and others aquired from analytical modeling show perfect agreement; thus, it is verified that the formulations are equivalent. Hence, they offer a compact and insightful analytical framework for the design and optimization of emerging multi-transmitter WPT topologies.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score0.980

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 head0.020
GPT teacher head0.212
Teacher spread0.192 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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