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Record W2141006816 · doi:10.1109/08ias.2008.128

Dynamic Induction Charging of Particles with Finite Conductivity

2008· article· en· W2141006816 on OpenAlexaff
Deying Yu, G.S.P. Castle, Kazimierz Adamiak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsConstant (computer programming)PermittivityConductivityFinite element methodRelaxation (psychology)Thermal conductionTime constantElectrodeMaterials scienceMechanicsParticle (ecology)Transient (computer programming)DielectricCondensed matter physicsPhysicsComposite materialElectrical engineeringThermodynamicsComputer scienceEngineeringOptoelectronicsQuantum mechanics

Abstract

fetched live from OpenAlex

Despite the common belief that in the process of induction charging the charging time constant and the relaxation time constant are equal, there is no proof that these parameters are related at all. The purpose of this paper is to determine the actual induction charging time constant for practical types of particles having both finite conductivity and permittivity. All investigations were based on numerical simulations done for idealized geometric models of the problem. The model was developed for the transient case and solved by using the COMSOL commercial software, which is based on the Finite Element Method. Spherical and rough particles with various contact areas with the grounded electrode were considered. The surface conduction of the particle was neglected. The effect of the particle contact area, conductivity, and permittivity on the actual charging time constant was investigated and the results were compared with that predicted by the classic relaxation time constant as defined by the material properties. It was found that the actual time constant is not equal to the relaxation time constant but is directly affected by the value of the contact area between the particle and ground electrode.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.256

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 head0.226
Teacher spread0.206 · 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 designObservational
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

Citations4
Published2008
Admission routes1
Has abstractyes

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