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Record W4323041744 · doi:10.18280/mmep.100119

A Comprehensive Design of Audio-Modulated Dual Resonant Solid State Tesla Coil: Mechanical and Electrical Aspects

2023· article· en· W4323041744 on OpenAlexvenueno aff
Mohammad A. Obeidat, Mohammad Nehad, Khaled A. Mahafzah, Ayman Mansour

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSolid-stateElectromagnetic coilDual (grammatical number)State (computer science)Materials scienceAcousticsElectrical engineeringComputer scienceEngineeringPhysicsEngineering physicsArt

Abstract

fetched live from OpenAlex

An Audio modulated Tesla coil is a high voltage, high frequency transformer.In this paper, a comprehensive design of Audio-Modulated Dual Resonant Solid State Tesla Coil (AUM-DRSSTC) is explored.Both mechanical and electrical design specifications of AUM-DRSSTC are investigated in detail.The geometrical mechanical model is derived and built based on mathematical equations.After that, the paper proposes the electrical design for modulating the audio signal, hence, transferring the energy from primary coil to the secondary coil.The methodology of this paper is unique in high voltage generating system engineering.The results of the introduced design are practically tested in the lab.A 15 kV, 200 kHz prototype is built to prove the design aspects.Due to the safety regulations in the research lab inside the university, the electrical board has been tested at low DC input voltage 15 V.

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 communication0.0000.000
Open science0.0000.000
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 head0.032
GPT teacher head0.225
Teacher spread0.193 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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