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Record W2028978343 · doi:10.1155/2013/410567

Power Consideration in a Piezoelectric Generator

2013· article· en· W2028978343 on OpenAlexafffund
Rémi Tardiveau, Frédéric Giraud, Adrian Z. Amanci, Francis Dawson, Christophe Giraud-Audine, Michel Amberg, Betty Lemaire‐Semail

Bibliographic record

VenueSmart Materials Research · 2013
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsUniversity of Toronto
FundersUniversity of Torontoİslam Tarih, Sanat ve Kültür Araştırma MerkeziInstitut national de recherche en informatique et en automatique (INRIA)
KeywordsGenerator (circuit theory)ExcitationEnergy harvestingVibrationPiezoelectricityElectricity generationPower (physics)Electric generatorAcousticsAmplitudeParticle displacementMechanical energyElectricityMaterials scienceDisplacement (psychology)Energy (signal processing)Electrical engineeringPhysicsEngineeringOptics

Abstract

fetched live from OpenAlex

A piezoelectric generator converts mechanical energy into electricity and is used in energy harvesting devices. In this paper, synchronisation conditions in regard to the excitation vibration are studied. We show that a phase shift of ninety degrees between the vibration excitation and the bender’s displacement provides the maximum power from the mechanical excitation. However, the piezoelectric material is prone to power losses; hence the bender’s displacement amplitude is optimised in order to increase the amount of power which is converted into electricity. In the paper, we use active energy harvesting to control the power flow, and all the results are achieved at a frequency of 200 Hz which is well below the generator’s resonant frequency.

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)0.001
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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.040
GPT teacher head0.295
Teacher spread0.254 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

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