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Power Estimation for Piezoelectric Energy Harvesters in Flexure Mode with Large Displacement Amplitude

2013· article· en· W1997129800 on OpenAlexaff
Motoaki Hara, Lê Văn Minh, Hiroyuki Oguchi, Hiroki Kuwano

Bibliographic record

VenueJournal of Physics Conference Series · 2013
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsHatch (Canada)
FundersMinistry of Education, Science and Technology
KeywordsAmplitudePiezoelectricityEnergy harvestingParticle displacementPower (physics)Displacement (psychology)Control theory (sociology)AcousticsEnergy (signal processing)CantileverRigidity (electromagnetism)Power functionMechanical energyMathematical analysisPhysicsMathematicsEngineeringComputer scienceStructural engineeringStatisticsOptics

Abstract

fetched live from OpenAlex

We propose a new method to estimate the output power from piezoelectric energy harvesters using flexure mode of the cantilever. In the energy harvester, displacement amplitude is too large for Bernoulli-Euler hypothesis to hold true. Hence, it is not easy to derive a theoretical solution of output power. In this study, applying the correction coefficient which is a function of flexure rigidity to a conventional theoretical solution, simple equation to estimate the output power was derived. This equation was applied to design a practical (K,Na)NbO3 based energy harvester. Measured output from the harvester was in good agreement with the calculated value.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score0.556

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 communication0.0000.001
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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 designTheoretical or conceptual
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

Citations5
Published2013
Admission routes1
Has abstractyes

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