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Record W1980205618 · doi:10.1177/1045389x14538540

Modeling, fabrication, and experimental validation of hybrid piezo-magnetostrictive and piezomagnetic energy harvesting units

2014· article· en· W1980205618 on OpenAlexafffund
Mohammed Ibrahim, Armaghan Salehian

Bibliographic record

VenueJournal of Intelligent Material Systems and Structures · 2014
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Waterloo
KeywordsEnergy harvestingMagnetostrictionPiezoelectricityVoltageBandwidth (computing)FabricationEnergy (signal processing)AcousticsMaterials sciencePower (physics)EngineeringElectrical engineeringElectronic engineeringMagnetic fieldPhysicsTelecommunications

Abstract

fetched live from OpenAlex

As sources of energy are becoming more scarce and expensive, energy harvesting technologies that convert ambient energy to electrical energy are receiving more global interest. Proposed in this article are two hybrid energy harvesters that each employs a combination of piezoelectric (PZT), magnetostrictive (MSM), and electromagnetic technologies. Harvesters employ spiral geometries to allow smaller natural frequencies compared to a straight beam. In particular, the hybrid technology that uses piezoelectric and magnetostrictive has shown significant improvement in the frequency bandwidth of the device. The two harvesters are fabricated, modeled, and tested for their voltage, power, and displacement outputs. The test results are shown to be in good agreement with those obtained from the model.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.211
Teacher spread0.198 · 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 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

Citations20
Published2014
Admission routes2
Has abstractyes

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Same venueJournal of Intelligent Material Systems and StructuresSame topicInnovative Energy Harvesting TechnologiesFrench-language works237,207