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Record W2782295820 · doi:10.1139/cjp-2017-0708

Analytical and experimental studies on a new linear energy harvester

2018· article· en· W2782295820 on OpenAlexvenueno aff
Erol Kurt, Mustafa Kale, Sinan Akbaba, Nicu Bizon

Bibliographic record

VenueCanadian Journal of Physics · 2018
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsMagnetCore (optical fiber)VoltageMagnetic fieldMechanical energyVibrationPower densityPower (physics)ElectricityElectrical engineeringEnergy (signal processing)AcousticsNuclear magnetic resonanceMechanical engineeringOptics

Abstract

fetched live from OpenAlex

A new electromagnetic energy harvester has been designed to generate electricity from mechanical vibrations. The new system operates with two springs attached to two ends of a linear-laminated core and a winding circulated on the core directs the electrical energy to the output. Initially an electromagnetic model has been developed for the Halbach-oriented magnets at the ends of core. That orientation has been used to deviate the magnetic field at the tips of the core unit. Some preliminary studies prove that the output peak voltage U = 0.75 V and maximal peak power P = 14 mW can be achieved experimentally, thereby a power density of p = 0.3684 mW/cm 3 is obtained with the new system. The efficiency of that new designed linear harvester reaches 36% at its optimum frequency and electrical load conditions.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.381

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 head0.044
GPT teacher head0.275
Teacher spread0.231 · 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 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

Citations9
Published2018
Admission routes1
Has abstractyes

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