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Record W2275802604

Comparison of harvested energy in AC and DC standard interface circuits using Metglas2605SC

2015· article· en· W2275802604 on OpenAlexvenueno aff
Kamran Ali Khan Niazi, Mansour Moradi

Bibliographic record

VenueMechanical Engineering Research · 2015
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsEnergy harvestingElectronic circuitElectrical engineeringMagnetostrictionBridge circuitEnergy (signal processing)Electric potential energyVibrationProof massElectronic engineeringMaterials scienceMicroelectromechanical systemsComputer scienceEngineeringAcousticsOptoelectronicsVoltagePhysicsMagnetic field
DOInot available

Abstract

fetched live from OpenAlex

One of the solutions for power generation in wireless technology is energy harvesting technique. The energy harvesting means the conversion of ambient energy such as vibration, heat, light, RF energy, etc. to electrical energy using smart materials and their structures. Harvesting vibration energy from magnetostrictive material attracts more attention in recent years and it can be used in applications of intelligent microgenerator. In this paper, a simple interface circuits have been introduced for magnetostrictive materials. 15 layers Metglas2605SC are used for magneto-elements. Theoretical modeling of the system done to deliver results. First, the standard AC circuit and then standard DC circuit was investigated by adding an electrical bridge and their harvested energy was compared. Followed by mentioned energy harvesting analyses the effect of four important parameters, equivalent load resistance, frequency, displacement amplitude and external force amplitude are examined. Finally, considering the obtained equations and effective parameters that was tested in this paper to compare the Metglas energy harvesting in AC and DC standard circuits, indicated that the AC Standard circuit harvested more energy. Keywords: Energy harvesting, Smart materials, Standard AC circuit, Standard DC circuit, Magnetostrictive, Microgenerators, MEMS, Metglas2605SC

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.171
GPT teacher head0.392
Teacher spread0.221 · 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 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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