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Record W2169324736 · doi:10.1063/1.4931794

Bandwidth widening of vibration energy harvesters through a multi-stage design

2015· article· en· W2169324736 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Renewable and Sustainable Energy · 2015
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsVibrationBandwidth (computing)USableOptimal designMaximizationEnergy harvestingAcousticsExcitationRange (aeronautics)Energy (signal processing)Computer scienceElectronic engineeringEngineeringPhysicsElectrical engineeringTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

A vibration harvester is usually designed to work in resonance responding to source vibration. However, in many cases, this source vibration may occur at a wide range of frequencies. If the harvester has very narrow tuning range, it becomes ineffective when there is a mismatch in the frequencies between source excitation and device resonance. Increasing the bandwidth of vibration harvesters has been an important design objective. We propose a two-stage design to improve of a harvester's performance. In a previous work [J. S. Fernando and Q. Sun, Rev. Sci. Instrum. 84(11), 114704 (2013)], we have demonstrated that use of a two-stage design can increase the power production at a single frequency excitation. In this paper, we will show that a two-stage design can also increase the width of the usable frequency band of the harvester. An optimization routine was used to determine the optimal choice of harvester design parameters with respect to the maximization of an objective function. Experiments were used to verify the electromechanical model as well as the trends predicted by the optimization. Performance comparisons between single- and two-stage harvesters are made through numerical simulation and experiments.

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.

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)0.000
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.046
GPT teacher head0.250
Teacher spread0.205 · 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