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Record W2169863934 · doi:10.1051/matecconf/20120101004

Nonlinear Modeling and Analysis of a Vertical Springless Energy Harvester

2012· article· en· W2169863934 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

VenueMATEC Web of Conferences · 2012
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVibrationEnergy harvestingNonlinear systemEnergy (signal processing)AcousticsElectric potential energyMechanical energyWind powerPhysicsComputer scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Harvesting energy from ambient sources has attracted the attention of researchers and scientists over the last few decades. While solar, thermal and wind energies have been exploited over the years, a new type of energy that has emerged in recent years, and is the subject of many research projects, is vibration energy harvesting. In this paper we will describe and analyze a recently proposed vibration energy harvester, namely the “Springless” vibration energy harvester. In this study, we will model and analyze the “Springless” vibration energy harvester in the vertical configuration. The vertically-aligned configuration is used when vibrations are predominantly in the vertical direction. Test results of a prototype model as well as results form a mathematical model describing the behavior of the harvester are presented. Test results show that the “Springless” energy vibration harvester behaves as a softening nonlinear oscillator for excitations above 0:2g with its center frequency shifting to the right. Similar results were obtained using a mathematical model of the underlying impact oscillator.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.380

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 head0.028
GPT teacher head0.236
Teacher spread0.208 · 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