MétaCan
Menu
Back to cohort
Record W2108786819 · doi:10.1109/08ias.2008.72

A Methodology to Design Linear Generators for Energy Conversion of Ambient Vibrations

2008· article· en· W2108786819 on OpenAlexaff
Haodong Li, Pragasen Pillay

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsVibrationTransient (computer programming)Energy harvestingGenerator (circuit theory)VoltageLinear congruential generatorAcousticsBridge (graph theory)Electrical engineeringElectric generatorEnergy (signal processing)Power (physics)EngineeringPhysicsComputer science

Abstract

fetched live from OpenAlex

An air-core tubular linear generator is designed, using an analysis of the transient vibrations of a bridge created by traffic; the energy is used to supply a wireless sensor for the bridge. The relationship is described between the moving mass, the spring and the damping for harvesting sufficient vibration energy. The voltage and power of the linear generator with sinusoidal speed are attained with a transient electromagnetic field analysis. Finally, the ambient experimental results of the linear generator are obtained and analyzed when excited by bridge vibrations.

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: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.390
Threshold uncertainty score0.354

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 head0.132
GPT teacher head0.283
Teacher spread0.151 · 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
GenreMethods

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

Citations14
Published2008
Admission routes1
Has abstractyes

Explore more

Same topicInnovative Energy Harvesting TechnologiesFrench-language works237,207