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Record W1995527630 · doi:10.1109/iecon.2013.6699810

Modeling and design of a motion converter for utilization as a vibration energy harvester

2013· article· en· W1995527630 on OpenAlexaff
Amir Maravandi, Mehrdad Moallem

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMechanism (biology)Reciprocating motionShock absorberVibrationKinematicsRotation around a fixed axisShock (circulatory)Energy harvestingEngineeringPower (physics)Mechanical engineeringControl theory (sociology)Computer scienceAcousticsPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

This paper presents the analysis and design of a mechanism to be utilized as a regenerative shock absorber. The device consists of an algebraic screw mechanism, a planetary gearhead, and a DC rotary machine. The algebraic screw is a kinematic mechanism that converts the translational vibration motion into a reciprocating rotary motion which drives a rotary generator. The energy generated by the rotary machine is converted into the battery charge through a power electronic converter. In this study, the amount of damping provided by the shock absorber is analyzed using the dynamic analysis of a quarter car system. To this end, expressions for the input, captured, and lost power are presented in terms of the parameters of the shock absorber and road excitation profile. Simulations are carried out to study the characteristics of design in terms of converting vibration energy into rotary motion. Validation of the model is demonstrated by comparing the simulation and numerical results.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.279

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 communication0.0000.001
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 head0.047
GPT teacher head0.231
Teacher spread0.184 · 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".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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