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Record W1664265052 · doi:10.5267/j.esm.2015.7.004

Analysis of Eddy current damper for suppression of vibrations using COMSOL software

2015· article· en· W1664265052 on OpenAlexvenueno aff
Rajwinder Singh, Vijay Pratap Singh

Bibliographic record

VenueEngineering Solid Mechanics · 2015
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsnot available
Fundersnot available
KeywordsEddy currentVibrationDamperSoftwareCurrent (fluid)AcousticsStructural engineeringMaterials scienceEddy-current testingMechanical engineeringEngineeringComputer sciencePhysicsElectrical engineering

Abstract

fetched live from OpenAlex

An Eddy current damper uses magnets to suppress vibrations due to external excitations. These dampers also called electromagnetic dampers, have advantages of no mechanical contact, high reliability and stability, but require a relatively large volume and mass to attain a given amount of damping. The magnets respond to an external excitation field. Along with the construction of the damper, COMSOL software is used for analysis of the eddy current damper and got various results like magnetic flux density, eddy current intensity, velocity and acceleration of the moving magnet. For this a standard dimension of an automotive vehicle damper is used so that the prototype could be tested on a damper testing machine. The standard dimension is chosen to increase the adaptability, compatibility and to ease of testing the damper. After this task the response of damper under various loads is observed. Different materials of housing tube are taken to observe the effects of various parameters like flux density, current intensity and, of course, the damping capability of the prototype damper.

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: Methods · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.493

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 head0.033
GPT teacher head0.275
Teacher spread0.242 · 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
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

Citations4
Published2015
Admission routes1
Has abstractyes

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