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Record W2030556511 · doi:10.1115/imece2014-37646

A Study on Calculation Method of Natural Frequency for Rubber Damped Torsional Vibration Absorbers

2014· article· en· W2030556511 on OpenAlexaff
Wen‐Bin Shangguan, Yumin Wei, Subhash Rakheja, Xu Zhao, Jun-wei Rong, Yajie Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVehicle Noise and Vibration Control
Canadian institutionsConcordia University
FundersNational Natural Science Foundation of China
KeywordsNatural rubberVibrationNatural frequencyMaterials scienceDamperShear (geology)Structural engineeringFractional calculusMechanicsComposite materialMathematicsEngineeringPhysicsAcousticsMathematical analysis

Abstract

fetched live from OpenAlex

The natural frequency is the key performance parameters of a rubber materials damper, and it is determined by the static and dynamic shear properties of the rubber materials (rubber ring) and the moment of inertia of the inertia ring. The rubber ring is usually in compression state, and its static and dynamic shear properties are dependent on its sizes, compression ratio and chemical ingredients. A special fixture is designed and used for measuring static and dynamic shear performance of a rubber ring under different compression ratios in the study. To characterize the shear static and dynamic performances of rubbers, three constructive models (Kelvin-Voigt, the Maxwell and the fractional derivative constitutive model) are presented and the method for obtaining the model parameters in the fractional derivative constructive models are developed using the measured dynamic performance of a rubber shear specimen. The natural frequency of a rubber materials damper is calculated using the fractional derivative to characterize the rubber ring of the damper, and the calculated frequencies are compared with the measurements.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.715
Threshold uncertainty score0.305

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 head0.014
GPT teacher head0.283
Teacher spread0.268 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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