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Record W2783198177 · doi:10.1115/imece2017-70773

A Tool to Identify Damping During Large Amplitude Vibrations of Viscoelastic Structures

2017· article· en· W2783198177 on OpenAlexaff
Prabakaran Balasubramanian, Giovanni Ferrari, Marco Amabili

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsViscoelasticityDissipationDamping torqueVibrationAmplitudeMagnetic dampingNonlinear systemThermoelastic dampingMechanicsHysteresisVibration controlDamping ratioExcitationPhysicsAcousticsVoltageThermalOpticsCondensed matter physics

Abstract

fetched live from OpenAlex

Various damping models are available to describe the dissipation energy present in structures. Among them, viscous and viscoelastic damping models are widely used to describe the damping in viscoelastic structures. Recent studies show that both viscous and viscoelastic damping of a structure varies as it experiences large amplitude vibrations. This makes it necessary to adjust the damping values with respect to the maximum vibration amplitude. The knowledge of damping values allows engineers to estimate the maximum vibration amplitude of a structure under various operating scenarios, thus improving the estimate of the safety margin and the efficiency of design. However, the variation of hysteretic damping during large amplitude vibrations was not addressed yet. Hysteretic damping is defined as dissipation energy due to the internal friction between the internal planes of the material and is independent on frequency. Hysteretic damping is well defined in linear vibrations as the ratio of loss and storage energies. The concept is here extended and hysteretic damping is identified during nonlinear vibrations. This paper presents the experimental data measured on a clamped-clamped rubber square plate under harmonic excitation at various force levels. A tool based on temporal method was developed to identify the nonlinear parameters and to calculate the hysteretic damping from the experimental data. The results show that hysteretic damping decreases with excitation frequency.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.515

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 head0.023
GPT teacher head0.353
Teacher spread0.329 · 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
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

Citations2
Published2017
Admission routes1
Has abstractyes

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