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Record W2046021512 · doi:10.1115/imece2003-42267

Chaotic Motion of a Two-Frequency Forced Oscillator With Dry Friction

2003· article· en· W2046021512 on OpenAlexaff
Gong Cheng, Jean W. Zu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLyapunov exponentExcitationBifurcationChaoticAmplitudePhysicsDry frictionPoincaré mapBifurcation diagramClassical mechanicsMechanicsHarmonic oscillatorControl theory (sociology)MathematicsStatistical physicsNonlinear systemQuantum mechanicsComputer scienceMaterials science

Abstract

fetched live from OpenAlex

In this paper, the dynamic behavior of a dry friction oscillator subjected to simultaneous self- and external excitations is studied. The dry friction in the system follows the classical Coulomb’s law, and the external excitation consists of two harmonic forces with different frequencies. The focus of the paper is laid on bifurcation analysis to gain insight into the influence of the two-frequency excitation upon the qualitative features of system dynamics. Numerical simulations are performed and the simulation results are visualized by means of bifurcation diagrams, Poincare´ sections and Lyapunov exponents. New and interesting conclusions are reached from the study. It is shown that small excitation frequencies and amplitudes tend to cause chaos in the system, whereas large excitation amplitudes can induce only periodic motions. Furthermore, it is found that the probability of the occurrence of periodic motions increases, as the ratio between the two excitation frequencies increases.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.207
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2003
Admission routes1
Has abstractyes

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