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Record W4210543475 · doi:10.1115/imece2021-72545

Solitary Waves in an Array of Nonlinear Oscillators With Time-Periodic Damping and Stiffness Coefficients

2021· article· en· W4210543475 on OpenAlexaff
Mohammad Reza Talebi Bidhendi, Ahmad Mohammadpanah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNonlinear Photonic Systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNonlinear systemStiffnessPhysicsStability (learning theory)Mathematical analysisControl theory (sociology)Nonlinear Schrödinger equationClassical mechanicsEnergy (signal processing)SolitonMechanicsMathematicsControl (management)Computer scienceQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract The localized nonlinear responses of a chain of nonlinear pendulums with time-periodic damping and stiffness coefficients are investigated. The existence conditions and stability of the solitary waves are revisited for the aforementioned system. In essence, the parametrically driven discrete Klein-Gordon equation with time-periodic damping coefficient is converted to a damped parametrically driven discrete nonlinear Schrodinger equation using the method of multiple scales. The numerical simulations show how the stability and characteristics of the solitary waves are modified when the periodically modulated damping coefficient, which is either synchronized or asynchronized with the time-periodic stiffness coefficient, is added. In practice, time-periodic damping coefficient can be treated as a new way to tune the characteristic of the solitons (i.e., required threshold of the soliton activation and the period of oscillations) in the nonlinear periodic structures. This modification may provide some insights towards the control of the energy localization phenomena in nonlinear periodic structures with time-varying coefficients for efficient energy transport/management applications.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.406

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 head0.008
GPT teacher head0.240
Teacher spread0.231 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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