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Record W2069601837 · doi:10.1115/imece2013-65990

Nonlinear Longitudinal Vibration Solutions of an Elastic Rod

2013· article· en· W2069601837 on OpenAlexaff
Hassan Askari, Ebrahim Esmailzadeh, Davood Younesian

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicFractional Differential Equations Solutions
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsNonlinear systemMathematical analysisGalerkin methodDuffing equationJacobian matrix and determinantMathematicsVibrationDifferential equationPartial differential equationPhysicsApplied mathematics

Abstract

fetched live from OpenAlex

Nonlinear longitudinal vibration of an elastic rod is studied. The motion of a uniform elastic rod is described by a nonlinear partial differential equation, which has a cubic nonlinear term and a Winkler elastic force that acts along the longitudinal axis of the rod. Galerkin method is used to develop the nonlinear differential equation of elastic rod, which resembles similarity with the Duffing equation. Three different types of robust analytical methods are chosen to solve the nonlinear differential equation and obtain the natural frequency of the system. These are the Homotopy analysis method (HAM), Energy balance method (EBM) and Hamiltonian approach (HA). Subsequently, the analytical results are compared with the numerical solution of the exact equation in order to evaluate the correctness of the applied approaches. Moreover, the effects of the constant coefficients of the elastic force on the ratio of the nonlinear to the linear frequencies are studied. The singular points of the nonlinear differential equation of the elastic rod are extracted and the Jacobian matrix is constructed to recognize their types. Finally, phase-plane trajectories of the system are constructed in order to verify the results obtained from the Jacobian matrix.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.481
Threshold uncertainty score0.998

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.085
GPT teacher head0.323
Teacher spread0.238 · 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.

Study designTheoretical or conceptual
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

Citations3
Published2013
Admission routes1
Has abstractyes

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