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Record W4389584916 · doi:10.17118/11143/21045

Prediction of mode-splitting phenomenon in rings deviated fromaxisymmetric

2023· article· en· W4389584916 on OpenAlexaff
Mohammad Javad Abedini Laksar, Jianming Yang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRotational symmetryMode (computer interface)PhysicsMechanicsComputer science

Abstract

fetched live from OpenAlex

Abstract: When a structure deviates from axisymmetric conditions for any reason, the system behaviour can be qualitatively different from that of the idealized representation. Classical approaches analyze the vibration of systems with simple geometries having homogenous material and symmetrical boundary conditions. In the presence of any perturbations in a system, the harmonic mode shapes can be contaminated by additional wavenumbers as the modes split. In this work, one of the most straightforward axisymmetric structures, namely, a ring that exhibits motion in radial and tangential directions, is investigated. The studied ring is mounted into its frame at different points with different types of supports. An analytical method is used in this research that allows one to obtain the system's natural frequencies and mode shapes when this ring is non-axisymmetric due to a nonuniformity in the boundary conditions of the ring. The deviation from the axisymmetric can cause a significant change in the system’s natural frequencies and the corresponding mode shapes. This change is crucial for cases with repeated natural frequencies and degenerated modes. For the studied cases in this work, results show that for an axisymmetrical ring, the contamination of the split modes occurs at wavenumbers far from the base modes, however, for rings with non-uniform or anti-symmetrical boundary conditions, a significant distortion occurs in the contaminant modes lower than the base natural frequencies. An algebraic relationship between the nodal diameter and the contamination wavenumber is discussed in this work, and the corresponding diagrammatic schematics for different cases are plotted. The results for different scenarios are presented and individually validated with the help of Abaqus software.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.196
Teacher spread0.182 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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