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Record W1998595754 · doi:10.1115/1.2776338

Modeling and Control of Torsional Beam Vibrations: A Wave-Based Approach

2008· article· en· W1998595754 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of vibration and acoustics · 2008
Typearticle
Languageen
FieldEngineering
TopicControl Systems in Engineering
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaSimon Fraser University
KeywordsTorsional vibrationControl theory (sociology)VibrationTorsion (gastropod)Boundary value problemTransfer functionBeam (structure)Vibration controlInertial frame of referenceController (irrigation)EngineeringPhysicsMechanicsStructural engineeringComputer scienceClassical mechanicsAcoustics

Abstract

fetched live from OpenAlex

This paper presents a wave-based modeling and control approach for suppressing torsional vibrations of an elastic shaft driven by a motor at one end and an inertial load at the other end. A two-port network model representing the dynamics of torsional displacements is obtained starting from the partial differential equations governing a shaft in torsion. By incorporating appropriate boundary conditions, the infinite dimensional transfer function of the system is obtained. Furthermore, the system is represented by delay elements that can be used for simulation purposes. An inversion-based controller that can be used to suppress vibrations while rotating the shaft according to a specific trajectory is then developed. The performance of the controller is further studied using numerical simulations.

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.

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: none
Teacher disagreement score0.785
Threshold uncertainty score0.310

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 head0.013
GPT teacher head0.187
Teacher spread0.175 · 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