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Record W2034479276 · doi:10.1115/imece2010-39485

Effective Modelling of Sticking Motions in Vibro-Impacting Continuous Systems

2010· article· en· W2034479276 on OpenAlexaff
C. P. Vyasarayani, Sukhpreet Singh Sandhu, John McPhee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLagrange multiplierSticking coefficientObstacleWork (physics)Control theory (sociology)Multiplier (economics)Mode (computer interface)Computer scienceCoefficient of restitutionMechanicsPhysicsMathematical optimizationMathematicsThermodynamicsArtificial intelligenceChemistry

Abstract

fetched live from OpenAlex

In this work we propose a new methodology to simulate sticking motions occurring in vibro-impacting continuous systems. We have developed this method in the framework of the coefficient of restitution approach. During the sticking phase, the sticking constraints are imposed exactly using a Lagrange multiplier, which represents the reaction between the continuous system and the obstacle. The expression for the Lagrange multiplier is developed in closed form. The proposed method does not require the mode-shapes during the sticking phase, unlike the mode-switching method. The developed methodology is supported by illustrative 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.

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 score0.437
Threshold uncertainty score0.383

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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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