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Record W4210345558 · doi:10.1139/tcsme-2021-0015

Experimental investigation of dynamic vibration absorption to design an improved particle damper

2022· article· en· W4210345558 on OpenAlexvenueno aff
Kai Zhang, Farong Kou

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsnot available
FundersXi'an University of Science and TechnologyChina Postdoctoral Science Foundation
KeywordsCantileverTuned mass damperStiffnessDamperVibrationSpring (device)Materials scienceVibration controlDynamic Vibration AbsorberResonance (particle physics)Particle (ecology)Frequency responseStructural engineeringSine waveControl theory (sociology)AcousticsPhysicsEngineeringComputer scienceControl (management)

Abstract

fetched live from OpenAlex

We introduce a tuned particle damper (TPD) to improve the damping performance of the traditional particle damper by adding a dynamic vibration absorption structure. To better design a TPD as a dynamic vibration absorber (DVA), we changed the dynamics of a DVA system based on a primary cantilever system by introducing stainless steel balls and a carbon steel mass block. Using a series of sine-sweep tests on the primary cantilever system attached with a spring-mass system, we obtained frequency response function (FRF) curves under different conditions. Our experimental results show that the dynamic behavior of the primary cantilever system was more prominent on the resonance peak closer to the mass control area, whereas the dynamic behavior of the additional spring-mass system is more prominent on the resonance peak closer to the stiffness control area. Based on these results, we analyzed the abnormal but desirable dynamic characteristics of TPD presented in the discrete mass experiment, and the results indicates preliminary success with our design of a TPD.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.321

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 head0.014
GPT teacher head0.204
Teacher spread0.190 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicVibration Control and Rheological FluidsFrench-language works237,207