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Record W4365137755 · doi:10.1155/2023/7307224

Theoretical and Experimental Analysis of a Winding Rope Fluid Viscous Damper

2023· article· en· W4365137755 on OpenAlexaff
Cheng Zhang, Wenxue Zhang, Lijun Su, Ying Chen, Xiuli Du

Bibliographic record

VenueStructural Control and Health Monitoring · 2023
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsUniversity of British Columbia
FundersNational Natural Science Foundation of China
KeywordsDamperRopeParametric statisticsStructural engineeringDisplacement (psychology)EngineeringWire ropeControl theory (sociology)MechanicsComputer scienceMathematicsPhysics

Abstract

fetched live from OpenAlex

This paper investigated a winding rope fluid viscous damper (WRFVD) that uses the frictional amplification mechanism of a winding rope to obtain the operating characteristics of a viscous damper-like device. The WRFVD combined the advantages of fluid viscous dampers and friction dampers. It not only retained the mechanical characteristics of the fluid viscous damper but also reduced manufacturing costs. First, the construction and working principles of the WRFVD were introduced. A theoretical model that could accurately simulate the hysteretic characteristics of the damper was derived. Then, a series of dynamic tests were performed on six prototypes of the WRFVD. The dynamic performance under different displacement amplitudes and device parameters was analyzed based on the test results. In addition, the theoretical model was validated by experimental results. Finally, a series of parametric analyses of the WRFVD were performed. The experimental results showed that the WRFVD is a type of velocity-dependent damper with smooth and plump hysteretic curves under sinusoidal displacement excitation. Fatigue loading tests showed that the WRFVD had excellent fatigue resistance capacity and stable operational performance. The established theoretical model was reasonable and satisfactorily reproduced the hysteretic properties of the WRFVD. The parametric analyses showed that it was not recommended to improve the performance of the WRFVD by the method of adjusting the damping coefficient and pretightening load. It was reasonable to adjust the performance of the WRFVD by setting a smaller velocity exponent, an appropriate winding turn of winding ropes, and a suitable friction coefficient.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.298
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2023
Admission routes1
Has abstractyes

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