MétaCan
Menu
Back to cohort
Record W1567378991 · doi:10.1002/stc.1670

Optimal design of distributed tuned mass dampers for passive vibration control of structures

2014· article· en· W1567378991 on OpenAlexafffund
Fan Yang, Ramin Sedaghati, Ebrahim Esmailzadeh

Bibliographic record

VenueStructural Control and Health Monitoring · 2014
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsUniversity of Ontario Institute of TechnologyConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsTuned mass damperVibration controlVibrationDamperStructural engineeringControl theory (sociology)Computer scienceEngineeringControl (management)PhysicsAcoustics

Abstract

fetched live from OpenAlex

The distributed tuned mass damper (DTMD) system consists of multiple tuned mass dampers, which are designed to suppress the undesirable structural vibration over a bandwidth centered at a particular tuned frequency. In this study, an innovative practical approach to optimally design the DTMD system has been proposed. Comparisons were made between the optimal DTMD system, obtained based on the proposed design approach, and those using the conventional design approach. The superior performance and robustness of the optimally designed DTMD system based on the proposed approach compared with that based on the conventional approach have been demonstrated through illustrative examples. It has been shown that the proposed design approach provide a simple, clear, and straightforward way to effectively attain the optimum parameters of the DTMD system. Copyright © 2014 John Wiley & Sons, Ltd.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.265
Teacher spread0.246 · 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 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

Citations30
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueStructural Control and Health MonitoringSame topicVibration Control and Rheological FluidsFrench-language works237,207