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Record W2321803095 · doi:10.1115/imece2003-42467

Modeling and Control of Magnetorheological Dampers for Vibration Isolation

2003· article· en· W2321803095 on OpenAlexaff
A. Narimani, M. F. Golnaraghi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMagnetorheological fluidDamperMagnetorheological damperVibration isolationVibration controlControl theory (sociology)VibrationEngineeringController (irrigation)Structural engineeringHysteresisWork (physics)Control systemReliability (semiconductor)Computer scienceControl (management)Mechanical engineeringPhysicsAcoustics

Abstract

fetched live from OpenAlex

Semi-active isolators offer significant improvement in performance over passive isolators. These systems benefit from the advantages of active systems with the reliability of the passive systems. In this work we study a vibration isolation system with a magnetorheological (MR) damper. The experimental investigation of the mechanical properties of a commercially available linear MR damper (RD-1005-3) was conducted next. The mathematical Bouc-Wen model was adopted to predict the performance of MR damper. In addition, a modified Bingham model has been developed to characterize the damper behavior more accurately and efficiently. The measured hysteresis characteristics of field-dependent damping forces are compared with the simulation results from the described mathematical models. The accuracy of a damping-force controller using the proposed method is also demonstrated experimentally. Finally, a scaled quarter car model is set up to study the performance of the control strategy. The experimental results show that with the semi-active control the vibration of the quarter car model is well controlled.

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: none
Teacher disagreement score0.931
Threshold uncertainty score0.179

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 head0.011
GPT teacher head0.200
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
Published2003
Admission routes1
Has abstractyes

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