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Record W2168740485 · doi:10.1177/1045389x15586449

The effect of magneto-rheological fluid on vibration suppression capability of adaptive sandwich plates: Experimental and finite element analysis

2015· article· en· W2168740485 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Intelligent Material Systems and Structures · 2015
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceRheologyComposite materialMagnetoVibrationFinite element methodPolyethylene terephthalateCore (optical fiber)CantileverStructural engineeringAcousticsMagnetMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

This article presents an experimental and theoretical study of vibration analysis of a magneto-rheological fluid-based sandwich plate. Two sandwich plates consisting of polyethylene terephthalate face layers were fabricated with two different magneto-rheological fluids (MRF-132DG and MRF-122EG) as the core layer and silicon rubber spacer as the sealant. The dynamic responses of the cantilever sandwich plate were experimentally characterized. A finite element model based on the Classical Plate Theory was formulated to obtain governing equations of motion of the multi-layer magneto-rheological plate. The complex shear modulus of each magneto-rheological fluid in the pre-yield region was described by a phenomenological model as a function of the magnetic flux density and excitation frequency. The results clearly showed enhanced vibration suppression properties of the magneto-rheological sandwich plate over a broad frequency range through variations in both the stiffness and damping.

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.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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