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Record W2900995640 · doi:10.1115/smasis2018-8209

Static and Dynamic Characterization of Magnetorheological Elastomers Under Shear Mode Operation

2018· article· en· W2900995640 on OpenAlexaff
Ashkan Dargahi, Ramin Sedaghati, Subhash Rakheja

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceComposite materialMagnetorheological fluidShear modulusElastomerShear (geology)Magnetorheological elastomerVolume fractionShear stressDynamic mechanical analysisPure shearSimple shearMagnetic fieldPolymerPhysics

Abstract

fetched live from OpenAlex

Static and dynamic properties of six magnetorheological elastomers (MRE) with iron particles volume fraction ranging from 12.5% to 40% were experimentally characterized under shear mode operation. The experiments were designed on the basis of standardized methods defined in ISO-1827 and ISO-4664. The static shear stress-shear strain data obtained under strains up to 30% were used to quantify absolute and relative MR effects of the MREs as functions of magnetic flux density in the 0 to 450 mT range. The MRE specimen with highest iron particles fraction and a softening agent revealed greatest MR effect. The dynamic characteristics of this MRE specimen were then evaluated under harmonic excitations in the 0.1–50 Hz frequency range with shear strain amplitude and magnetic flux density ranging from 2.5 to 20%, and 0 to 450 mT, respectively. The data were then utilized to evaluate elastic and loss shear moduli of the specimen.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.969
Threshold uncertainty score0.682

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)0.0010.000

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 head0.005
GPT teacher head0.216
Teacher spread0.210 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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