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Record W1517148943 · doi:10.1109/ceidp.1999.804598

Numerical simulation of electrorheological properties of anisotropically filled elastomers

2003· article· en· W1517148943 on OpenAlexaff
Bo Liu, S.A. Boggs, Montgomery T. Shaw

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceElectric fieldPermittivityElastomerElectrostaticsPolarizabilityComposite materialElectrical resistivity and conductivityConductivityModulusParticle (ecology)DielectricPhysics

Abstract

fetched live from OpenAlex

We report the results of numerical simulations for the change of both mechanical and electrical properties of elastomers with anisotropically filled polarizable particles under the electric and mechanical fields. Such composites have potential applications in electro-mechanical control. We have used numerical techniques to study the effect of particle shape, permittivity/conductivity ratio, and spatial arrangement on the shear modulus as a function of electric field. We also investigated the influence of the high field, nonlinear conductivity in the polymer matrix. The results indicate that electrostatic energy and changes therein, which result in electrorheological effects, are concentrated between particles, and that the electrostatic interaction between the particles is concentrated in very narrow regime at the tips of the particles. The interaction increases with the electric field intensity until the field between the particles is high enough to cause nonlinear electrical conduction in the polymer resulting in a redistribution of the electric field and electrostatic energy.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.199
Teacher spread0.187 · 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

Citations3
Published2003
Admission routes1
Has abstractyes

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