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Record W2013589296 · doi:10.1115/imece2012-88915

The Effect of Microstructural Morphologies on the Effective Electromechanical Properties of Piezoelectric Particle Composites

2012· article· en· W2013589296 on OpenAlexaff
Vahid Tajeddini, Chien-hong Lin, Anastasia Muliana, Martin Lévesque

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials sciencePiezoelectricityComposite materialMicrostructureVolume fractionMicromechanicsParticle (ecology)Composite numberRepresentative elementary volumePermittivityElastic modulusDielectric

Abstract

fetched live from OpenAlex

This study introduces a micromechanical model that incorporates detailed microstructures for analyzing the effective electro-mechanical properties, such as piezoelectric and permittivity constants as well as elastic moduli, of piezoelectric particle reinforced composites. The studied composites consist of polarized spherical piezoelectric particles dispersed into a continuous and elastic polymeric matrix. A micromechanical model generated using three-dimensional (3D) continuum elements within a finite element (FE) framework. For each volume fraction (VF) of particles, realization with different particle sizes and arrangements were generated in order to represent microstructures of a particle composite. We examined the effects of microstructural morphologies, such as particle sizes and distributions, and particle volume fractions on the overall effective electro-mechanical properties of the active composites. The overall electro-mechanical properties determined from the present micromechanical model were compared to those generated using the Mori-Tanaka, self-consistent, and simplified unit-cell micromechanical models.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.145

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 head0.006
GPT teacher head0.188
Teacher spread0.182 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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