MétaCan
Menu
Back to cohort
Record W2901807812 · doi:10.25071/10315/35394

Modeling Of Magneto-Mechanical Response Of Magnetorhological Elastomers Having Different Arrangement Of Magnetic Particles

2018· article· en· W2901807812 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

VenueProgress in Canadian Mechanical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicVibration Control and Rheological Fluids
Canadian institutionsConcordia University
Fundersnot available
KeywordsMagnetoElastomerMaterials scienceBiomagnetismMagnetic nanoparticlesCondensed matter physicsMagnetic fieldComposite materialPhysicsMechanical engineeringMagnetEngineeringNanotechnologyNanoparticle

Abstract

fetched live from OpenAlex

A model describing the magneto-mechanical properties of magnetorheological elastomers (MREs) under an external magnetic field and a mechanical shear deformation is presented. The main purpose of the present study is to demonstrate the effect of particle distribution and applied magnetic field on the MRE mechanical properties. Four types of rectangular lattice models are considered as the representation of spatial distribution of magnetic particles in the matrix. Using the energy method, shear modulus is obtained and numerically calculated as function of the strength of the external magnetic field and the shear strain. The results show a high sensitivity of shear modulus on the spatial distribution of particles. Depending on the lattice type, shear modulus exhibits an increasing or decreasing behavior with the increase of magnetic field intensity.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.830

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.216
Teacher spread0.205 · 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