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Record W1987585834 · doi:10.1002/pc.23427

Two‐dimensional long‐flexible fiber simulation in simple shear flow

2015· article· en· W1987585834 on OpenAlexaff
Gleb Meirson, Andrew N. Hrymak

Bibliographic record

VenuePolymer Composites · 2015
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceSimple shearCompression moldingShear (geology)Composite materialShear flowFlow (mathematics)FiberOrientation (vector space)Molding (decorative)Simple (philosophy)MechanicsGeometryMathematicsPhysics

Abstract

fetched live from OpenAlex

Long‐flexible fiber orientation under the influence of a flow field is an important engineering problem. One can encounter this problem in many fields. For example in fiber reinforced thermoplastics produced in both injection and compression molding, fiber orientation affect final part properties. Fiber orientation models are constructed for short fibers in a simple shear flow case and though this case is important it is not the general case. In this work we extract rotational friction coefficients from Jeffery's model, create a general case long‐flexible fiber orientation model, and apply it in a simple shear flow. POLYM. COMPOS., 37:2425–2433, 2016. © 2015 Society of Plastics Engineers

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.156
Threshold uncertainty score0.872

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 head0.021
GPT teacher head0.254
Teacher spread0.233 · 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 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

Citations8
Published2015
Admission routes1
Has abstractyes

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