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Characterization and modeling of the anisotropic flow behavior of long carbon fiber reinforced thermoplastic compression molding

2025· article· en· W4411196623 on OpenAlexaff
Louis Schreyer, Constantin Krauß, Benedikt M. Scheuring, Andrew N. Hrymak, Luise Kärger

Bibliographic record

VenueComposites Part A Applied Science and Manufacturing · 2025
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsWestern University
FundersDeutsche ForschungsgemeinschaftApplied Materials
KeywordsMaterials scienceComposite materialCompression moldingThermoplasticThermoplastic compositesAnisotropyMolding (decorative)Characterization (materials science)Compression (physics)Flow (mathematics)FiberMechanicsMold

Abstract

fetched live from OpenAlex

The anisotropic rheological properties of compression-molded long carbon fiber reinforced polyamide 6 are examined using isothermal squeeze flow tests between two parallel plates at various temperatures and compression velocities. Due to the aligned initial fiber orientation state, the material exhibits strongly anisotropic flow behavior independent of the temperature and compression velocity. However, the material’s stress response is dependent on the shear rate and temperature, which are both investigated. In addition, lofting effects during heating are discussed. A two-dimensional model for non-lubricated squeeze flow that considers shear thinning behavior and the coupling between fiber orientation and flow is developed to capture the anisotropic viscous material behavior. The Mori–Tanaka-based fiber orientation evolution equation describes the fiber reorientation. The material properties are determined using state-of-the-art optimization techniques in a two-step procedure. First, the material parameters describing the shear thinning and anisotropic flow behavior are determined, followed by the temperature-dependent parameters. The obtained material properties agree well with the experimentally observed temperature and shear rate dependence. The material’s anisotropic nature, expressed by an ellipse-like deformation, is also well represented. Finally, the sensitivity of the anisotropy ratio on the velocity field for different shear thinning behavior is investigated.

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 score0.356
Threshold uncertainty score0.396

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 head0.008
GPT teacher head0.202
Teacher spread0.194 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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