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Record W3199502240 · doi:10.3390/polym13183181

Design and Ductile Behavior of Torsion Configurations in Material Extrusion to Enhance Plasticizing and Melting

2021· article· en· W3199502240 on OpenAlexaff
Ranran Jian, Weimin Yang, Mohini Sain, Chuanwei Zhang, Lupeng Wu

Bibliographic record

VenuePolymers · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsTorsion (gastropod)Materials scienceExtrusionPolymerPlasticizerComposite materialFabricationMechanicsMechanical engineering

Abstract

fetched live from OpenAlex

In the present work, the ductile formation mechanism of a newly proposed torsion configuration has been investigated. One of the unique attributes of this paper is the first-time disclosure of the design and fabrication of a novel prototype screw with torsional flow character validating the orthogonal test model experimentally. The torsional spiral flow patterns that occurred in the torsion channel cause a ductile deformation of polymer in the form of a spiral, which in turn enhances the radial convection, achieving an effective mass transfer of material from the top region to the bottom region and vice versa. Furthermore, the characteristic parameters of torsion configuration have a significant influence on the plasticizing and melting capability of polymer. By range analysis and weight matrix analysis, the best factor and level combination was obtained. Results indicated that the aspect ratio of the torsion channel is almost equal to 1, and the plasticizing and melting capability of polymer is optimal. This novel design innovation offers a paradigm shift in the energy-efficient plasticization of polymer compounds.

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 score0.033
Threshold uncertainty score0.237

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 head0.010
GPT teacher head0.251
Teacher spread0.242 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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