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Record W2048876684 · doi:10.3139/217.1695

Three-dimensional Numerical Modeling of Co-injection Molding

2002· article· en· W2048876684 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

VenueInternational Polymer Processing · 2002
Typearticle
Languageen
FieldEngineering
TopicInjection Molding Process and Properties
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceCore (optical fiber)Isothermal processMolding (decorative)Work (physics)Finite element methodPolymerMechanicsComposite materialNewtonian fluidFlow (mathematics)Mechanical engineeringThermodynamicsPhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract In this work, a three-dimensional finite element flow analysis code is used to solve sequential co-injection molding problems. Non-Newtonian, non-isothermal flow solutions are obtained by solving the momentum, mass and energy equations. Two additional transport equations are solved for tracking polymer/air and skin/core polymers interfaces. Solutions are shown for a center gated rectangular plate. The effect of varying the melt/mold temperature and the ratio between the skin and core materials is investigated. The solution obtained for the same skin and core materials is compared with those in which viscosities of core and skin materials are much different. Finally, the solution for the co-injection of a C-shaped plate is presented. The three-dimensional modeling of co-injection molding provides the complete shape of the core polymer as well as the skin polymer thickness at any location. This is a major improvement over the traditional mid-plane approach, which is unable to recover the material behavior in critical regions as near corners, obstacles, and changes in part thickness.

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)0.000
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 score0.497
Threshold uncertainty score0.591

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)0.0010.000

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 head0.028
GPT teacher head0.247
Teacher spread0.218 · 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