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Record W2088020922 · doi:10.1002/pen.20142

Modeling and simulation of stretch blow molding of polyethylene terephthalate

2004· article· en· W2088020922 on OpenAlexaff
Xuan-Tan Pham, F. Thibault, L‐T. Lim

Bibliographic record

VenuePolymer Engineering and Science · 2004
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsHusky Injection Molding Systems (Canada)
Fundersnot available
KeywordsMaterials scienceBlow moldingPolyethylene terephthalateHyperelastic materialBottleComposite materialFinite element methodMolding (decorative)PolymerMoldStructural engineering

Abstract

fetched live from OpenAlex

Abstract When polyethylene terephthalate (PET) is stretched, it exhibits strain‐hardening properties, which are temperature and strain‐rate dependent. In this paper, two grades of PET are experimentally characterized using biaxial tests. A visco‐hyperelastic model is used to describe the stretching behavior for the polymer. A biaxial characterization method is employed to determine the model parameters using a robust nonlinear curve‐fitting program. This model can represent adequately well the stretching behavior of PET. Based on this model, the membrane finite element formulation is developed to simulate the stretch blow molding process. Two bottles of different designs, produced based on the single‐stage injection blow molding process, are used to validate the model. Good agreement with the bottle thickness profile is observed. Polym. Eng. Sci. 44:1460–1472, 2004. © 2004 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations55
Published2004
Admission routes1
Has abstractyes

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