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Record W2053293376 · doi:10.3139/217.1879

Nozzle Injection of Physical Blowing Agents in the Injection Molding of Microcellular Foams

2005· article· en· W2053293376 on OpenAlexaff
V. L. Bravo, Andrew N. Hrymak

Bibliographic record

VenueInternational Polymer Processing · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceNozzleBlowing agentInjectorPressure dropSpark plugMolding (decorative)Composite materialMoldPolymerInjection mouldingPorosityInjection molding machineMechanical engineeringMechanicsEngineeringPolyurethane

Abstract

fetched live from OpenAlex

Abstract Results obtained from the implementation of a physical foaming system for injection molding are presented. The implemented design involves the injection of gas in the upstream side of a special nozzle composed by a static mixing element (SMX type) and a shut-off valve. In order to avoid the formation of large pockets of gas in the injection point, a porous metal plug is used to create a multiple point injection area with 20 lm size pores. Gas injection simultaneously with polymer melt injection gave a consistent foamed material. However, given the total pressure drop in the system of static mixers, runners and mold, there is an inherent operational pressure limitation. The polymer injection pressure needs to be kept at a pressure below the gas injection pressure, therefore limiting the speed at which the polymer can be injected in the mold.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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 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

Citations9
Published2005
Admission routes1
Has abstractyes

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