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Record W1980713978 · doi:10.1002/pc.21157

Relation between volumetric changes of unsaturated polyester resin and surface finish quality of fiberglass/unsaturated polyester composite panels

2011· article· en· W1980713978 on OpenAlexaff
Loleï Khoun, Geneviève Palardy, Pascal Hubert

Bibliographic record

VenuePolymer Composites · 2011
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceShrinkageComposite materialUnsaturated polyesterComposite numberMolding (decorative)Transfer moldingPolyesterPolyester resinGelcoatSynthetic resinMold

Abstract

fetched live from OpenAlex

Abstract Resin dimensional changes, including cure shrinkage and thermal expansion, highly influence the surface finish quality of composite parts. Low profile additives (LPA) are commonly incorporated in unsaturated polyester (UP) resins to compensate for resin shrinkage and obtain a high quality surface finish. In this study, the dimensional change of an UP resin with different LPA contents was characterized. Both resin cure shrinkage and resin thermal expansion were measured. A simple methodology was then developed to estimate the surface finish quality of panels, manufactured by resin transfer molding (RTM), based on the prediction of part thickness variation during the process. Results show good agreement with the experimental investigations. POLYM. COMPOS., 2011. © 2011 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)0.000
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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.054
GPT teacher head0.254
Teacher spread0.201 · 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

Citations10
Published2011
Admission routes1
Has abstractyes

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