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Record W2089879629 · doi:10.1115/detc2010-28472

A Viscoelastic Based Mechanism for Improving Spring-In Angle Predictions in Compression Molded Thermoplastic Matrix Composites

2010· article· en· W2089879629 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersMitacs
KeywordsComposite materialMaterials scienceCompression moldingViscoelasticityThermoplasticSpring (device)Finite element methodComposite numberMatrix (chemical analysis)Compression (physics)MoldStructural engineering

Abstract

fetched live from OpenAlex

In this paper, dimensional distortion during the compression molding of thermoplastic matrix composites, typically described as spring-in or spring forward, is investigated through a finite element model. Spring-in is the reduction of the enclosed angle of two surfaces on the final component shape with respect to the original mold shape. Spring-in of thermoplastic matrix composites has typically been attributed to the difference in the thermal expansion of in-plane and through thickness directions of the composite. However, using this mechanism alone during modeling has not shown complete agreement with the experimental data. A new meso-level mechanism based on the viscoelasticity effect of the thermoplastic matrix is proposed. With this mechanism, the predicted spring-in angle can be in good agreement with experiments.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.709

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 head0.006
GPT teacher head0.227
Teacher spread0.221 · 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

Quick stats

Citations1
Published2010
Admission routes2
Has abstractyes

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