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Record W1992494915 · doi:10.1106/f97f-u8rd-qyn8-q8ju

Curing of Thick Angle-Bend Thermoset Composite Part: Curing Process Modification for Uniform Thickness and Uniform Fiber Volume Fraction Distribution

2000· article· en· W1992494915 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

VenueJournal of Composite Materials · 2000
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsConcordia University
Fundersnot available
KeywordsMaterials scienceThermosetting polymerComposite materialCuring (chemistry)EpoxyComposite numberVolume fractionComposite laminatesGraphite

Abstract

fetched live from OpenAlex

The effect of existing cure cycles and processes on the quality of angle-bend thermoset parts was presented in a previous paper. In this paper, the 2-D finite difference scheme developed before was used to model the processing of arbitrary shaped composite laminates. The effect of different processing parameters on the final part was studied. An optimal curing process is defined as one which will produce uniform thickness and uniform fiber volume fraction distribution throughout the composite part including straight sections and curved sections. Based on the results of the model, a modified curing process was developed. This process was applied to a graphite/epoxy HerculesAS4/3501-6 curved laminate. Results obtained from simulation and experiment were compared. Good parts were obtained using an optimal curing process.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.259
Teacher spread0.243 · 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