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Record W2049445354 · doi:10.1515/secm.2000.9.3.111

Cure Kinetics of Hexcel W3T282-42/F155 Graphite/Epoxy Prepreg

2000· article· en· W2049445354 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

VenueScience and Engineering of Composite Materials · 2000
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceEpoxyComposite materialGraphiteKineticsMaterials processingProcess engineering

Abstract

fetched live from OpenAlex

In this work, differential scanning calorimetry (DSC) in dynamic and isothermal modes is used to develop a cure kinetics model for the graphite/epoxy prepreg Hexcel W3T282-42/F155. The evolution of heat from the composite system was measured from dynamic DSC scans and the total heat of reaction of the system calculated. Isothermal heat flow measurements were then taken at different constant temperatures, and the isothermal heat of reaction, the rate of cure, and the degree of cure were calculated as a function of time for each temperature. A variety of different cure kinetics models proposed in the literature were examined in order to develop an expression for resin cure rate as a function of degree of cure and temperature. Best results were obtained by using a semi-empirical equation in which the maximum achievable degree of cure was considered to be temperature dependent. A least squares technique based on the Levenberg-Marquardt algorithm was used for curve fitting. Very good agreement between experimental measurements and model results was observed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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