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Record W1843637124

Preform Characterization in VARTM Process Model Development

2004· article· en· W1843637124 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransfer moldingCompactionMaterials scienceComposite materialFabricationComposite numberFinite element methodInfiltration (HVAC)PorosityMolding (decorative)Structural engineeringEngineeringMold
DOInot available

Abstract

fetched live from OpenAlex

Vacuum-Assisted Resin Transfer Molding (VARTM) is a Liquid Composite Molding (LCM) process where both resin injection and fiber compaction are achieved under pressures of 101.3 kPa or less. Originally developed over a decade ago for marine composite fabrication, VARTM is now considered a viable process for the fabrication of aerospace composites (1,2). In order to optimize and further improve the process, a finite element analysis (FEA) process model is being developed to include the coupled phenomenon of resin flow, preform compaction and resin cure. The model input parameters are obtained from resin and fiber-preform characterization tests. In this study, the compaction behavior and the Darcy permeability of a commercially available carbon fabric are characterized. The resulting empirical model equations are input to the 3- Dimensional Infiltration, version 5 (3DINFILv.5) process model to simulate infiltration of a composite panel.

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 score0.799
Threshold uncertainty score0.323

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 head0.010
GPT teacher head0.214
Teacher spread0.203 · 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

Citations15
Published2004
Admission routes1
Has abstractyes

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