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Record W1973620112 · doi:10.1002/pc.22290

Capillary effects in vacuum‐assisted resin transfer molding with natural fibers

2012· article· en· W1973620112 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

VenuePolymer Composites · 2012
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsPolytechnique Montréal
FundersSecretaria de Ciencia y Tecnica, Universidad de Buenos AiresConsejo Nacional de Investigaciones Científicas y TécnicasGovernment of Canada
KeywordsMaterials scienceTransfer moldingComposite materialCapillary actionCapillary pressureComposite numberPermeability (electromagnetism)PorosityVoid (composites)Molding (decorative)Porous mediumMold

Abstract

fetched live from OpenAlex

Abstract The study of the capillary flow developed during the processing of composite materials is key because it acts as an important driving force for the impregnation of the fiber tows. It is also the main mechanism of void formation during infiltration of the fibers. In this work, capillary pressure of jute/vinylester composites was measured and the impact of capillary forces on fabric permeability was analyzed. It was found that the capillary pressure was significantly higher in vegetal than in synthetic fiber fabrics. In addition, the permeability of the fibers was characterized using various fluids. The resulting permeability was influenced by the nature of fluid and its polar property. Finally, the capillary pressure measured by this work was used to correct the experimental permeability in order to obtain a property independent of the test fluid. POLYM. COMPOS., 2012. © 2012 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.

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 score0.044
Threshold uncertainty score0.874

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 head0.197
Teacher spread0.191 · 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