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Record W2963727823 · doi:10.1177/0731684419865783

Experimental and numerical study of coupled gas and resin transport and its effect on porosity

2019· article· en· W2963727823 on OpenAlexaff
Mohammad Mohseni, Navid Zobeiry, G. Fernlund

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2019
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPorosityMaterials scienceComposite materialWork (physics)FiberCharacterisation of pore space in soilMechanical engineering

Abstract

fetched live from OpenAlex

Partially-impregnated prepregs are three-phase systems consisting of fiber, resin, and gas. During processing, one of the main goals is to evacuate the gas and infiltrate the space left behind with liquid resin to minimize porosity. Most work in this area has focused on gas and resin transport independently, and the interaction between resin and gas transport in these systems is currently poorly understood. The current study examines this interaction by evaluating the resulting laminate porosity as a function of different bag and applied pressures during debulk and cure. Experimental results show that resin flow can promote gas evacuation without the need for hard vacuum under the bag. An explicitly-coupled gas–resin transport model is developed on the basis that fiber-bed porosity is a function of resin infiltration. The model extends previous work in the area and is shown to predict the experimentally measured porosity under different pressure situations with acceptable accuracy.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.216
Teacher spread0.210 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2019
Admission routes1
Has abstractyes

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Same venueJournal of Reinforced Plastics and CompositesSame topicEpoxy Resin Curing ProcessesFrench-language works237,207