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Record W2039304167 · doi:10.1002/pc.10038

Analysis of dynamic flows through porous media. Part I: Comparison between saturated and unsaturated flows in fibrous reinforcements

2003· article· en· W2039304167 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

VenuePolymer Composites · 2003
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPorous mediumMaterials scienceSaturation (graph theory)PorosityComposite numberDegree of saturationPermeability (electromagnetism)Composite materialFlow (mathematics)MechanicsMathematicsGeologyChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract This article presents a general approach to model flows through unsaturated porous media as they occur in Liquid Composite Molding (LCM). Saturated and unsaturated flows will be studied here both from the experimental and theoretical points of view. It is indeed important to distinguish between these two flow behaviors in order to understand the interactions between the three phases that coexist in a fibrous reinforcement: the solid and fluid phases on one hand, and the air content on the other. The experimental work presented here includes the study of permanent and transient flow regimes, both for saturated and unsaturated porous media. The dynamic effects that occur during fluid injection through fibrous reinforcements highlight the double scale , structure of their pore volume. The ratio between saturated and unsaturated permeabilities appears to be connected to the degree of saturation and to the porosity of the part. Given the importance of permeability as a key input parameter in process simulation, this article proposes to introduce the degree of saturation in the equations that govern the flow in order to increase the accuracy of numerical predictions. This will not only provide a better understanding of the underlying physical phenomena during the fluid impregnation of a fibrous preform, but will also ultimately allow the study of air entrapment mechanisms that govern the quality of composite parts.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.015
GPT teacher head0.254
Teacher spread0.238 · 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