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Record W2140385571

NUMERICAL INVESTIGATION OF FLOW IN FIBROUS POROUS MEDIA

2008· article· en· W2140385571 on OpenAlexaff
Ali Tamayol, Majid Bahrami

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPorous mediumPermeability (electromagnetism)PorosityMaterials scienceMechanicsFlow (mathematics)Composite materialPhysicsChemistry
DOInot available

Abstract

fetched live from OpenAlex

Fibrous porous materials involve in many natural and engineering processes. In this study, the permeability of ordered fibrous media towards normal and parallel flows is studied numerically. Porous material is represented by a “unit cell ” which is assumed to be repeated throughout the media and 1D fibers are modeled as a combination of Channel-like conduits. The numerical results are successfully compared with the experimental data collected by others and existing correlations in the pertinent literature, for square arrangement of fibers over a wide range of porosity. A compact correlation is proposed for parallel permeability of fibrous media, which can predict the results accurately over the entire range of porosity. Moreover, microscopic velocity profiles in the unit cell are investigated in detail for both parallel and normal flows. The numerically predicted velocity distributions for normal and parallel flow cases are compared with experimental and simple parabolic profiles. The comparison showed that although assumption of the parabolic velocity distribution results in reasonable values for permeability, this form of the velocity profile is not realistic.

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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.207

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 head0.014
GPT teacher head0.197
Teacher spread0.182 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations6
Published2008
Admission routes1
Has abstractyes

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