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Record W2042202699 · doi:10.1115/fedsm2008-55071

Analytical Determination of Viscous Permeability of Fibrous Porous Media

2008· article· en· W2042202699 on OpenAlexaff
Ali Tamayol, Majid Bahrami

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPermeability (electromagnetism)Porous mediumMaterials sciencePorosityComposite materialMechanicsMembraneChemistryPhysics

Abstract

fetched live from OpenAlex

In this study, the permeability of ordered fibrous media towards normal and parallel flow is determined analytically. In this approach, porous material is represented by a “unit cell” which is assumed to be repeated throughout the media. Several fiber arrangements including: touching and non-touching arrays are considered. Modeling 1D touching fibers as a combination of Channel-like conduits, a compact relationship is proposed to predict permeability. Employing an integral technique and assuming a parabolic velocity profile within the unit cells, analytical relationships are developed for pressure drop for rectangular arrangements. The developed models are successfully compared with existing experimental data collected by others for square arrangement over a wide range of porosity. Due to the random nature of the porous micro structures, determination of exact permeability of real fibrous media is impossible. However, the analyses developed for ordered unit cells enable one to predict the trends observed in experimental data. Moreover, it is shown that the proposed normal flow permeability of square unit cell serves as a lower bound for the permeability of fibrous media. The effects of unit cell aspect ratio and fibers diameter on the permeability are also investigated. It is noted that with an increase in the aspect ratio the normal permeability decreases while, the parallel permeability remains constant. It is also shown that the permeability of fibrous media is related to the diameter of fibers squared.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.233

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 head0.016
GPT teacher head0.236
Teacher spread0.220 · 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 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

Citations6
Published2008
Admission routes1
Has abstractyes

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