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Record W4410069440 · doi:10.1002/cjce.25741

Flow of Boger fluids through packed bed of spherical and non‐spherical particles: Asymptotic behaviour

2025· article· en· W4410069440 on OpenAlexvenueno aff
Amanjot Kaur, Amit Sobti, R. K. Wanchoo

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsnot available
FundersUniversity Institute of Chemical Engineering and Technology, Panjab University
KeywordsPacked bedFlow (mathematics)Materials scienceMechanicsPhysicsChromatographyChemistry

Abstract

fetched live from OpenAlex

Abstract The effect of fluid elasticity on frictional pressure drop during the flow of Boger fluids (constant viscosity elastic fluids) through packed bed of spherical and non‐spherical particles has been examined and comprehensive data on pressure drop–flow rate behaviour were generated using spheres, cylinders, triangles, and square plates as packing material to cover the sphericity range of 0.547 ≤ ɸ ≤ 1. Boger fluids used in the present study were 0.01%–0.045% wt./vol. polyacrylamide in glycerol water blends. The phenomenon of drag enhancement was observed in comparison to purely viscous fluid which follows asymptotic behaviour with elasticity number ( E = We/Re mod ). The asymptotic behaviour depicts the dominance of elasticity at low elasticity number and effect of inertia at higher Reynolds number (Re). Based on the observed experimental results, elasticity number function f ( E ), which well captures the dominance of elasticity at low E and inertial effects at higher Re, is incorporated in the existing Ergun equation (applicable to packed bed flow of purely viscous fluids) to predict the friction factor for Boger fluids. The developed correlation can adequately be applied to the available experimental data on non‐Newtonian inelastic fluids, shear thinning viscoelastic fluids, Boger fluids as well as for non‐spherical particles if the diameter of non‐spherical particle is replaced with equivalent diameter, that is, volume mean diameter times sphericity ( d p = d eq = d v ɸ ).

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.512

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 head0.195
Teacher spread0.188 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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