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Record W1628246506 · doi:10.1139/cjp-2014-0195

Magnetohydrodynamic flow of Newtonian fluid in a scraped surface heat exchanger

2015· article· en· W1628246506 on OpenAlexvenueno aff
A. M. Siddiqui, Muhammad Ali Imran, Muhammad Zeb, M. A. Rana

Bibliographic record

VenueCanadian Journal of Physics · 2015
Typearticle
Languageen
FieldEngineering
TopicFreezing and Crystallization Processes
Canadian institutionsnot available
Fundersnot available
KeywordsMechanicsPhysicsNewtonian fluidIsothermal flowMagnetohydrodynamic driveFlow (mathematics)Open-channel flowHeat exchangerFluid dynamicsNon-Newtonian fluidTransverse planeMagnetohydrodynamicsClassical mechanicsThermodynamicsMagnetic field

Abstract

fetched live from OpenAlex

This paper aims to study a mathematical model of electrically conducting incompressible Newtonian fluid flow in a scraped surface heat exchanger in the presence of a transverse magnetic field. In our case the gap between the blades and the device wall is narrow so lubrication theory approximations work for the flow. Steady isothermal flow of an electrically conducting Newtonian fluid is considered around a periodic array of pivoted scraper blade in a channel in which the lower wall is moving and the upper wall is at rest. Two-dimensional flow in the transverse section of a scraped surface heat exchanger is taken. Details of the flow properties, including the possible presence of regions of reversed flow under the blades, the forces on the blades and walls, and the fluxes of fluid above and below the blades are calculated. Graphic representation for involved flow parameters is also given.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.191
Teacher spread0.177 · 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 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
Published2015
Admission routes1
Has abstractyes

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