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Record W2962594411 · doi:10.18280/ejee.210207

Numerical Study of Electro-convection and Electro-thermo-convection in Solar Chimney Geometry

2019· article· en· W2962594411 on OpenAlexvenueno aff
R. Gannoun, Walid Hassen, Alberto T. Pérez, Mohammed Naceur Borjini

Bibliographic record

VenueEuropean Journal of Electrical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSolar chimneyConvectionMechanicsChimney (locomotive)Convection zoneCombined forced and natural convectionNatural convectionMaterials scienceAtmospheric sciencesMeteorologyEnvironmental sciencePhysicsThermodynamics

Abstract

fetched live from OpenAlex

In this article, a numerical study was conducted to analyze the effect of electro-convection and electro-thermo-convection in a solar chimney geometry subjected to the simultaneous action of an electric field and a thermal gradient (in the case of electro-thermo-convection).The full set of equations is solved using the finite element software COMSOL Multiphysics.The effects of thermal and electric Rayleigh numbers on charge density distribution, fluid flow and temperature distribution are analyzed.Also the impact of different chimney collector widths is studied in order to determine the optimum width allowing achieving the maximum fluid velocity.It was shown that using a smaller chimney collector width is more convenient in order to increase the fluid flow velocity.In addition, an evaluation of the heat transfer enhancement was made by observing the evolution of heat flow at the exit of the chimney tower as a function of both, the electric and thermal Rayleigh numbers.It was found that the heat transfer enhancement reaches more than 90 % when thermal Rayleigh rises from 5000 to 20000.Finally, the effect of Prandtl number was investigated.

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.164
Teacher spread0.161 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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Same venueEuropean Journal of Electrical EngineeringSame topicSolar Energy Systems and TechnologiesFrench-language works237,207