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Record W2997750286 · doi:10.2514/6.2020-1935

Swirling Flow Patterns through Refrigerator Vortex Tubes

2020· article· en· W2997750286 on OpenAlexaboutno aff
Mahmoud AbdelGhafaar, Karam R. Beshay, Gamal ElHarriri, Essam E. Khalil

Bibliographic record

VenueAIAA Scitech 2020 Forum · 2020
Typearticle
Languageen
FieldEngineering
TopicRanque-Hilsch vortex tube
Canadian institutionsnot available
Fundersnot available
KeywordsVortex tubeVortexVortex generatorRefrigerator carMechanicsTube (container)Axial compressorMechanical engineeringTurbulenceHeat transferHeat exchangerFlow (mathematics)NozzleVortex ringMaterials sciencePhysicsEngineeringGas compressor

Abstract

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Swirling Flow Patterns through Refrigerator Vortex Tubes Mahmoud M. Abdelghfar1, Karam R. Beshay2, Gamal Elhariry3 and Essam E. khalil2, 1Teaching Assistant, Faculty of Engineering, Ahram Canadian University, Cairo, Egypt 2Professor, Mechanical Power Engineering Department, Faculty of Engineering, Cairo University, Cairo, Egypt 3Associate Professor, Mechanical Engineering Department, Faculty of Engineering, Cairo University, Cairo, Egypt ABSTRACT It is well recognized that the swirling flow enhance heat transfer of fluids flowing in tubes and that refers to excessive turbulence, mixing, and secondary circulations formed by the radial body force when desirable density gradients are existing. Production of swirl flow can be reached by various methods such as looped wires, helical fins, coiled pipes, twisted tapes and inlet vortex generators. When comparing the swirl flow and the axial flow at constant compressing work shows that about a 20% rise in heat transfer amount can be gained with the swirling flow. Swirl flow in refrigerator vortex tubes has dissimilar flow characteristics from those mentioned due to temperature separation effect taking occurs within the vortex tube. The refrigerator vortex tube is non-complicated apparatus that working as an energy splitting device with no rotating parts. It mainly consists of a metal or non-metal tube. In this device compressed air is directed circumferentially with a high kinetic energy towards the vortex generator. While the gas swirls speedily through the vortex tube, energy separation process takes place there. Exact near the entrance nozzle (s) a cold air stream moves leaving the main tube through the cold vent, while at the other end of the tube a warm air stream finishes adjacent the tube wall. Separation effect is referring to the point appears due to air flow against pressure and the particles have lower kinetic energy (swirling flow momentum) can’t resist the pressure gradient and back towards the lower pressure zone at the cold exit and get cooled and accelerated while moving back. This phenomenon of temperature separation in the vortex tube was earliest informed by the Georges J. Ranque and first publishing was by Rudolf Hilsch who introduced experimental findings by fluctuating introducing pressure and geometrical aspects of vortex tubes. Their great work resulted in that this device is usually linked to their names as Hilsch- Ranque vortex tube. To investigate the nature and effects of the swirling flow inside refrigerator vortex tube, a three dimensional flow field of counter flow type is computer-generated using Ansys CFD package. Using three-dimensional simulation is not usually related to accuracy. Three-dimensional simulations are more real than two dimensional simulations. It expected that the central layer of third dimension is quite similar to that attained by two-dimensional simulations, but not essentially to the external layers of 3D shape. The 3-D simulation is highly important in some cases. For example, in case of simulating the turbulence and want to capture the all the features of turbulence then 3-D simulation must be applied to avoid symmetry imposing in turbulent structures. 3D computations accurately express the real gas flow study case, and 2D simulations are usually applied by assuming that the net mass flow in one or more of the spatial dimensions is zero and no convective terms are predicted in that direction, and the surface and body forces affect in that direction are neglected in 3D computations you can defined the actual values.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.204
Teacher spread0.194 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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