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Record W2160316968 · doi:10.1109/ceidp.2003.1254951

Electrohydrodynamic pumping of vapour refrigerant bubbles in a two-phase natural circulation heat transport loop

2004· article· en· W2160316968 on OpenAlexaff
S.J. Shelestynsky, C.Y. Ching, Justin S. Chang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNuclear Engineering Thermal-Hydraulics
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsElectrohydrodynamicsMechanicsBuoyancyDragRefrigerantMaterials scienceBubbleNatural circulationThermodynamicsWorking fluidTwo-phase flowFlow (mathematics)PhysicsElectric field

Abstract

fetched live from OpenAlex

The objective of this work is to develop an enhanced two-phase thermal transport loop. In this work, an Electrohydrodynamic (EHD) device, namely an ion-drag pump is analyzed to enhance the performance of a Natural Circulation Loop (NCL). The benefit of these EHD devices is that they require no moving parts and substantial weight savings when compared with classical pumps. The enhancement can be twofold: 1) single-phase liquid pumping and 2) two-phase flow control. When the NCL is working in a subcooled off-design point, bubbles are generated due to a pressure drop. The control of bubbly flow is desired to optimize the system when it returns to the design-point operation. In a dielectric fluid such as R134a, the dielectrophoretic force on an induced dipole such as a vapor bubble can be dominant depends on the bubble diameter. When /spl alpha/ /spl ap/ 0 (r/sub b/0 (r/sub b/ > r/sub cr/) - the bubbles follow the trajectory defined by an analytical model based on a force balance between buoyancy, dielectrophoresis, and friction drag.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.005
GPT teacher head0.229
Teacher spread0.224 · 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 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

Citations4
Published2004
Admission routes1
Has abstractyes

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Same topicNuclear Engineering Thermal-HydraulicsFrench-language works237,207