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On Distribution of Local Thermal and Mass Flow Rate Parameters of Two-Phase Coolant in the Bundle of 7 Rods

2012· article· en· W2016608612 on OpenAlexaff
V. A. Dalipagich, E. M. Mayevskiy, V. G. Razumovskiy, Eugene Pis’mennyi, A. E. Koloskov, Igor Pioro

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsBundleSubcoolingCoolantMechanicsMaterials scienceMass flow rateMass fluxThermal hydraulicsHydraulic diameterVolumetric flow rateThermodynamicsRodHeat transferMass flowHeat fluxReynolds numberPhysicsComposite material

Abstract

fetched live from OpenAlex

Distribution of thermal and mass flow rate parameters of coolant in the cross-section of 7-rod bundle consisting of the tubes of 6.0-mm outside diameter and 1.0-m heated length for two types of discretization of its cross-section into characteristic cells is experimentally investigated by the method of isokinetic sampling. The range of operation parameters corresponds to the conditions of LOCA accompanied by pressure and flow rate decrease relative to the nominal ones and is as follows: bundle-averaged outlet vapor content varies from −0.6 to 0.2, outlet pressure is 6 and 10 MPa, bundle-averaged mass velocity varies from 300 to 1500 kg/(m2s), inlet temperature varies from deep subcooling to (ts − 20) °C, and heat flux rate reaches 1.0 kJ/kg. It is confirmed by the experiment that the surface in the gap between the peripheral rods is most probable place of burnout in the bundle. Physical model of two-phase flow in the bundle that considers it as the equivalent annular channel with an eccentricity is proposed. The programs of thermal-hydraulic computation of fuel assembly and their adaptation to the experimental data for the two types of discretization into characteristic cells are performed and comparative assessment of them is made. The data resulted from the study concerning one-phase coolant could be applicable for a reference estimation of heat transfer in future designs of the fuel bundles.

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 score0.200
Threshold uncertainty score0.158

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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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