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Record W2898506052 · doi:10.1115/icone26-81045

CFD Analysis of Supercritical-Water Flow and Heat Transfer in Vertical Bare Tube

2018· article· en· W2898506052 on OpenAlexaff
Anastasiia Zvorykina, Dmytro Khmil, Наталія Фіалко, Igor Pioro, Svitlana Stryzheus

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsTurbulenceMechanicsBuoyancyComputational fluid dynamicsHeat transferMaterials scienceThermodynamicsSupercritical fluidHeat transfer coefficientHeat fluxFluentPhysics

Abstract

fetched live from OpenAlex

In this paper CFD analyses of mixed convection in bare tubes cooled with water at supercritical pressure is presented. The study was carried out using the FLUENT code for upward flow in vertical tubes with a heated length of 4 m and an inside diameter of 10 mm at relatively low water mass flux (G ≈500 kg/m2s) and heat fluxes q (from 239 to 310 kW/m2). Various models of turbulence have been tested. The results of the studies demonstrated a reasonable good agreement between CFD predictions and experimental data on the heat transfer coefficient and internal-wall temperature with use the SST turbulence model. Comparison of the CFD simulation data, which correspond to the presence or absence of the buoyancy forces, was performed. The regularities of the influence of these forces on the damping of turbulent transport, the deformation of the radial profiles of velocity and temperature along the channel length, the reduction of the heat transfer coefficients, etc. were studied. The features of the motion of the pseudo-phase transition within various conditions are presented.

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 categoriesInsufficient payload (model declined to judge)
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 score0.149
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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.

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

Citations2
Published2018
Admission routes1
Has abstractyes

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