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ICONE23-1731 NUMERICAL ASSESSMENT AND COMPARISON OF HEAT TRANSFER CHARACTERISTICS OF SUPERCRITICAL WATER IN BARE TUBES AND TUBES WITH HEAT TRANSFER ENHANCING APPENDAGES

2015· article· en· W2714852938 on OpenAlexaff
Amjad Farah, Glenn Harvel, Igor Pioro

Bibliographic record

VenueThe Proceedings of the International Conference on Nuclear Engineering (ICONE) · 2015
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsHeat transferMechanicsTurbulenceBody orificeSupercritical fluidComputational fluid dynamicsFluid dynamicsThermodynamicsFluentMaterials scienceComputer simulationPhysicsMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Computational Fluid Dynamics (CFD) is a numerical approach to model fluids in multidimensional space using the Navier-Stokes equations and databases of fluid properties to arrive at a full simulation of a fluid dynamics and heat transfer system. A numerical study on heat transfer to supercritical water (SCW) flowing in a vertical tube is carried out using the ANSYS FLUENT code and employing the SST k-ω turbulence model. The 3D mesh consists of a 1/8 section (45 ° radially) of a bare tube. The numerical results on wall temperature distributions under normal and deteriorated heat transfer conditions are compared to experimental results. The same geometry is then simulated with an orifice to study the effect of geometrical perturbation on the flow and heat transfer characteristics of SCW. The orifice is placed areas to test the effect on normal, deteriorated and enhanced heat transfer regimes. The flow effects and heat transfer characteristics will be studied around the appendages to arrive at a fundamental understanding of the phenomena related to supercritical water turbulence.

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 score0.170
Threshold uncertainty score0.524

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 head0.026
GPT teacher head0.251
Teacher spread0.225 · 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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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