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Record W2175073397 · doi:10.1115/icone22-30137

Improvement of Supercritical Water Heat-Transfer Correlations for Vertical Bare Tubes

2014· article· en· W2175073397 on OpenAlexaff
Sarah Mokry, Igor Pioro

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsSupercritical fluidHeat transferCoolantThermodynamicsNuclear engineeringConvective heat transferMaterials scienceCritical heat fluxHeat transfer coefficientConvectionMechanicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Currently, there are a number of Generation IV SuperCritical Water-cooled nuclear Reactor (SCWR) concepts under development worldwide. These high temperature, high pressure reactors will have much higher operating parameters compared to current Nuclear Power Plants (NPPs) (i.e., steam pressures of about 25 MPa and steam outlet temperatures up to 625°C). Additionally, SCWRs will have a simplified flow circuit in which steam generators, steam dryers, steam separators, etc. will be eliminated. In support of developing these SCWRs, studies are currently being conducted for heat transfer at supercritical conditions. Currently, there are no experimental datasets for heat transfer at supercritical conditions from power-reactor fuel bundles to a coolant (water) available in open literature. Therefore, for preliminary calculations, heat-transfer correlations obtained with bare-tube data can be used as a conservative approach. A number of empirical generalized correlations, based on experimentally obtained datasets, have been proposed to calculate Heat Transfer Coefficients (HTCs) in forced convective heat transfer for various fluids, including water at supercritical pressures. There have been a number of methods applied to correlate heat transfer data. The most conventional approach is to modify the classical Dittus-Boelter correlation for forced convection. The Bishop et al. correlation is an example of this type modification with an addition of an entrance-region term. The Mokry et al. correlation (2009) was developed as a Dittus-Boelter-type correlation with thermophysical properties taken at a bulk-fluid temperature. The derived correlation has shown a good fit for experimental data at supercritical conditions within a wide range of operating conditions in normal and improved heat-transfer regimes. This correlation has an uncertainty of about ±25% for HTC values and about ±15% for calculated wall temperature. However, this correlation does not take into account the entrance-region effect. The objective of this paper is an investigation of the entrance-region effect to be incorporated into the proposed Mokry et al. correlation (2009) in an attempt to further improve its accuracy.

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 score0.429
Threshold uncertainty score0.660

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)0.0010.000

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 head0.009
GPT teacher head0.214
Teacher spread0.206 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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