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Record W1519146079 · doi:10.5772/13792

Heat Transfer to Supercritical Fluids

2011· book-chapter· en· W1519146079 on OpenAlexaff
Igor Pioro, Sarah Mokry

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsSupercritical fluidHeat transfer fluidHeat transferMaterials scienceThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Deteriorated Heat Transfer (DHT) is characterized with lower values of the wall heat transfer coefficient compared to those at the normal heat transfer; and hence has higher values of wall temperature within some part of a test section or within the entire test section. Improved Heat Transfer (IHT) is characterized with higher values of the wall heat transfer coefficient compared to those at the normal heat transfer; and hence lower values of wall temperature within some part of a test section or within the entire test section. In our opinion, the improved heat-transfer regime or mode includes peaks or "humps" in the heat transfer coefficient near the critical or pseudocritical points. Normal Heat Transfer (NHT) can be characterized in general with wall heat transfer coefficients similar to those of subcritical convective heat transfer far from the critical or pseudocritical regions, when are calculated according to the conventional single-phase Dittus-Boelter-type correlations: Nu = 0.0023 Re 0.8 Pr 0.4 . Pseudo-boiling is a physical phenomenon similar to subcritical pressure nucleate boiling, which may appear at supercritical pressures. Due to heating of supercritical fluid with a bulk-fluid temperature below the pseudocritical temperature (high-density fluid, i.e., "liquid"), some layers near a heating surface may attain temperatures above the pseudocritical temperature (low-density fluid, i.e., "gas") (for specifics of thermophysical properties, see Chapter "Thermophysical Properties at Critical and Supercritical Conditions"). This low-density "gas" leaves the heating surface in the form of variable density (bubble) volumes. During the pseudo-boiling, the wall heat transfer coefficient usually increases (improved heat-transfer regime). Pseudo-film boiling is a physical phenomenon similar to subcritical-pressure film boiling, which may appear at supercritical pressures. At pseudo-film boiling, a low-density fluid (a fluid at temperatures above the pseudocritical temperature, i.e., "gas") prevents a highdensity fluid (a fluid at temperatures below the pseudocritical temperature, i.e., "liquid") from contacting ("rewetting") a heated surface (for specifics of thermophysical properties, see Chapter "Thermophysical Properties at Critical and Supercritical Conditions"). Pseudofilm boiling leads to the deteriorated heat-transfer regime. Water is the most widely used coolant or working fluid at supercritical pressures. The largest application of supercritical water is in supercritical "steam" generators and turbines, which are widely used in the power industry worldwide Currently, upper limits of pressures and temperatures used in the power industry are about 30 -35 MPa and 600 -625C, respectively. New direction in supercritical-water application in the power industry is a development of SuperCritical Water-cooled nuclear Reactor (SCWR) concepts, as part of the Generation-IV International Forum (GIF) initiative. However, other areas of using supercritical water exist Supercritical carbon dioxide was mostly used as a modelling fluid instead of water due to significantly lower critical parameters (for details, see Chapter "Thermophysical Properties at Critical and Supercritical Conditions"). However, currently new areas of using supercritical carbon dioxide as a coolant or working fluid have been emerged

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score1.000

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.218
Teacher spread0.198 · 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
GenreOther

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

Citations15
Published2011
Admission routes1
Has abstractyes

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