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Record W2610393021 · doi:10.1139/tcsme-2006-0036

GENERALIZATION OF AN ANALYTICAL TWO-PHASE STEAM FLOW CALCULATOR TO HIGH-PRESSURE CASES

2006· article· en· W2610393021 on OpenAlexvenueno aff
M.J. Kermani, M. Zayemouri

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicNuclear Engineering Thermal-Hydraulics
Canadian institutionsnot available
Fundersnot available
KeywordsStagnation temperatureThermodynamicsStagnation pressureCondensationReal gasMechanicsInflowFlow (mathematics)Vapor pressureMaterials scienceHeat transferChemistryPhysicsStagnation pointMach number

Abstract

fetched live from OpenAlex

Extension of a recently developed analytical two-phase steam flow calculator to high pressure cases is performed in this paper. The initial solution, obtained in earlier study was developed for low pressure cases. In low pressure cases, the vapor portion of the two-phase mixture reliably obeys the ideal gas Equation of State (EOS). In the present high pressure study, real gas effects are included using the more suitable EOS of “Lee-Kesler”. The model similar to the low pressure model assumes local equilibrium between the phases, in which condensation onsets as soon as the saturation line is closed. Before the condensation onset, the stagnation properties echo those at the inflow. However, beyond the condensation onset, the transfer of latent heat toward the vapor portion of the two-phase mixture rises its stagnation temperature. To evaluate this rise in the vapor portion stagnation temperature, a non dimensional parameter ζ is defined. Comparison for low- and high-pressure cases between the present analytical solution and the published experimental values in the literature show very good agreement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.224
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicNuclear Engineering Thermal-HydraulicsFrench-language works237,207