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Record W4323042538 · doi:10.1002/cjce.24891

Drawbacks of phase change models in simulating flashing of steam with a subsaturation downstream boundary condition

2023· article· en· W4323042538 on OpenAlexafffundvenue
Carlos F. Lange

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaRGL Reservoir ManagementCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsFlashingMechanicsTurbulenceBreakupBarotropic fluidSuperheatingMass transferNozzleComputational fluid dynamicsPhase changeMultiphase flowThermodynamicsCabin pressurizationMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Abstract The development of phase change models applicable to a wide range of temperatures, pressures, and mass flow rates is primarily limited by the metastable or partially stable behaviour of the fluid. Due to this, the fluid does not change phase even after crossing saturation conditions. Most liquid–vapour phase change models have been developed primarily for the cavitation process where the phase change is not sustained, occurs in a very narrow region of space, or occurs under equilibrium conditions. In this paper, the mechanism of phase change is discussed along with the review of three different computational fluid dynamics (CFD)‐based phase change methods available in OpenFOAM, which are used to simulate flashing of steam, in applications related to steam assisted gravity drainage (SAGD) systems. The first method is based on barotropic compressibility (BC) used with the realizable turbulence model, the second combination is of mass transfer model (MTM) with the realizable turbulence model, and the third one is based on two fluid (TF) method along with a family of turbulence models. These methods are tested on a converging–diverging nozzle with pressure driven phase change. It is demonstrated that these methods are not able to adjust their physics to different depressurization rates, do not account for liquid to be in superheated conditions, and have significant discrepancies with experimental results. In the end, better approaches to model this category of phase change are discussed.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.275

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 head0.016
GPT teacher head0.237
Teacher spread0.222 · 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 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

Citations2
Published2023
Admission routes3
Has abstractyes

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