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Record W4408290380 · doi:10.1063/5.0254823

Non-equilibrium condensation modeling of CO2 nozzle flow under subcritical and supercritical conditions

2025· article· en· W4408290380 on OpenAlexaboutno aff
Junbin Chen, Cong Guo, Chunyu Feng, Xiao Qu, Sicong Tan, Wan Sun, Yuyan Jiang

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsPhysicsSupercritical fluidNozzleCondensationMechanicsFlow (mathematics)Supercritical flowThermodynamicsStatistical physicsClassical mechanics

Abstract

fetched live from OpenAlex

Turbomachinery is crucial in transcritical CO2 heat pumps and supercritical CO2 Brayton cycles. During the internal transcritical expansion process, non-equilibrium condensation can occur, leading to droplet formation, which reduces turbomachinery efficiency and may damage the blades. Currently, non-equilibrium condensation calculations face inaccurate predictions of condensation shock waves and downstream pressures. To investigate the influence of various factors on the accuracy of non-equilibrium condensation numerical simulation, this study examines the effects of nucleation models, droplet growth models, and turbulence models. The Eulerian–Eulerian source term model is employed to compare and study the non-equilibrium condensation within a CO2 Laval nozzle under subcritical and supercritical inlet conditions. The results indicate that different nucleation models directly affect the numerical accuracy of the nucleation location and the condensation shock wave, with minimal impact on the pressure distribution downstream of the throat. Besides, different droplet growth models have little effect on the numerical accuracy of nucleation location and the downstream pressure distribution. The large eddy simulation has a significant impact on numerical accuracy, with a larger pressure jump and better experimental agreement for downstream pressure distribution. These findings provide guidance for the further development of non-equilibrium condensation models.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.451

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 head0.024
GPT teacher head0.308
Teacher spread0.283 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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