The Prediction of Condensation Characteristics of Supercritical Carbon Dioxide in the Laval Nozzle During Supersonic Flow
Bibliographic record
Abstract
Abstract The non-equilibrium condensation and nucleation process contribute to enormous challenges to accurately predict the condensation behaviors in rotating machines. Considering the similarity of flow, the analysis of the condensation characteristics in the Laval nozzle is the basis for the study in the compressor. In this paper, an Eulerian-Eulerian Source term (EES) numerical model is developed to investigate non-equilibrium condensation features in supersonic compressible flow in nozzle. High precision real gas property table is introduced to calculate the thermophysical properties of CO2 in nozzle. The difference of droplet distribution and liquid fraction between EES model and homogeneous equilibrium (HEM) model is discussed. The relationships between inlet parameters, condensation site and nucleation rates are also analyzed. The numerical analysis result shows that although the prediction deviation of EES model and HEM model at outlet temperature and pressure is less than 3%, the liquid mass fraction at the outlet of HEM model is 12% larger than that of EES model. Shock wave of supersonic flow causes the forward movement of condensation site in HEM model, indicating that HEM model might overestimate condensation characteristics and aerodynamic effects in the nozzle. Decreasing the inlet pressure and increasing the inlet temperature delay the occurrence of condensation and reduce the liquid mass fraction, but could also bring about the increase of the droplet average radius at the outlet. These results provide valuable suggestions in the analysis of non-equilibrium condensation characteristics of supersonic flow and the design of compressor inlet conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".