Numerical Investigation of a Steam Nozzle with Focus on Non-Equilibrium Condensation and Unsteady Flow Behavior
Bibliographic record
Abstract
Present work analyses the condensation of superheated water vapor in supersonic Barschdorff nozzle. The influence of pneumatic mounts in 3D laval nozzle is analyzed using steady and unsteady two phase non-equilibrium condensation steam flow model in Ansys CFX16. Mesh independency studies in 2D model showed that at a lower inlet total temperature and very fine mesh (e.g. 100.2°C and 77k mesh elements) there is problem with the convergence using steady simulation. This is possibly due to the ability of very fine mesh to capture the small flow unsteadiness. The variation in location of Wilson’s point, Wilson’s pressure and maximum sub-cooling rate at the centerline of the nozzle is below 1.5%. The 2D CFD nucleation rate is 50% stronger and droplet diameter is 18% higher compared to the 3D CFD results. The deviation in nucleation rate and droplet diameter at nozzle outlet is the result of dissipation due to wing structure in the 3D model. Nucleation zone predicted by Ansys CFX16 is far upstream the experimental one. Different correction factors in modified nucleation model were used to fit the computed pressure distribution with the experimental one. The correction factor is dependent on boundary conditions and nozzle profile. It is thus concluded that the significance of such correction factor is not unique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".