Numerical Study on the Nucleation Law of Water Vapor Condensation in Laval Nozzle
Bibliographic record
Abstract
In order to explore the formation of condensed droplets and the process of agglomeration into droplets during the gas-liquid separation in the Laval nozzle, the wet gas is taken as the research object, and the numerical simulation model and control equations for the condensation of wet gas are established, which are simulated by Fluent software the effects of three parameters, the inlet relative humidity, the inlet and outlet pressure ratio and the inlet temperature, on the law of water vapor condensation and nucleation in the supersonic nozzle were analyzed. The results show that the higher the relative humidity is, the greater the peak value of the nucleation rate is, and the location of water vapor nucleation is getting closer to the throat of the nozzle; as the pressure ratio increases, the peak value of the nucleation rate becomes larger, and the pressure ratio is It has an impact on the peak value of the nucleation rate; the lower the inlet temperature, the greater the peak value of the nucleation rate, and the inlet temperature has the greatest influence on the nucleation rate. When the inlet temperature is 285K, the nucleation rate reaches the maximum value and the nucleation position is closest to Throat, that is, the time of nucleation is the shortest, and the position of nucleation is the most forward. Therefore, in the actual application process, the length of the expansion section can be adjusted by the relative humidity of the wet gas, and the equipment can be simplified; at the same time,the dehydration efficiency of the Laval nozzle can be improved by increasing the inlet and outlet pressure ratio or reducing the inlet temperature of the nozzle.
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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 | 0.000 | 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) | 0.004 | 0.003 |
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; both teacher heads agree on what is shown here.
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".