Effect of Inlet Temperature on Supersonic Liquefaction Characteristics of Natural Gas
Bibliographic record
Abstract
To reveal the effect of inlet temperature on the supersonic liquefaction characteristics of natural-gas mixtures, a mathematical model for the supersonic condensation flow of two-component natural gas mixtures was established in this study. The spontaneous condensation process of methane-ethane mixed gas in a Laval nozzle at different inlet temperatures was studied. The results indicate that when the inlet pressure and gas composition of the Laval nozzle remained the same, with the decrease in the inlet temperature, the nucleation position of the mixed gas moved forward; the nucleation rate, droplet radius, droplet number, and liquid mass fraction were all increased; and the liquefaction characteristics was improved. By using the Laval nozzle structure designed in this study, inlet gas pressure of 6 MPa, inlet gas temperature of 265 K, methane content of 90% and ethane content of 10% resulted in maximum nucleation rate of 0.9822×1021 (m3?s)?1 in the Laval nozzle, maximum droplet radius of 4.7194×10?7 m, maximum droplet number of the unit mass of 5.0704×1014 kg?1, and maximum liquid mass fraction of 7.8121%. The liquefaction efficiency of the Laval nozzle sharply decreased when the inlet temperature was higher than 275 K. In an actual production, the liquefaction efficiency of the Laval nozzle can be improved by lowering the inlet temperature and reducing the heat exchange between the Laval nozzle and outside environment.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 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".