Developing a Mathematical Model to Predict the Behavior of a Supersonic Superheated Steam Flow inside a Laval Nozzle
Bibliographic record
Abstract
The objective of the investigation was to mathematically correlate the behavior of a supersonic superheated steam flow inside a Laval nozzle, against the decision parameters. The decision parameters are the inlet temperature ranging from 374.3 K to 504.3 K and the inlet pressure from 40050.14 Pa to 133375.7 Pa. Indeed, the outlet temperature, outlet pressure as well as the Mach number are mathematically correlated against the decision parameters. The numerical approach based on the Computational Fluid Dynamics (CFD) is selected to study the behavior of the supersonic superheated steam flow inside the nozzle. By examining the different temperature and pressure conditions of the inlet fluid, it was found that the closest distance from the starting point of condensation to the throat is at the highest pressure and lowest temperature. Conversely, the farthest distance from the starting point of condensation to the throat is at the lowest pressure and highest temperature. In addition, three mathematical correlations were developed. Due to the high accuracy of the mathematical correlations, the efficiency of the predictor models in predicting the outputs was proved.
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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 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".