Numerical Simulation of Flow Field in the Laval Nozzle Based on Euler Equation
Bibliographic record
Abstract
Abstract A nozzle is a versatile fluid device that is utilized to control the characteristics of a fluid flow. In order to enhance the performance or better the design of the nozzle, it is critical to carry out extensive research into its inner flow. Thus, the investigation of the nozzle flow remains an important challenge. This article used a numerical simulation method based on Euler equations to solve the internal flow of the divergent, convergent-divergent, and convergent nozzles. Specifically, we simplify all three equations of the one-dimensional Euler equation (the continuity equation, the momentum equation, and the energy balance equation) by assuming a constant nozzle shape, then discretizing them using a central differential scheme. After conducting systematic research on the influence on the internal nozzle flow due to the change of nozzle shape, we found that the mass flow rate varied as it fluctuated and peaked at the middle point of the Laval nozzle. However, with the nozzle becomes flatter, the mass flow rate appeared to restore conserved. Moreover, it appeared that the flatter the Laval nozzle is, the smaller acceleration and smaller decrease of the pressure of the fluid flow gets. In short, the results suggested that it is dependable to apply this numerical method when analysing a relatively flat Laval nozzle.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".