Evaluation of simultaneous effects of inlet stagnation pressure and heat transfer on condensing water-vapor flow in a supersonic Laval nozzle
Bibliographic record
Abstract
In supersonic two-phase flows of steam, under the influence of rapid expansion, the vapor becomes supersaturated. Following this condition, nucleation happens during the vapor phase; formed tiny droplets grow along the passage and, therefore, the condensation phenomenon occurs. The effects of the condensation phenomenon in power steam turbines include efficiency drop and mechanical damage. In the previous work of the authors, volumetric heating was introduced as an approach towards reducing the mentioned damage and loss. However, further investigations revealed that heating decreases the mass flow rate, which can be increased by adjusting the inlet stagnation pressure. In this paper, using a semi- analytical and a one-dimensional modeling approach, the simultaneous effects of volumetric heat transfer and inlet stagnation pressure variation are investigated in order to remedy the mass flow rate reduction. The results show that increasing the inlet stagnation pressure up to 5% can fix the mass flow rate of the non-adiabatic flow, compared to the adiabatic flow under the same conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".