Increasing Boiling Fluid Flowing Efficiency from Motive Nozzles of Two-Phase Ejectors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The article contains the possibility of increasing boiling fluid flowing efficiency from expanding channels. This process takes place in the motive flow nozzle of a liquid-vapor ejector, working on the principle of thermal stream compression. Efficiency increasing by profiling the diffuser part of the nozzle. Modern industry uses nozzles, which are like de Laval nozzles, with straight walls of the diffusers. The authors suggest paying closer attention to profiling these nozzles, which might increase their efficiency and improve their gas-dynamic characteristics. For comparison, we choose a channel of a traditional form (with straight walls of the diffuser) and a channel of parabolic shape. The article contains a mathematical model to calculate the process of flowing the boiling fluid from the authors-designed channels – the peculiarities of this model that appear after changing the geometry of its streaming part. We obtain comparative analysis calculation results based on the mathematical model and the Ansys CFX workflow model. As a result of numerical calculation using the authors mathematical model and modelling in the Ansys CFX software package, it concludes that the parabolic shape of the diffuser is the most favourable. In the boiling process, the liquid central core is boiling at the optimum distance from the nozzle throat, and the flow of a stable vapor structure with the required pressure value for each regime forming at the outlet.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it