Development and validation of new cryogenic cavitation model for rocket turbopump inducer
Bibliographic record
Abstract
A rocket propellant is often used cryogenic fluid such as liquid hydrogen or liquid oxygen, and it is known that a suction performance of turbopump inducer (Fig.1) in cryogenic fluid is improved due to Thermodynamic effect . Thermodynamic effect can be explained by temperature decrease inside a cavity region arising from the latent heat absorption. Although this effect is also to be observed in water cavitation, it becomes more accentuated in cryogenic fluid. In order to properly understand the cavitation performance of the inducer, this thermodynamic effect should not be overlooked. In the present study, cryogenic cavitation model without energy equation was established. During the design phase of an inducer, wall clock time of CFD simulation becomes an important point, therefore, equation number should be small. The present model considers that temperature decrease due to latent heat absorption is analytically estimated. Validation calculations were carried out for blunt head form and hydrofoil for water cavitation and two-dimensional blunt body, Laval nozzle and inducer for cryogenic fluids.
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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".