Bibliographic record
Abstract
The steady tip vortex flow of a marine propeller governed by Reynolds-Averaged Navier Stokes (RANS) equations was numerically simulated. The RANS equations were solved by a commercial RANS code, ANSYS-CFX. The k - ∊ turbulence model and the shear stress transport (SST) turbulence model were applied in the computation. A spiral-like computational domain was set up as one blade-to-blade passage with two side/periodic boundaries. The grid was formed by following the inlet flow angle so that the clustered grid can be aligned with the tip vortex. -- Validation studies had been carried out for a uniform flow past the rotating David Taylor propeller model. In the computation, the effect of grid resolution was first investigated. Three computational grids with different minimum Jacobian, minimum volume and minimum skew angle were used. The k - ∊ and the SST turbulence models were then applied. The numerical results were validated by comparing with the experimental results and other numerical solutions. It has been demonstrated that the CFX RANS solver with two-equation turbulence models is able to predict the viscous tip vortex flow accurately. The effect of the k - ∊ and the SST turbulence models on the solution is insignificant.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".