Cavitation Inception in Crossflow Hydro Turbines
Bibliographic record
Abstract
Cavitation is a common flow phenomena in most hydraulic turbines and has the potential to cause vibration, blade surface damage and performance loss. Despite the fact that crossflow turbines have been used in small-scale hydropower systems for a long time, cavitation has not been studied in these turbines. In this paper, we present the findings of a computational study on cavitation inception in crossflow turbines. Cavitation inception was assessed using three-dimensional (3D) Reynolds-Averaged Navier–Stokes (RANS) computations. A homogeneous, free-surface two-phase flow model was used. Pressure distributions on the blades were examined for different flow rates, heads and impeller speeds to assess cavitation inception. The results showed that cavitation occurs in the second stage of the turbine and was observed on the suction side near the inner edge of the blades. For the particular turbine studied, cavitation always occurred at shaft speeds greater than that, giving the maximum efficiency for each combination of flow rate and head. The implication is that the useful operating range of crossflow turbines is up to and including the maximum efficiency point.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".