A Numerical Study of an Impingement Array Inside a Three Dimensional Turbine Vane
Bibliographic record
Abstract
A simplified impingement high pressure turbine vane is modeled and solved via Fluent. A relatively flat section of the vane is fitted with 15 0.51mm diameter impingement holes — 5 rows of 3 jets. Results are then compared to known experimental data. Two different turbulence models are used to study this preliminary configuration: K-omega SST and the RNG k-epsilon model. The jet exit Reynolds numbers, cross flow velocity, and the average and local heat transfer distribution are analyzed with varying Reynolds numbers and jet to target spacing. It is observed that the static pressure decreases across the vane with the cross flow velocity increasing towards the trailing edge exit, thereby uniformly increasing the jet exit velocity at each row. Forced convection is seen in the downstream rows in-between span-wise jets due to high cross flow velocities. All numerical results were capable of replicating the higher heat transfer obtained with a higher Reynolds number, and conversely, a lower heat transfer with an increase in jet to target spacing. In its entirety, validating against all correlations, the RNG model obtained an average deviation of 15.7%, while the K-omega SST yielded only 7.8%.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".