Investigation of Heat Transfer and Vortex Dynamics in Relation to Film Cooling Effectiveness of Cratered Injection
Bibliographic record
Abstract
A thorough numerical analysis of of cratered injection holes which are frequently seen in turbine blades with thermal barrier coatings (TBCs)-is presented in the current research.During the TBC application process, injection holes are typically masked, resulting in a characteristic cratered geometry where the hole is surrounded by a raised layer of coating.This alteration in surface topology is expected to influence the flow behavior and cooling effectiveness compared to standard cylindrical holes.The objective of this research is to evaluate the influence of such cratered geometries on film cooling effectiveness and associated vortex dynamics.Threedimensional simulations are performed using the k-ε to resolve the flow field and thermal characteristics.The study is conducted at a fixed mainstream Reynolds number, based on the freestream velocity and hole diameter.Film cooling effectiveness is evaluated for both cylindrical and off-centered forward cratered (OCFC) holes across three blowing ratios (BR): 0.6, 1.0, and 1.4.Air is used as the coolant, maintaining a density ratio of 1.14.The results indicate that cratered holes consistently yield higher area-averaged film cooling effectiveness in comparison to cylindrical holes.The enhancement is attributed to the altered vortex structures and improved lateral spreading of the coolant film induced by the crater geometry.The most significant performance gain is observed at BR = 1.0 with lower vorticity, where cratered holes exhibit up to a 48% improvement in cooling effectiveness.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".