A Porous Media Function That Mimics the Effect of Discrete Holes
Bibliographic record
Abstract
Simulating full-coverage film cooling remains an elusive task for aerodynamicists given the small scale of the holes relative to the duct size where the holes are applied. Source term models were developed to simulate the effect through a perforated surface; however, the documented approaches failed to adequately describe how source term locations within the computational domain were selected. This paper presents a continuous ‘checker-board’ surface function that enables a distributed selection of cells where the source terms are applied; furthermore, the source term strengths applied to cells within a given hole are weighted. A 3:1 aspect ratio S-duct with an 1.5 area ratio exhaust diffuser, and 4% porosity applied to the upstream convex bend was evaluated. Steady-RANS obtained with the realizable k-ε model and source terms derived based on the approach of Andreini et al. (2014) had good pressure distribution, outlet velocity, and coolant mass flow agreement with respect to experiment when the hole diameter was resolved with two nodes. Reducing the computational domain element count by 75% and simulating hole diameters 2.8-times larger with 4% surface porosity gave back pressure and outlet distortion coefficients within grid uncertainty of the finest grid solution; however, local-convex-surface-averaged quantities showed grid dependency.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".