Aerodynamic Characterization of Irregular Undulating (Stochastic) Surface Roughness
Bibliographic record
Abstract
Aerodynamic characterization of the roughness is essential to enable computation of flows over rough surfaces. Most roughness of practical interest is stochastic, that is, irregular and undulating. Examples include corrosion or deposits on turbomachinery blading or contamination on aircraft wings. This paper presents the first available method for aerodynamic characterization of stochastic surface roughness. A semi-empirical correlation approach is used. Simple physically meaningful roughness-topography characterization parameters that are suitable for both stochastic and deterministic (i.e., regular arrays of simple elements) roughness are proposed. These parameters can be evaluated from profilometer traces or laser scans of rough surfaces. Measurements of boundary-layer development along five stochastically rough surfaces are presented and are used, together with data from the literature for standard-sand roughness and deterministic roughness, to develop a unified characterization scheme that predicts the aerodynamic effects of both stochastic and deterministic roughness. The characterization scheme yields the effect of the roughness on the law-of-the-wall; this can easily be converted to an equivalent standard-sand roughness height for input to computational fluid dynamics codes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".