Investigation of skin porosity damping effects on free stream disturbance induced unsteady wing loads
Bibliographic record
Abstract
Abstract Numerical simulations were performed to analyse the possibility of damping abrupt incoming free stream disturbances upon a porous aerofoil using an unsteady Reynolds-averaged Navier-Stokes (URANS) model. To mimic the turbulence disturbance levels that are typically encountered in the atmosphere, two flow configurations were considered. In the first configuration, the unsteadiness of the flow was created with vortices shed from a circular cylinder installed ahead of a WTEA-TE1 aerofoil. The continuous von Kármán shedding vortices contained within the cylinder wake were convected downstream and projected upon the aerofoil. In the second configuration, an instantaneous pair of discrete vortices was created by a rotational snapping of a flat plate, installed upstream of the aerofoil. Solid and porous aerofoil configurations, with porosity settings of 11 and 22%, were applied on 50% of the chord of the aerofoil starting from the leading edge. Both steady and unsteady flow simulations were performed to assess the performance of the porosity under steady and unsteady effects. The steady state flow simulations revealed a noticeable reduction in the aerofoil lift coefficient for the porous aerofoil. For unsteady solutions with a continuous or distinct series of vortices interacting with the aerofoil, the porosity showed insignificant damping of the lift coefficient amplitude. The porosity values investigated in the current exercise had indiscernible effect upon the unsteady lift-load alleviations caused by free stream disturbances.
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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".