Direct numerical simulation of installation effects on airfoil noise
Bibliographic record
Abstract
To evaluate installation effects on velocity statistics and its influence on farfield noise, three Direct Numerical Simulations (DNS) have been run using the Lattice-Boltzmann Method with the PowerFLOW software on the Controlled-Diffusion (CD) airfoil at a Reynolds number of 150 000 and 8 degrees angle of attack installed in the Universite de Sherbrooke (UdeS) wind tunnel. Differences in setup between these DNS simulations are the addition of voxel refinements and turbulent trips to the simulation setup for better capturing of the jet shear layer downstream of the wind tunnel nozzle lip. Results show that the airfoil boundary layer displacement thickness, momentum thickness and shape factor are slightly increased after jet shear layer refinement due to an increase in mean angle of attack caused by a change in shear layer state. Despite these changes caused by the mixing layer state, maximum Reynolds stress magnitude near the trailing edge of the airfoil was changed by only 6%. This indicates that adjustments to the wall pressure statistics which are relevant to trailing edge noise generation was only marginal. As such, changes to boundary layer statistics had limited impact on far-field noise in the mid-frequency range in this operating state. • Changes to the jet shear layer caused an increase in time-averaged angle of attack. • Stronger adverse pressure gradient were triggered, thickening boundary layer at trailing edge • Peak Reynolds stress magnitude increased marginally by 6% at the trailing edge. • Change in trailing edge noise was slight and was overshadowed by stronger secondary noise sources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".