Numerical investigation of transition in a boundary layer subjected to favourable and adverse streamwise pressure gradients and elevated free stream turbulence
Bibliographic record
Abstract
Laminar-to-turbulent transition of a boundary layer subjected to streamwise pressure gradients and elevated free stream turbulence is computed through direct numerical simulation. The streamwise pressure distribution and elevated free stream turbulence levels mimic the conditions present on the suction side of highly-cambered airfoils. Longitudinal streamwise streaks form in the laminar boundary layer through the selective inclusion of low-frequency disturbances from the free stream turbulence. The spanwise spacing normalized by local inner variables indicates stabilization of the streaks occurs by the favourable pressure gradient and prevents the development of secondary streak instability modes until downstream of the suction peak. Two distinct processes are found to trigger transition to turbulence in the adverse pressure gradient region of the flow. One involves the development of varicose secondary instability of individual low-speed streaks that results in their breakdown and the formation and growth of discrete turbulent spots. The other involves a rapid amplification of free stream disturbances in the inflectional boundary layer in the adverse pressure gradient region that results in a largely homogeneous breakdown to turbulence across the span. The effect of high-frequency free stream disturbances on the streak secondary instability and on the nonlinear processes within the growing turbulent spot are analysed through the inviscid transport of instantaneous vorticity. The results suggest that free stream turbulence contributes to the growth of the turbulent spot by generating large strain rates that activate vortex-stretching and tilting processes within the spot.
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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".