Turbulent separations around a slanted-back Ahmed body with square and rounded leading edge
Bibliographic record
Abstract
An experimental study was conducted to study the effects of rounded (RL) and squared leading edge (SL) on the time-averaged and temporal characteristics around a slanted-back Ahmed body. Measurements were conducted at two Reynolds numbers of ReH = 1.70 × 104 and 3.60 × 104. The results showed that sharpening the leading edge induces a larger recirculation region near the leading edge of the body, but slightly reduces the recirculation region in the wake region. In both leading and near wake of bodies, the recirculation length for SL cases was independent of ReH, but for the RL body, it decreases in the leading edge and increases in the wake region as ReH increases. The analysis of turbulent structures showed that the extent of the region of elevated integral timescale around the body is larger in the SL case than RL one. Statistical analysis showed that sharpening the leading edge suppresses downwash flow, which in turn reduces the shear layer interaction behind the body and decreases the dominant shedding frequency. The dominant frequencies obtained using velocity fluctuations, reverse flow area, and the coefficient of the first proper orthogonal decomposition confirmed that the dominant frequency near the leading edge and the wake region of the RL body increases with ReH, while it is insensitive to ReH for SL case. The analysis performed in the spanwise plane also revealed that a region with higher streamwise mean velocity forms in the wake region of the RL body, which originates from the higher flow deviation near the trailing edge of the body.
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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 | 0.000 |
| 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) | 0.001 | 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".