Spatio-temporal behavior of long submerged bluff bodies located near a wall
Bibliographic record
Abstract
This study focuses on a comprehensive evaluation of the spatiotemporal dynamics of near-wall submerged bluff bodies, building upon the work of Edegbe et al. [Phys. Fluids 36(11), 115182 (2024)]. Three objects of the same cross-sectional area (W × h, where width, W = 1.4h, height = h) with a constant gap (C) between the body and the bed were investigated. The streamwise length (L) was varied to yield L/h = 1, 2, and 3. The flow characteristics were evaluated under the influence of a boundary layer-like approach flow with δ/h=3.6. The analysis employs instantaneous flow visualization, reverse flow area mapping, two-point spatial correlation, joint probability density functions, and spectral proper orthogonal decomposition (SPOD) to identify dynamic flow features that were not previously reported. The instantaneous flow visualization using Galilean decomposition and spanwise vorticity contour shows the presence of counterclockwise rotating backflow vortices returning to the top surface for the shortest streamwise length (L/h = 1), a characteristic that is absent for L/h = 2 and 3. Interestingly, a noticeable variation is observed in the size of these rotating backflow vortices at different time instances. The reverse flow area analysis further corroborated the intermittent flow reattachment phenomenon observed on the top surface for L/h = 2. Spectral proper orthogonal decomposition (SPOD) analysis revealed that as streamwise length increases, vortical structures become less intense, with L/h = 3 exhibiting the most rapid dissipation of turbulent fluctuations, highlighting the stabilizing influence of the body elongation on wake dynamics.
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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) | 0.000 | 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 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".