Investigation of coherent structures around a surface-mounted tripile cylinder array
Bibliographic record
Abstract
The present study examines turbulent flow around a three-dimensional tripile submerged foundation experimentally, using laser Doppler velocimetry, and numerically, using Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) techniques. The study is conducted at a Reynolds number of 104 with a tripile spacing ratio of 3. Flow measurements are compared to assess the predictive capabilities of the selected turbulence models. All RANS models succeeded in predicting primary mean flow phenomena, including flow detachment, vortex recirculation, and downstream reattachment. The LES model performed adequately well both near-wake and far-wake regions. Within the near wake region, the standard k−ϵ model exhibited the largest deviation from experimental data, although it performed appropriately well in the far-wake region. The k−ω shear stress transport model overpredicted the wake recovery. The observed discrepancies are likely due to limitations in modeling flows with large pressure gradients. Also, detailed structural analysis was conducted using the instantaneous flow data obtained from the LES simulations. Key flow features such as the horseshoe vortex, arch vortex, and a dipole structure composed of counter-rotating vortices are identified, exhibiting qualitative agreement with previous high-Reynolds number studies on an isolated cylinder. Instantaneous flow visualization revealed an antler-shaped vortex structure in the downstream wake, which resulted from the interaction of streamwise and spanwise vortices. Time-averaged surface streamlines were used to identify saddle points, attachment nodes, and swirl patterns on the tripiles. Notably, visualization at the free end of the downstream cylinder showed inward-shifted foci and a crescent-shaped recirculation region.
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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".