Transient flows past arrays of yawed finite prisms
Bibliographic record
Abstract
Transient flows past arrays of yawed finite-length prisms in tandem and staggered arrangements are simulated. Large eddy simulation method is employed to characterize spatial and temporal characteristics of flows in the vicinity of prisms. Drag coefficients of prisms are determined for different spacing and yaw angle of prisms. Three-dimensional effects are investigated for different spacings of prisms in a tandem array. Drag coefficient of downstream prism is significantly lower compared to that of upstream prism when prisms are tightly spaced. Drag coefficient of downstream prism predicted by simulations in three-dimensional geometry is recovered fully as spacing approaches 10 times the height of the prism while drag coefficient predicted by simulations in two-dimensional geometry is only about 30% of the upstream prism even when two prisms are separated by 20 times the height of the prism. The wake flow patterns do not influence the drag coefficient strongly for the staggered arrays of yawed prisms. Prisms can be placed in a tighter arrangement without a significant penalty of drag reduction. Mathematical models and numerical methods employed are validated by comparing simulation results against experimental results. Drag exerted on these prisms can directly be related to power generation by devices containing translating blades of marine-current applications. This study demonstrates that arrangement, spacing, and yaw angle can be used to design and optimize energy harvesting devices and other offshore structures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".