Spectral analysis of turbulence energy transport in a channel mounted with circular-arc ribs
Bibliographic record
Abstract
Spectral analysis of the transport process of turbulence kinetic energy (TKE) in a channel roughened with spanwise-aligned circular-arc ribs is conducted based on direct numerical simulations (DNS). Test cases of varying pitch-to-height ratios ( $P/H=3.0$ , 5.0 and 7.5) and bulk Reynolds numbers ( ${\textit{Re}}_b=5600$ and 14 600) are compared. It is observed that the characteristic spanwise wavelength of the energy-containing eddies in the internal shear layer (ISL) increases as the value of $P/H$ increases, but decreases as the Reynolds number increases. In the ISL, the energy transport processes are dominated by turbulent production as the lead source term, but by turbulent diffusion and dissipation as the lead sink terms. It is found that regions with high production and dissipation rates of TKE in the ISL are associated with moderate and small wavelengths, respectively. The TKE production for sustaining moderate- and large-scale motions enhances gradually with an increasing value of $P/H$ , while that for sustaining small-scale motions augments as the Reynolds number increases. It is interesting to observe that the interscale-transport term plays a critical role in draining TKE at moderate wavelengths as a sink and carries the drained TKE to small-scale eddies as a source. It is discovered that a higher pitch-to-height ratio leads to shortening of the characteristic spanwise wavelength of the dissipation process but prolongation of those of the production, interscale-transport and turbulent-diffusion processes in the ISL. By contrast, a higher Reynolds number results in reductions in the characteristic spanwise wavelengths of all spectral transport terms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".