Energy Redistribution Between the Mean and Pulsating Flow Field in a Separated Flow Region
Bibliographic record
Abstract
One of the main features of the backward-facing step (BFS) low frequency pulsatile flow is the unsteadiness due to the convection of vortical (coherent) structures, which characterize the flow dynamics in the shear layer. The physics of the flow field is analyzed by looking at energy redistribution between the mean and pulsating flow field obtained via a particle image velocimeter (PIV) using the concept of a triple decomposition. The total fluctuating kinetic budget is calculated and discussed for a mean Reynolds number of 100 and for 0.035 ≤ St ≤ 2.19. The effects that these coherent structures have on the fluctuating kinetic energy production, dissipation, and transport mechanism are examined. The results provide insight into the physics of the flow and suggest reasons for vortex growth and decay. Fluctuating kinetic energy is generally produced at the separated shear layers and transported towards the core flow and then to the upper and lower walls where viscosity dissipates the energy. The remaining energy is transported streamwise and decays as it is convected downstream (St = 0.4 and 1 cases). It was also found that the pressure-velocity correlation diffusion plays a significant role in the transport of kinetic energy and Reynolds stresses, especially in the separated shear layer. More energy was dissipated at the walls for the high Strouhal number case St = 2.19 due to the transverse pressure diffusion term being increasingly dominant. This could be the reason why the convected primary vortices were much smaller in size and weaker with no upper wall vortices formed at this pulsation Strouhal number. The shear production for St = 0.035 was very minimal; thus, the vortices died down quickly even before the shedding could happen. Finally, the pressure-strain correlation term was found to be significant in redistributing the kinetic energy from u-component to v-component.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".