Analysis of laminar boundary-layer separation in retarded flow over bodies of revolution
Bibliographic record
Abstract
The laminar boundary-layer separation phenomenon is an interesting and important aspect of boundary-layer flows. It occurs in various physical situations because of a decrease in wall shear stress caused by retarded flow velocity, among other things. Flow separation can be prevented or delayed by utilizing bodies of revolution because the surface transverse curvature produces a favorable pressure gradient, which in turn increases the wall shear stress that keeps the flow attached to the surface. Bodies of revolution, whose body contours follow a power-law form, also play a vital role in delaying flow separation. Bodies of revolution of varying cross sections and involving surface transverse curvature are utilized to examine their effects on flow separation. In particular, a convex transverse curvature has been considered owing to its effects on the nature of the favorable pressure gradient, which delays the flow separation. A Görtler-type retarded flow velocity was considered in this study to investigate the flow separation process. A detailed analysis is provided to understand the flow separation by calculating the separation points under various assumptions. It has been observed that the body contour exponent n and the convex transverse curvature parameter k play an assistive role in the delay of boundary-layer separation even under the influence of strong retardation. The results are presented through various tables and graphs to highlight the role of the power-law exponent of external velocity m, convex transverse curvature parameter k, and body contour exponent n on the separation points.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".