Centrifugal Instability with Convective Heat Transfer Through a Tightly Coiled Square Duct
Bibliographic record
Abstract
In this paper, a numerical study on centrifugal instability with convective heat transfer through a curved square duct is presented by using a spectral method, and covering a wide range of the Dean number ( ) 0 5000 Dn for a tightly coiled square duct of curvature 0.5 The outer and bottom walls of the duct are heated while cooling from the inner and the ceiling.The main objective of this study is to expose combined effects of centrifugal and buoyancy forces on fluid flows through a curved channel.For this purpose, solution structure of the steady solutions is obtained first.As a result, four branches of symmetric/asymmetric steady solutions are obtained.Linear stability of the steady solutions is then investigated.It is found that only the first branch is linearly stable while the other branches are linearly unstable.Unsteady flow behavior, obtained by time evolution calculations, shows that the steady-state flow turns into chaotic flow via periodic and multiperiodic flows, if Dn is increased.Typical contours of secondary flow pattern, stream-wise velocity distribution and temperature profiles are obtained at several values of Dn and it is found that the flow consists of asymmetric two-to four-vortex solutions.The present study shows that convective heat transfer is significantly enhanced by the secondary flow; and the chaotic flow, which occurs at large Dn's, enhances heat transfer more effectively than the steady-state or periodic solutions.Finally, a comparison between the numerical and experimental investigations has been made, and it is found that there is a good agreement between the numerical and experimental investigations.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".