An Experimental Study of Mixed Convection in Vertical, Open-Ended, Concentric and Eccentric Annular Channels
Bibliographic record
Abstract
The effect of eccentricity on heat transfer in upward flow in a vertical, open-ended, annular channel with a diameter ratio of 0.61, an aspect ratio of 18:1, and both internal surfaces heated uniformly has been investigated experimentally. Results have been reported for eccentricities ranging from the concentric case to the near-contact case and three inlet bulk Reynolds numbers, equal approximately to 1500, 2800, and 5700. This work complements our recently reported experimental results on natural convection in the same facility. The present results are deemed to be largely in the mixed convection regime with some overlap with the forced convection regime and likely to include cases with laminar, transitional, and turbulent flows in at least a part of the test section. Small eccentricity had an essentially negligible effect on the overall heat transfer rate, but high eccentricity reduced the average heat transfer rate by up to 60%. High eccentricity also resulted in wall temperatures in the narrow gap region that were much higher than those in the open channel. The concentric-case Nusselt number was higher than the Dittus–Boelter prediction, whereas the highly eccentric-case Nusselt number was significantly lower than that.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".