Heat transfer augmentation in a circular tube fitted with tri-partition flow splitters
Bibliographic record
Abstract
This paper focuses on the numerical and experimental study of a heated tubes heat transfer and flow characteristics with a novel tri-partition flow splitter under forced convection. A low thermal conducting fluid like air is considered to be a working fluid. Tri-partition flow splitters were manufactured with different thickness and arranged alternatively with 180° rotations to change the direction of airflow. Seven Reynolds number in the range of 5000–15,000 were considered as an operating parameter. The results of the plain tube are validated with the standard Dittus–Boelter and Gnielinski equations available in literature. In addition, the experimental results with tri-partition flow splitters are used to validate the computational fluid dynamics model used to examine the flow characteristics in the heated tube. The overall thermal performance enhancement is evaluated by the performance evaluation criteria (PEC). The results showed that the Nusselt number (Nu) is increased with an increase in Reynolds number. The maximum PEC 1.98 is obtained for 2 mm thickness splitters. The highest Nusselt number (Nu = 271.99) is found for 10 mm thickness with a higher friction drop. Friction factor values are found dropped by reducing the thickness of the splitters.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".