Experimental and numerical investigations on the effect of a novel internal surface micro-grooving toward improving convective heat transfer performance of tube heat exchangers
Bibliographic record
Abstract
In the present work, the use of passive heat transfer enhancement technique through surface alteration was explored. The enhancement was achieved through internal conduit surface micro-grooving using a new apparatus that was developed by modifying a magnetic abrasive finishing technique. A new surface profile was created and later verified using optical and laser profiler measurements. The new profile was numerically investigated to compare the heat transfer and hydrodynamic performance against other profiles that have been studied in the literature. It was found from the results that the new profile shows much higher heat transfer improvement and comparable pressure loss to the previously investigated profiles (i.e., square, rectangular, trapezoidal, and circular). Overall, the new groove geometry provides the highest performance followed by the circular, triangular, curvy, square, and rectangular grooves. Also, the results indicate that designs with a smooth profile performs better than those with sharp edges, owing to the elimination of stationary fluid spots within the grooves. The effectiveness between the profiles was compared based on the level of heat transfer enhancement against the flow penalty. Experimental validation was further conducted for the experimentally generated groove. The results revealed that a relatively small surface temperature drop was obtained, corresponding to a slight improvement in heat transfer. This confirms the results generated by the simulation that groove size plays a major role in attaining significant improvement in heat transfer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".