Laminar convective heat transfer in helical twisted multilobe tubes
Bibliographic record
Abstract
Augmentation of heat transfer performance has long been the main interest in thermal fluid engineering sector. Some commonly adopted thermal enhancement methods are adoption of helical tubes, twisted tubes and multilobe cross-sections. Several studies reported further enhancement when combination of these methods were implemented. Despite their promising potential, no investigation on the performance of heat transfer in helical twisted multilobe tubes has been reported. Therefore, present study is conducted with the main objective to study the laminar convective heat transfer of Newtonian fluid in a helical twisted multilobe tube through computational fluid dynamics (CFD) simulations. A three-dimensional model was developed with accordance to principles of fundamental conservation. The model was validated against available experimental data for which a good agreement was achieved. The model was thus utilised to investigate the fluid flow and heat transfer in the studied tube within a range of certain parameters, such as, number of lobes, number of twists, inlet Reynolds number as well as the geometry of the pipe (straight and helical). The performances of heat transfer of the investigated configuration are evaluated using the typical Nusselt number, friction factor and performance index (PI), which is a ratio between average Nusselt number and friction factor under constant pumping work condition. The results reveal that adding the number of lobes alone has negligible effect on the performance. However, combination of number of lobes and tube twisting result in considerable changes on the heat transfer coefficient with marginal effect on the friction factor. This is especially pronounced for tube with even number of lobe (bilobe and quadrilobe). Overall, helical coiled tube performs better within the range of Re 500 to Re 2000 as the performance index averagely increase by 18.4% as compared to straight tube, whereas below Re 500, straight tube is slightly outperforming the helical tube (3.65%). Twisting of the tubes result in the opposite effect, i.e. it improves the performance of straight tube but deteriorate the performance of helical tube. Thus, twisting is recommended primarily for straight tubes. Highest performance index yielded is 7.01 by bilobe helical tube without twist at Re 2000. Lastly, correlations for friction factor and Nusselt number are developed for straight and helical multilobe twisted tube within studied range. This correlation can serve as quick design tools for non-conventional heat exchanger utilizing twisting multilobe tubes.
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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 | 0.000 |
| 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 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".