Thermo-Hydraulic Performance Analysis on the Effects of Truncated Twisted Tape Inserts in a Tube Heat Exchanger
Bibliographic record
Abstract
This paper investigates the convective heat transfer in a heat exchanger equipped with twisted tape elements to examine effects of the twisted tape truncation percentage, pitch value, position and Reynolds number using 3D numerical simulation. A symmetric heat flux is applied around the tube as the studied heat exchanger. Based on the influences in both heat transfer enhancement and pressure drop, the performance evaluation criterion (PEC) is utilized. Inserting twisted tape elements and reducing the pitch value significantly augment the Nusselt number, friction coefficient and PEC number compared to the plain tube. For the best case with a Reynolds number of 1000, the average Nusselt number increases by almost 151%, which is the case of fully fitted twisted tape at a pitch value of L/4. Moreover, increasing the twisted tape truncation percentage reduces both heat transfer and pressure drop. Furthermore, the highest heat transfer rate is achieved when the truncated twisted tape is located at the entrance of the tube. Finally, it is concluded that for P = L, L/2, L/3 and L/4, the optimum cases from the viewpoint of energy conservation are twisted tapes with truncation percentages of 75, 50, 50 and 0%, in which the related PEC numbers at a Reynolds number of 1000 are almost equal to 1.08, 1.24, 1.4 and 1.76, respectively.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".