Performance Enhancement of Convective Heat Transfer in Double Pipe Heat Exchangers using Different Vortex Generators’ Configurations
Bibliographic record
Abstract
Double-pipe heat exchangers (DPHEs) are important devices used for efficient heat transfer between fluids, affecting system energy Performance. This study explores different configurations for the integration of vortex generators (VGs) into DPHEs to enhance the convective heat transfer. VGs create vortical structures that enhance mixing between the near wall and outer flows, thus improving the convective heat transfer mechanism. Different VG configurations (8, 12, and 16 rows on the inner tube of the DPHE) were analyzed using CFD simulations, focusing on key performance metrics like heat transfer rates, heat transfer coefficient, effectiveness, and pressure drop. Results showed that the heat transfer enhancement increases with the number of VGs rows, with a heat transfer coefficient rises by 7.61% and effectiveness by 7.14% with 16 VG rows, for the counter-flow DPHE configuration. The parallel flow DPHE showed significantly higher enhancements, with 11.47% increase in heat transfer rate and a 9.98% improvement in effectiveness. This research underscores the potential of VGs for enhancing heat transfer in industrial heat exchangers and provides a framework for future thermal system optimization.
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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".