CFD Study on Cross-Cut Design of Horizontal Plate-Fin Heat Sinks
Bibliographic record
Abstract
In this work, simulations are conducted to investigate the effect of the cross-cut design on reducing the so-called ineffective zone that has low velocity in a long horizontal plate-fin heat sink.The low-velocity region exists when the plate-fin channels are too long for air from one end to reach the centre, causing the reduction of thermal performance.It is found that the lateral flows penetrating into the low-velocity region through cuts on the fins prevents the heat sink from an incomplete usage and thus improves its thermal performance.In this numerical study, we found that the cut length (Lc) and cut number (Nc) are two crucial factors that affects the total heat transfer of a cross-cut heat sink.For the heat sink with length of 200 mm, height of 12 mm, width of 100 mm and spacing of 6.8 mm the best cut number along with the corresponding optimum cut length are Nc = 4 and Lc = 12 mm, with which the heat sink has improvement of 22.3% reduction in its temperature excess and 13.6 % reduction in its weight.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".