Effect of Notched Pin Fin Heat Sink on the Heat Transfer Performance: Numerical Study
Bibliographic record
Abstract
The increasing complexity and miniaturization of electronic applications necessitate the development of efficient and compact heat sink designs for effective heat dissipation.This study presents a numerical investigation of heat transfer performance in circular pin-fin heat sinks featuring notches of varying sizes.Five distinct heat sink models are analyzed, with the first model comprising a solid fin, while the remaining four incorporate notched fins of different dimensions.Results indicate a significant influence of notch size on heat transfer performance, particularly for larger notches.The Nusselt number for a heat sink with a 4 mm notch size exhibits an increase of approximately 9% compared to that of a solid-fin heat sink.Additionally, the average temperature of heat sinks decreases with the introduction of notched fins, resulting in a temperature difference of 2.15℃ between solid-fin and 4 mm-sized notch heat sinks.An assessment of overall efficiency and overall effectiveness reveals that all notched heat sinks are viable options, with the 4 mm-sized notch heat sink demonstrating optimal performance in this study.This investigation provides valuable insights for the design of highperformance heat sinks in compact electronic applications.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".