Improved thermal–hydraulic performance of a microchannel with hierarchical honeycomb porous ribs
Bibliographic record
Abstract
Abstract Microchannel cooling technology has been proven to be extraordinarily efficient for the removal of heat flux in electronic devices. Here, we numerically investigate the thermal and hydraulic characteristics of microchannels with different shapes of ribs, namely, circular ribs, square ribs, regular ribs, and hierarchical honeycomb ribs. Those ribs are composed of solid and porous media. Results indicate that heat transfer can be promoted by adding different shapes of ribs. Especially, microchannels with hierarchical honeycomb ribs possess the greatest heat transfer capability. Pressure drop (Δ p ) and friction factor ( f ) display the largest values when microchannel ribs are hierarchical honeycomb and solid, whereas Δ p of the microchannel with hierarchical honeycomb porous ribs dramatically decreases, which achieves an 81.1%–81.7% reduction. Results of j/f show that the microchannel with hierarchical honeycomb porous ribs presents the best comprehensive performance, which is ascribed to the superior heat transfer capability and the low Δ p induced by the ultra‐hydrophobic effect.
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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) | 0.001 | 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".