Design and Numerical Evaluation of a Split-and-Recombined ‘(Y-H)<sub>αβ</sub>’ Micromixer
Bibliographic record
Abstract
A novel split-and-recombined (SAR) micromixer namely '(𝑌 -𝐻) 𝛼𝛽 ' composed with a 'Y' and a 'H' shaped mixing unit is proposed.The proposed '(𝑌 -𝐻) 𝛼𝛽 ' micromixer is composed of four identical elements that are connected by angles 𝛼 and 𝛽.The value of alpha (𝛼) is varied from 0° to 90° to analyze the effect on mixing performance.Numerical analysis of fluid flow and mixing performance is conducted for miscible fluids, using Fluent 15 software for Reynolds numbers from 0.1 to 100.A well-known SAR mixer called 'H-C' is also analyzed for comparison.The numerical data shows that connecting angle 𝛼 has a strong effect on the SAR process; the efficiency increases from 65% to 98% when alpha (𝛼) changes from 0 ° to 45 ° at 𝑅𝑒 = 100.The '(𝑌 -𝐻) 𝛼𝛽 ' mixer shows notably lower pressure drop than the 'H-C' mixer irrespective of the value of connecting angle 𝛼 and Reynolds numbers.The proposed mixer has a significantly lower Mixing Energy Cost (MEC) compared to the '(𝐻 -𝐶)' mixer.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".