Numerical Study of a Planar Micromixer with Circular and Fin Obstacles
Bibliographic record
Abstract
The design and characterization of a passive planar O mixer with two different kinds of barriers to improve mixing performance are reported in this study.The computational fluid dynamics (CFD) program ANSYS 15 is used to perform computational studies on mixing and fluid flow in microchannels over a broad range of Reynolds numbers, from 1 to 100.The outcomes demonstrate that the O mixer with obstacles performs significantly better at mixing than the O mixer without obstacles.The explanation is that obstacles cause the fluid path length to increase, giving the fluids more time to diffuse.The O mixer with circular and fin obstacles is three times more efficient than the O mixer without obstacles in all scenarios.Due to the absence of any obstructions within the channel, the O mixer has the lowest pressure drop.The O mixer with circular & fin obstacles is the most economical one since it has the lowest mixing cost, which is a crucial feature for incorporation into intricate, cascading microfluidic systems.The proposed O mixer with obstacles can be easily manufactured and integrated into devices for a variety of macromixing applications due to its low mixed cost and simple planar construction.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".