Inertial flow dynamics and energy dissipation in asymmetrical converging–diverging microchannels: A computational study
Bibliographic record
Abstract
Abstract This study presents a three‐dimensional computational analysis of inertial flow behaviour, hydraulic resistance, and thermodynamic performance in asymmetrical converging–diverging microchannels. Three configurations are examined by introducing asymmetries in the lower arm—through variations in tapering angle, throat width, and throat length—while keeping the upper arm unchanged. Flow distribution analysis reveals that the steep‐angle design achieves the most balanced flow split, improving symmetry by approximately 55% and 83% compared to the extended‐throat and wide‐throat designs, respectively. At a representative flow rate of 20 μL/min, the wide‐throat configuration exhibits the lowest flow resistance, reducing pressure drop by 46.7% and 28.0% relative to the extended‐throat and steep‐angle cases, respectively. The steep‐angle design also outperforms the extended‐throat geometry by 26.0%. In terms of thermodynamic performance, entropy generation is lowest in the steep‐angle configuration, showing a 27% reduction compared to the extended‐throat case for Re 2.82. Overall, the wide‐throat design minimizes energy loss and hydraulic resistance, the steep‐angle configuration offers a balanced trade‐off between flow symmetry and efficiency, and the extended‐throat geometry results in the highest pressure and entropy penalties. These findings offer quantitative guidance for the optimized design of energy‐efficient microfluidic systems operating under inertial flow regimes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".