Thermal mixing in T-shaped micromixers with a porous block by the lattice Boltzmann method: Influence of the mixing channel configuration
Bibliographic record
Abstract
The present paper investigates the thermal mixing and cooling processes in a passive micromixer, which is applicable for the cooling of electronic devices. Employing a porous block and testing different configurations for the mixing channel is considered to enhance the mixing process and cooling performance. A 2D lattice Boltzmann thermal model is utilized to investigate the thermal performance of a T-micromixer with a porous block. Two different types of mixing channel configurations, including a step-shaped and a zigzag-shaped channel, are considered, and the obtained results are compared with those of the simple mixing channel. The thermal mixing and cooling of two miscible fluids, at 50 and 25°C entering the micromixer, are investigated. The results show that changing the mixing channel configuration may create a chaotic laminar flow, which enhances the heat transfer rate between the mixed flow and the channel wall. Whatever the Reynolds number, the step-shaped mixing channel exhibits better mixing performance than the zigzag-shaped one. For the T-micromixer with a zigzag-shaped and step-shaped mixing channel, the cases with h/H = 0.5 and h/H = 0, respectively, exhibit better thermal mixing and cooling performance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".