Transient Analysis of a Liquid Flow in Microchannel of Varying Cross-Section
Bibliographic record
Abstract
In this study the transient analysis of a laminar liquid flow in a three-dimensional microchannel of varying rectangular cross-section was numerically investigated. The imposed heat fluxes on the microchannel upper and bottom wall, the Joule heating due to an applied electric potential at the microchannel inlet and outlet, the electroosmosis, the pressure-driven flow, and the liquid temperature-dependent thermophysical properties were accounted for. The time-dependent liquid flow velocity profile and the time-dependent liquid temperature distribution were obtained respectively solving the Navier-Stokes equations and the energy equations for a laminar incompressible liquid flow using a computational fluid dynamics code. The effects of the microchannel divergence angle and the microchannel dimensions on the liquid flow and the heat transfer in the microchannel were analyzed. Results obtained show significant influences of the pressure difference between the microchannel inlet and outlet, the imposed heat flux, and the microchannel inlet width on the transient and steady states of the liquid flow velocity and the liquid temperature distribution. A comparison of the results of the developed model with those achieved considering the liquid constant thermophysical properties and those obtained from a microchannel of a constant cross-section was made.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".