Characteristics of Single-Phase Flow in Microchannels
Bibliographic record
Abstract
Experiments were performed to study the flow behaviour of de-ionized water and nitrogen gas through round capillary rubes having an inner diameter of 100µm. At steady state, the single-phase pressure drop along the glass microchannel was measured and analysed. To compare with conventional flow theory, an evaluation was made of the friction factor constant for laminar flow and critical Reynolds number for the transition from laminar to turbulent flow. The liquid flow data were well predicted by the conventional friction factor equations for larger channels, and the critical Reynolds number was close to the traditional macro-scale value. For single-phase gas flow, the measured friction factors were found to agree with theory if compressibility effects are taken into account. The addition of compressibility yields a non-linear pressure distribution that arises from the density change of the gas in the channel. Unlike liquid flow in microchannels, the gas friction factor constant depends on the Reynolds number, which changes along the channel length. Moreover, compressibility caused the velocity to vary all along the length of the channel and prevented the flow from being fully-developed. The neglect of the slip-flow boundary condition and compressibility may account for the discrepancy between the experimental results of various researchers.
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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 | 0.001 | 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) | 0.001 | 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".