Prediction of the Onset of Flow Instability in a Single Horizontal Microtube With an Inlet Orifice
Bibliographic record
Abstract
A methodology to predict the onset of flow instability (OFI) in a single horizontal microtube with an inlet orifice is developed based on the predication of pressure drop. The predictive methodology states, for the same flow rate, the flow instability occurs as the single-phase liquid pressure drop under no heating condition equals the two-phase pressure drop under heating condition in a single microtube. The addition of inlet orifice increases the heat flux at the onset of flow instability by increasing the upstream pressure. The present methodology is validated by comparing the predicted heat flux at the onset of flow instability with our previous experimental data in the microtubes with three sizes of inlet orifices. The results show that the present method can predict the heat flux at the onset of flow instability with a deviation of 30% and mean absolute error of 13% at mass fluxes from 700 to 3000 kg/m2 s. The effects of inlet orifice size and saturation pressure on the onset of flow instability are also studied based on the present methodology. It is found that, at mass fluxes from 100 to 2000 kg/m2 s, the area ratio less than 15% eliminates the flow instability completely before the critical heat flux occurs.
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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) | 0.001 | 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 | 0.001 | 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 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".