Effect of Inlet Restriction on Flow Boiling Heat Transfer in a Horizontal Microtube
Bibliographic record
Abstract
Flow boiling heat transfer in a horizontal microtube with inlet restriction (orifice) under uniform heating condition is experimentally investigated using FC-72 as working fluid. A stainless steel microtube with an inner diameter of 889 μm is selected as main microtube. Two microtubes with smaller diameters are assembled at the inlet of main microtube to achieve the restriction ratios of 50% and 20%. The experimental measurement is carried out at mass fluxes ranging from 160 to 870 kg/m2·s, heat fluxes varying from 6 to 170 kW/m2, inlet temperatures of 23 and 35 °C, and saturation pressures of 10 and 45 kPa. The effects of the orifices on two-phase pressure drop, critical heat flux (CHF), and flow boiling heat transfer coefficient are studied. The results show that the pressure drop caused by the orifice takes a considerable portion in the total pressure drop at low mass fluxes. This ratio decreases as the vapor quality or mass flux increases. The difference of normal critical heat flux in the microtubes with different orifice sizes is negligible. In the aspect of flow boiling heat transfer, the orifice is able to enhance the heat transfer at low mass flux and high saturation pressure, which indicates the contribution of orifice in the nucleate boiling dominated regime. However, the effect of orifice on flow boiling heat transfer is negligible in the forced convective boiling dominated regime.
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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 | 0.000 |
| 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".