Transient Two-Phase Flow Patterns by Application of a High Voltage Pulse Width Modulated Signal and the Effect on Condensation Heat Transfer
Bibliographic record
Abstract
The objectives of this study are (i) to determine the transient phase redistributions of a two-phase flow in a smooth horizontal annular channel by applying high voltage pulses to induce electric fields and (ii) to quantify the resultant changes in the condensation heat transfer. The experiments were performed using refrigerant R-134a flowing in a tube that was cooled on the outside by a counter-current flow of water. The electric fields are established by applying high voltage to a concentric rod electrode inside a grounded tube. The effect of the electrohydrodynamic (EHD) forces on the changes to the initial stratified/stratified wavy flow pattern was visualized using a high speed camera. The EHD effect results in the redistribution of the liquid-vapour phase within the channel and unique flow structures, such as twisted liquid cones and entrained droplets, are observed. These structures only appear during the initial application of EHD and are absent in the steady state flow pattern. Experiments were performed using a 8kV pulse width modulated (PWM) signal with duty cycles ranging from 0–100% to evaluate the heat transfer and pressure drop characteristics of the transient EHD flow patterns. The resultant heat transfer increased with the duty cycle to approximately 2.7-fold at a low mass flux (45–55kg/m2s) and 1.2-fold at a high mass flux (110kg/m2s). The enhancement was higher as the pulse width was increased.
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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 | 0.000 |
| 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".