Estimation of Average Void Fraction for Gas-Liquid, Two-Phase Flow in an Industrial Nozzle Assembly Using a Quick-Closing-Valve
Bibliographic record
Abstract
Experimentally accurate void fraction measurements are a challenge in an air/water, two-phase flows through an industrial nozzle assembly, as a highly non-uniform void fraction exists in the feeding conduit prior to the nozzle. In this study, average void fractions were measured by isolating a section in the feeding conduit of a horizontal nozzle assembly, termed as the quick-closing-valve (QCV) technique. A high-speed video camera was utilized to capture the asynchronization closing time, tac. The average closing time and asynchronization for the pneumatically controlled valves were 200 ms and 2 ms, respectively. Based on the equation of 100umtac (1−α)/αlc, the synchronization error between the two valves was 1.12%, 1.26%, and 1.79% for the 1%, 2% and 4% ALR cases, respectively; here um is the mixture velocity, α is the void faction, and lc is the closing length. Higher synchronization error at 4% ALR occurs due to enhanced momentum in the flow regime. Experimental results indicate that the average α over the 33.4 cm feeding conduit (6.25 mm ID) was 76% (αtheoretical = 75%) for the 2% ALR, and 85% (αtheoretical = 83%) for the 3.3% ALR. In the two-phase, two-component flow the α affects the drop size and stability of the spray produced from an industrial nozzle assembly. Learning from this study will yield insights and conceptual understanding of two-phase flow phenomena in conduit, which would affect stability, pulsation tendency, and possibly atomization performance of the nozzle downstream. Two-phase flow nozzles have wide applications in the industries, e.g. petrochemical, pharmaceutical, and others.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".