Measurement of Bubbly Two-Phase Flow in a Vertical Pipe Using Ultrasonic Velocity Profiler and Digital Optical Imaging
Bibliographic record
Abstract
In this study, a novel measurement framework for two-phase air-water bubbly flow has been developed.It consists of ultrasonic and digital optical imaging systems.The measured parameters include instantaneous velocity profiles of the two phases, void fraction and bubble size of the gas phase.The simultaneous velocity profiles of both phases are measured by the state-of-the-art multiwave Ultrasonic Velocity Profile methodmultiwave UVP for short.The void fraction and bubble size are measured by a digital imaging system that exploits high-speed video imaging.Non-intrusive measurement of these instantaneous flow parameters is still a challenge in two-phase flow study.In the present investigation, two ultrasonic signal processing algorithms have been implemented and tested, namely Doppler signal processing and correlation one.Similarly, rigorous digital image processing algorithms implemented in ImageJ tool have been exploited and tested to obtain the average void fraction and bubble size distribution.Furthermore, measurements and analyses have been carried out for various flow conditions.For the particular flow configuration investigated, important experimental data of the two-phase counter-current bubbly flow have been successfully obtained for the first time.The measured data are useful for both experimental and numerical analyses, especially computational fluid dynamics -CFD analyses, of two-phase flows.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".