Void Fraction Measurement for Two-Phase Flow Using Electrical Resistance Tomography
Bibliographic record
Abstract
Measurement of void fraction of two-phase flows remains a challenging area. In this paper the application of an electrical resistance tomography (ERT) system for this purpose has been studied. A new approach through the direct use of the voltage data measured by the ERT system is presented. The measured voltage data are first compressed through a feature extraction, and a polynomial regression procedure is followed to obtain the relationship between the void fraction and the feature extracted. Both simulation and experiment are carried out to verify the approach. The methodology of the new approach, simulation and experimental results are presented in the paper. La mesure de la fraction de vide des écoulements biphasiques reste un domaine difficile. Dans cet article, on a étudié l'application de la tomographie à résistance électrique (ERT) à cette fin. Une nouvelle approche par l'utilisation directe des données de tension mesurées par la technique ERT est présentée. Les données de tension mesurées sont d'abord comprimées par une extraction des caractéristiques, suivie d'une régression polynomiale pour obtenir la relation entre la fraction de vide et la caractéristique extraite. La simulation et des expériences sont toutes deux réalisées pour vérifier cette approche. La méthodologie de cette nouvelle approche, les résultats de la simulation et les résultats expérimentaux sont décrits en détail dans cet article.
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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 | 0.001 |
| 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".