Uncertainty Quantification of Low Void Fraction Measurements Using Wire-Mesh Sensors in Horizontal Air-Water Flows
Bibliographic record
Abstract
The need for a revised methodology and uncertainty quantification for wire-mesh sensor void fraction measurements in horizontal low void fraction flow conditions was identified. Two-phase flow measurements were performed at a low-pressure, adiabatic and horizontal flow loop using wire-mesh sensors over a range of water superficial velocities from 3.5 to 5.5 m/s, air superficial velocities from 0.05 to 0.9 m/s and volumetric void fractions from 1 to 16% Using this proposed analysis, a corrected trend with average percent differences of 36, 21 and 6% was obtained for the low, medium and high gas flow rate cases, respectively, when comparing the wire-mesh sensor void fractions to two-phase pipe flow models. By combining these measurements of the void fraction with those of the interfacial velocity, the gas superficial velocity was calculated based on the physical theory, and compared to the superficial velocity measured by the flowmeters for validation purposes. An estimation of the uncertainty of these parameters showed that most of the measured parameters agreed reasonably with physical theory within 20%.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".