A New Capacitance Sensor for Measuring the Void Fraction of Two-Phase Flow Through Tube Bundles
Bibliographic record
Abstract
Evaluating the two-phase flow parameters across tube bundles is crucial to the analysis of vibration excitation mechanisms. These parameters include the temporal and local variation of void fraction and phase redistribution. Understanding these two-phase parameters is essential to evaluating the stability threshold of tube bundle configurations. In this work, capacitance sensor probes were designed using finite element analysis to ensure high sensor sensitivity and optimum response. A simulation-based approach was used to calibrate and increase the accuracy of the void fraction measurement. The simulation results were used to scale the normalized capacitance and minimize the sensor uncertainty to ±5%. The sensor and required conditioning circuits were fabricated and tested for measuring the instantaneous void fraction in a horizontal triangular tube bundle array under both static and dynamic two-phase flow conditions. The static calibration of the sensor was able to reduce the uncertainty to ±3% while the sensor conditioning circuit was able to capture instantaneous void fraction signals with frequencies up to 2.5 kHz.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".