A flowmeter for unsteady liquid flow measurements in total liquid ventilation
Bibliographic record
Abstract
A promising alternative to the use of conventional mechanical ventilators to treat pulmonary syndromes such as acute respiratory distress and meconium aspiration consists of employing total liquid ventilators, an experimental device which uses an oxygenated perfluorochemical liquid instead of a gas mixture of air and oxygen. Liquid ventilator development is an active field of research, as most components cannot be directly imported from gas ventilators and must be completely redesigned. The addressed problem is to provide a reliable measurement of the liquid flow in and out of the lungs considering that it must take into account unsteady effects to produce accurate measurements. An unsteady flowmeter was developed for implementation in the Inolivent-4, our total liquid ventilator prototype developed at Université de Sherbrooke. It consists of a symmetrical venturi tube comprising three pressure sensors and in which flow measurement is obtained by numerically solving a slightly modified version of the unsteady Bernoulli equation. A prototype was validated in-vitro by applying zero-mean sinusoidal flows. Low-frequency characterization determined the venturi discharge coefficient as a function of the Reynolds number, and higher-frequency measurements determined the applicable bandwidth of the device. The velocity profiles were measured in the venturi by particle image velocimetry (PIV), and the device was calibrated by comparison with an ultrasonic flowmeter and measurements from a piston pump. Results showed that quasi-steady flows could be accurately measured in the 5 ml/s - 60 ml/s range, while low-amplitude (≤10 ml/s) oscillatory flows were well measured for frequencies below 3 Hz. Finally, PIV experiments showed that the flat velocity profile assumption required for a simple solution of the flowmeter equation was valid within the operating range.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".