Experiments and analyses of supercritical CO2 flow instability with study of dimensionless parameters
Bibliographic record
Abstract
Very limited experimental data on supercritical flow instability is present in the literature. To enrich this limited database and to further the understanding of supercritical flow instability, an experimental study was conducted using two vertical parallel channels facility (TVPC) with supercritical CO2 flowing upward. A total of 23 experimental cases were performed on the new facility; sixteen were published by Saini (2019) and the rest of the cases are presented herein. The system pressure for the seven new cases was in the range 8.25 – 9.1MPa and the inlet temperature was in the range 0.5 – 10.05 °C. For all the cases, oscillatory flow instability was observed. The current and the previous experiments performed by Saini were numerically analyzed without and with wall-heat storage effect using an in-house 1-D linear program. The numerical results showed good agreement with the experimental data. The inclusion of the wall-heat storage effect, for this parallel-channel system, yields a very small effect on the flow stability boundary. In addition, the dimensionless parameters proposed by Ambrosini and Sharabi (2008) for supercritical flow were examined using CO2 experimental instability data in combination with the numerical results. The dimensionless parameters performed very well.
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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 | 0.000 | 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 | 0.001 | 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) | 0.001 | 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".