Experiments on supercritical flow instability in two vertical parallelchannels
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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 with supercritical CO2. A total of 7 experimental cases were performed with a system pressure range of 8.25 -9.1MPa and inlet temperatures 0.5 -10.05 C. The channel inlet temperature and system pressure were held constant and the input power was increased gradually until mass flow oscillations commenced. The distribution of mass flow rate in the channels with input power increase was examined. Initially, at low input power, the flow rate in the channels was almost equal, with an increase in input power, it got distributed in channels and become asymmetric, and with the further input power increase, it started oscillating 180 out-of-phase. The results for seven experimental cases are presented and these would be useful for code validation purposes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it