Bibliographic record
Abstract
Accurate prediction of nonequilibrium condensation in turbomachinery is a critical issue for the design of lowpressure steam turbines and supercritical CO 2 compressors. Previously developed numerical methods for high-pressure flows with nonequilibrium condensations used REFPROP to simulate the effect of real gases; however, the estimation of the equation of state for supercooled gas was simply extrapolated from the saturated line. In this paper, an estimation method of the equation of state of a supercooled gas applicable to high-and low-pressure condensing flows is proposed. Laval nozzle flows of steam and CO 2 in high-and low-pressure conditions were then numerically investigated using the proposed method. Although the effect of real gas is much important in high-pressure conditions, the estimation method for supercool condition had relatively little effect on the pressure distribution in high-pressure flows with nonequilibrium condensation. In low-pressure steam flows containing nonequilibrium condensation, the slight difference of supercooled - diagram by the estimating method has the crucial effect on the pressure distribution due to high supersaturation ratio. Subscript in inlet condition l liquid phase g gas phase sat saturated point s value on isentropic line
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".