Pseudophase change effects in turbulent channel flow under transcritical temperature conditions
Bibliographic record
Abstract
We have performed direct numerical simulations of compressible turbulent channel flow using R-134a as a working fluid in transcritical temperature ranges ( $\unicode[STIX]{x0394}T=5$ , 10 and 20 K, where $\unicode[STIX]{x0394}T$ is top-to-bottom temperature difference) at supercritical pressure. At these conditions, a pseudophase change occurs at various wall-normal locations within the turbulent channel from $y_{pb}/h=-0.23$ ( $\unicode[STIX]{x0394}T=5$ K) to 0.89 ( $\unicode[STIX]{x0394}T=20$ K), where $h$ is the channel half-height and $y=0$ the centreplane position. Increase in $\unicode[STIX]{x0394}T$ also results in increasing wall-normal gradients in the semi-local friction Reynolds number. Classical, compressible scaling laws of the mean velocity profile are unable to fully collapse real fluid effects in this flow. The proximity to the pseudotransitioning layer inhibits turbulent velocity fluctuations, while locally enhancing the temperature and density fluctuation intensities. Probability distribution analysis reveals that the sheet of fluid undergoing pseudophase change is characterized by a dramatic reduction in the kurtosis of density fluctuations, hence becoming thinner as $\unicode[STIX]{x0394}T$ is increased. Instantaneous visualizations show dense fluid ejections from the pseudoliquid viscous sublayer, some reaching the channel core, causing positive values of density skewness in the respective buffer layer region (vice versa for the top wall) and an impoverishment of the turbulent flow structure population near pseudotransitioning conditions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".