An experimental investigation of jet flow on a stepped chute
Bibliographic record
Abstract
In this paper we report on the results from an experimental study conducted to investigate the properties of the turbulent two-phase flow that occurs on a stepped chute in the jet flow regime. Simultaneous measurements of the void fraction, bubble sizes and bubble velocities were made using a fiber-optic probe. The flow was found to be fully developed by the twelfth step and as expected the head loss along the step was found to be equal to the step height. When the discharge was increased by 40% the average void fraction decreased by 8%, the depth of flow decreases by 9% and the mean velocity increased by 17%. Estimates of the turbulence intensity were computed using the mean and RMS bubble velocities. The turbulence was found to be very intense with values of the turbulence intensity varying from approximately 0.25 to 0.6. A strong negative correlation was observed between the turbulence intensity and the average bubble diameter, i.e., higher turbulence intensities produced smaller bubbles. Hinze's (J. AlChe. 1, 1955, 289) theory was used to show that Reynolds stresses are responsible for the break-up of bubbles and that the magnitudes of the observed values of the turbulence intensity were consistent with the observed bubble sizes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".