Dissolved Oxygen Variation on the Steps with a Quarter Circle End Sill for Flows over the Stepped Spillways
Bibliographic record
Abstract
Determining the aeration efficiency of the stepped spillways is important because the Dissolved Oxygen (DO) concentration helps indicate the water quality. This study investigated the effects of varying step shape and chute slope on the aeration efficiency for stepped spillways. The measured parameters were DO, the inception point of the free surface, and the water surface profile above the crest to evaluate the geometry variation impacts. Several experiments were conducted on a six-step configuration over a stepped spillway with chute angle (θ = 26.6°, 21.8°, and 8.9°). The discharges up to 0.055 m3/s. The step configurations were including flat step, normal end sill, and quarter circle end sill. The results showed when the chute angle changed from 26.6° to 8.9°, the aeration efficiency of E20 improved with 11.51% at the lowest discharge and 6.05% at the highest discharge for the flat step model with 10 steps. Also, E20 improved 11.39% at the lowest discharge and 6.50% at the highest discharge for the flat step model with 6 steps. The performance of the steps with the quarter circle end sill model in terms of aeration efficiency increased by 10%.
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 | 0.000 |
| 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 | 0.000 | 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".