Influence of a Sloped Bottom on a 60-Degree Inclined Dense Jet Discharged into a Stationary Environment: A Large Eddy Simulation Study
Bibliographic record
Abstract
In the present study, numerical simulations were conducted to investigate the behavior of a 60° inclined dense jet discharged onto horizontal (0°) and sloped (5°) bottoms in a stagnant environment. The objective was to evaluate the capability of Large Eddy Simulation (LES) in capturing both the kinematic and mixing characteristics of inclined dense jets interacting with different bottom boundaries. A Reynolds-Averaged Navier–Stokes (RANS) model was also included for comparison. The LES simulations successfully reproduced the key kinematic and mixing characteristics, including the jet trajectory, centerline peak location, impact point, and terminal rise height, and showed strong agreement with the experimental observations. LES also predicted the concentration distributions and variations along both the horizontal and sloped bottoms, whereas the RANS model tended to underestimate both geometrical and dilution properties. A Gaussian fitting function was proposed to estimate the concentration distribution under both bottom conditions. Analysis of the spreading layer indicated that the concentration profiles exhibited self-similarity. Energy spectrum analysis showed that the sloped bottom enhanced shear-induced turbulence, thereby improving the mixing efficiency. Results confirm the reliability of LES for describing jet–bed interactions and emphasize the influence of bed slope on jet dilution and mixing behavior.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".