Analysis of plunging phenomenon in dam reservoirs using three-dimensional density flow simulations
Bibliographic record
Abstract
Density flow is investigated in a three-dimensional model through a dam reservoir with diverging and sloping bottom channels. When an inflow of higher density enters ambient dam reservoir water, it plunges below the ambient water and becomes density underflow. In the present model, nonlinear and unsteady continuity, momentum, energy, and turbulence model equations are formulated in the Cartesian coordinates. The k–ε turbulence model is used with an extension to include production or destruction of turbulent kinetic energy. To investigate the Coriolis force effect on the density flow in a dam reservoir, a Coriolis force parameter is included in the governing equations. The equations of the model are solved based on the initial and boundary conditions of the dam reservoir flow for a range of bottom slopes and divergence angles. In this paper, variation in density flow parameters, such as velocity, temperature, and turbulence viscosity through the dam reservoir, is investigated. Moreover, mixing rate, plunging points, and plunging depths are determined from the simulation results. The results of the present model are compared with the previous experimental work and model. The present model results follow the expected basic trend. The three-dimensional model simulation and analysis improve the understanding of density flow, underflow, divergence flow, mass transport, and dam–reservoir flow interaction.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".