Numerical simulation and optimization of a circular open channel for fish farming using Computational Fluid Dynamics (CFD)
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Bibliographic record
Abstract
Open canals are one of the most common and cost-effective methods in water supply networks; they are widely used in different industries such as agriculture, water and sewage treatment, urban drainage, pisciculture and water parks. Due to global warming, the demand in clean energy to replace fossil fuels has caused using water turbines in riverbeds and aqueducts to be important. On this basis, optimizing key parameters such as flow motion and canal turbulence is crucial to reduce breakdowns while designing canals. In fact, the inappropriate adjustment of velocity and pressure within the canals may lead to the system failure: imbalance between inlet and outlet will increase the water level and the pressure on canal walls thus, leading to breakdown. In this paper, a circular open canal was designed for a pisciculture system. The velocity and height of the water canal is controlled by the canal inlet and outlet system and the water flows continuously inside the canal. By keeping the canal water volume constant in any time and the flow motion with constant velocity, the system makes the fishes feel infinite movement. Furthermore, the water particles and impurities (e.g., food and fish feces) are removed by the outlet from the canal bottom, transferred to the filtration system, and returned to the fish farm by the canal inlet after the filtration procedure; the mentioned technique causes the water canal to be kept at its optimal level. Computational Fluid Dynamics (CFD) has been used to simulate the canal flow. Solving the Navier-Stokes equations numerically and assuming incompressible, unsteady, and two-phase flow, the parameters of the canal flow were extracted. Also, by mounting the system outlet along the path of water movement, greatly reduces the adverse effects of the outlet suction force on the canal main flow. Moreover, by dividing the canal inlet with guide vanes, the inlet has been modified for the entrance of the clean water simultaneously with the distribution of the inlet flow to several smaller flows in order to make the canal water continue to move continuously without any turbulence.
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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 | 0.000 | 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 it