Numerical analysis of the flow around a circular cylinder using RANS and LES
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Bibliographic record
Abstract
The present study is to simulate the flow past a circular cylinder at a Reynolds (Re) number of 5800, which is based on free-stream velocity and the cylinder diameter. The cylinder is slightly heated and the amount of heat is small enough to be considered as a passive scalar. Due to its complexity, the flow around a circular cylinder is considered as a challenging problem for computational fluid dynamics (CFD) simulation. Re-averaged Navier–Stokes (RANS) equations and large eddy simulation (LES) are two commonly used approaches in turbulent flow simulation. In this study, these two methods are both investigated by employing a CFD software called FLUENT. For two-dimensional (2D) simulation, the renormalization group k–ϵ model is used with enhanced wall treatment. Moreover, 2D LES is also tested, which reveals the necessity for three-dimensional (3D) LES computations. For 3D simulations, computations with the Smagorinsky–Lilly subgrid-scale (SGS) model and dynamic SGS model are used. A phase-averaging technique is employed to study turbulence structure in the circular cylinder wake. An instantaneous quantity is decomposed into a time-mean component, a coherent component and an incoherent component (Reynolds and Hussain Citation1972). After the triple decomposition and structural averaging, the coherent contributions to the Reynolds stresses and temperature variance can be analyzed. The reference phase for phase averaging is calculated for the time history of the lift coefficient CL. Both velocity field and temperature field are investigated and compared with the experimental measurements.
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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 | 0.001 |
| 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 it