Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Teorie mezní vrstvy× | Velká vírová simulace× | |
|---|---|---|
| Obor | Dynamika tekutin | Dynamika tekutin |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 1904 | 1963 |
| Tvůrce≠ | Ludwig Prandtl | Joseph Smagorinsky |
| Typ≠ | Analytical framework and approximation method | Scale-resolving turbulence simulation |
| Původní zdroj≠ | Prandtl, L. (1904). Über Flüssigkeitsbewegung bei sehr kleiner Reibung. In Verhandlungen des 3. Internationalen Mathematiker-Kongresses in Heidelberg (pp. 484-491). Teubner. link ↗ | Smagorinsky, J. (1963). General circulation experiments with the primitive equations: I. The basic experiment. Monthly Weather Review, 91(3), 99-164. DOI ↗ |
| Další názvy≠ | BL theory, Prandtl boundary layer, viscous layer | LES, subgrid-scale modeling |
| Příbuzné | 5 | 5 |
| Shrnutí≠ | Boundary Layer Theory is the analytical and approximate framework for understanding viscous flow near solid surfaces, pioneered by Ludwig Prandtl in 1904. The central insight is that at high Reynolds numbers, viscous effects are confined to a thin layer near walls (the boundary layer), while the flow outside remains essentially inviscid. This separation enables powerful approximations: the boundary layer equations reduce the full Navier-Stokes to a parabolic system solvable via streamwise marching, yielding analytical or semi-analytical solutions for many practical cases. Boundary layer theory remains fundamental to aerodynamics, hydrodynamics, and heat transfer. | Large Eddy Simulation (LES) is a turbulence modeling technique that explicitly resolves large-scale turbulent eddies while modeling small-scale subgrid-scale (SGS) motions. Introduced by Joseph Smagorinsky in 1963, LES represents a middle ground between Reynolds-Averaged Navier-Stokes (RANS) and Direct Numerical Simulation (DNS). By capturing the energy-containing scales of turbulence, LES provides superior accuracy for transient flows and complex geometries at computational costs significantly lower than DNS. |
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