By Fernando F. Grinstein, Len G. Margolin, William J. Rider
The numerical simulation of turbulent flows is a topic of serious functional significance to scientists and engineers. the trouble in attaining predictive simulations is likely to be top illustrated by way of the big variety of methods which were built and are nonetheless getting used via the turbulence modeling neighborhood. during this booklet the authors describe this kind of ways, Implicit huge Eddy Simulation (ILES). ILES is a comparatively new method that mixes generality and computational potency with documented good fortune in lots of parts of advanced fluid stream. This ebook synthesizes the theoretical foundation of the ILES technique and reports its accomplishments. ILES pioneers and lead researchers mix the following their adventure to offer a complete description of the technique. This e-book could be of basic curiosity to graduate scholars, simple learn scientists, in addition to execs curious about the layout and research of complicated turbulent flows.
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Additional info for Implicit Large Eddy Simulation Computing Turbulent Fluid Dynamics
However, without the nonlinear flux-correction process, the resultant solutions were just as bad as other linear, second-order algorithms. Rather than adding a strong numerical diffusion (“viscosity”) controlled by numerical derivatives that would be meaningless near discontinuities and sharp gradients, I began looking in detail at the physics of local profiles of the density being convected – before and after the antidiffusion stage. In each specific case it was clear just how much of the antidiffusive correction flux had to be thrown away to prevent a particular cell value from drifting past the monotonicity limits imposed by the neighboring values.
When a higher-order spectral, pseudospectral, or spectral-element representation is used to decrease the numerical diffusion and numerical dispersion, the Gibbs oscillations become more evident, especially at steep gradients. When coupled continuity equations are solved to describe fluid dynamics, other coupling difficulties can arise. The practical question is how to minimize the combined effect of these errors to obtain an accurate solution (Oran and Boris 1987, 2001). Nonlinear, monotone convection algorithms are designed to minimize these purely numerical problems while enforcing the important physical properties of global conservation, monotonicity (positivity), causality, and locality.
Viscous dissipation of the unresolved scales appears as heat. Furthermore, these methods are quite capable of capturing quantitatively how much unresolved structure from the long wavelengths is actually present. Diffusion of the eddy transport type is automatically left in the flow as required but the fluctuating driving effects of random phase, unresolved eddies on the large scales is missing unless specifically included as a subgrid phenomenology. A factor of two increase in the spatial resolution of such LES models will bring more improvement in the accuracy of the well-resolved scales than all the work in the world on the subgrid model of a more coarsely resolved LES model.