Detached-eddy simulation (DES) is well understood in thin boundary layers, with the turbulence model in its Reynolds-averaged Navier–Stokes (RANS) mode and flattened grid cells, and in regions of massive separation, with the turbulence model in its large-eddy simulation (LES) mode and grid cells close to isotropic. However its initial formulation, denoted DES97 from here on, can exhibit an incorrect behavior in thick boundary layers and shallow separation regions. This behavior begins when the grid spacing parallel to the wall Δ∥ becomes less than the boundary-layer thickness δ, either through grid refinement or boundary-layer thickening. The grid spacing is then fine enough for the DES length scale to follow the LES branch (and therefore lower the eddy viscosity below the RANS level), but resolved Reynolds stresses deriving from velocity fluctuations (“LES content”) have not replaced the modeled Reynolds stresses. LES content may be lacking because the resolution is not fine enough to fully support it, and/or because of delays in its generation by instabilities. The depleted stresses reduce the skin friction, which can lead to premature separation.

/pdf/a-new-version-of-detached-eddy-simulation-resistant-to-yuj0rxxfha.pdf

A new version of detached-eddy simulation, resistant to ambiguous grid densities

A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities

Computational Fluid Dynamics: Principles and Applications, Third Edition presents students, engineers, and scientists with all they need to gain a solid understanding of the numerical methods and principles underlying modern computation techniques in fluid dynamics By providing complete coverage of the essential knowledge required in order to write codes or understand commercial codes, the book gives the reader an overview of fundamentals and solution strategies in the early chapters before moving on to cover the details of different solution techniques

	This updated edition includes new worked programming examples, expanded coverage and recent literature regarding incompressible flows, the Discontinuous Galerkin Method, the Lattice Boltzmann Method, higher-order spatial schemes, implicit Runge-Kutta methods and parallelization

	An accompanying companion website contains the sources of 1-D and 2-D Euler and Navier-Stokes flow solvers (structured and unstructured) and grid generators, along with tools for Von Neumann stability analysis of 1-D model equations and examples of various parallelization techniques



	
		Will provide you with the knowledge required to develop and understand modern flow simulation codes
	
		Features new worked programming examples and expanded coverage of incompressible flows, implicit Runge-Kutta methods and code parallelization, among other topics
	
		Includes accompanying companion website that contains the sources of 1-D and 2-D flow solvers as well as grid generators and examples of parallelization techniques

Computational Fluid Dynamics: Principles and Applications Ed. 3

Detached-eddy simulation (DES) was first proposed in 1997 and first used in 1999, so its full history can be surveyed. A DES community has formed, with adepts and critics, as well as new branches. The initial motivation of high–Reynolds number, massively separated flows remains, for which DES is convincingly more capable presently than either unsteady Reynolds-averaged Navier-Stokes (RANS) or large-eddy simulation (LES). This review discusses compelling examples, noting the visual and quantitative success of DES. Its principal weakness is its response to ambiguous grids, in which the wall-parallel grid spacing is of the order of the boundary-layer thickness. In some situations, DES on a given grid is then less accurate than RANS on the same grid or DES on a coarser grid. Partial remedies have been found, yet dealing with thickening boundary layers and shallow separation bubbles is a central challenge. The nonmonotonic response of DES to grid refinement is disturbing to most observers, as is the absence of...

Detached-Eddy Simulation

The numerical simulation of high Reynolds number flows is hampered by model accuracy if the Reynolds-averaged Navier–Stokes (RANS) equations are used, and by computational cost if direct or large-eddy simulations (LES) that resolve the near-wall layer are employed. The cost of a calculation scales like the Reynolds number to the power 3 for direct numerical simulations, or 2.4 for LES, making the resolution of the wall layer at high Reynolds number infeasible even with the most advanced computers. In LES, an attractive alternative to compute high-Re flows is the use of wall-layer models, in which only the outer layer is resolved, while the near-wall region is modeled. Three broad classes of approaches are presently used: bypassing this region altogether using wall functions, solving a separate set of equations in the near-wall region, weakly coupled to the outer flow, or simulating the near-wall region in a global, Reynolds-averaged, sense. These approaches are discussed and their ranges of applicability are highlighted. Various unresolved issues in wall-layer modeling are presented.

Wall-layer models for large-eddy simulations

A Scale-Adaptive Simulation Model for Turbulent Flow Predictions

The paper summarises the validation activity performed with the Scale-Adaptive Simulation turbulence model (SAS model) using the two commercial CFD solvers, ANSYS-FLUENT and ANSYS-CFX. Both the KSKL-SAS and the SST-SAS model variants have been tested, although most cases have been computed with the second. The turbulence-resolving capability of the SAS method has been validated with a representative set of test cases, covering both underlying generic flows as well as practical engineering applications. In addition to the purely aerodynamic flows with massive separation and heat transfer they include also such physical phenomena as turbulent combustion and aeroacoustics. The illustrating results show the potentials of the SAS approach for industrial flow simulations. Most of the test case simulations were conducted during the recent EU project “DESider”.

The Scale-Adaptive Simulation Method for Unsteady Turbulent Flow Predictions. Part 2: Application to Complex Flows

Assessment of two-equation turbulence models for transonic flows

A new oil-fringe imaging fkin friction (FISF) technique to measure skin friction on wind tunnel models is presented. In the method used to demonstrate the technique, lines of oil are applied on surfaces that connect the intended sets of measurement points, and then a wind tunnel is run so that the oil thins and forms interference fringes that are spaced proportional to local skin friction. After a run the fringe spacings are imaged with a CCD-array digital camera and measured on a computer. Skin friction and transition measurements on a two-dimensional wing are presented and compared with computational predictions.

Boundary-layer transition and global skin friction measurement with an oil-fringe imaging technique

A new oil-fringe imaging fkin friction (FISF) technique to measure skin friction on wind tunnel models is presented In the method used to demonstrate the technique, lines of oil are applied on surfaces that connect the intended sets of measurement points, and then a wind tunnel is run so that the oil thins and forms interference fringes that are spaced proportional to local skin friction After a run the fringe spacings are imaged with a CCD-array digital camera and measured on a computer Skin friction and transition measurements on a two-dimensional wing are presented and compared with computational predictions

Florian R. Menter

Papers

A Scale-Adaptive Simulation Model for Turbulent Flow Predictions

The Scale-Adaptive Simulation Method for Unsteady Turbulent Flow Predictions. Part 2: Application to Complex Flows

Assessment of two-equation turbulence models for transonic flows

Boundary-layer transition and global skin friction measurement with an oil-fringe imaging technique

Boundary-layer transition and global skin friction measurement with an oil-fringe imaging technique