Large-Eddy im Yasni Exposé von Stefan Hickel

Large Eddy Simulation (LES) is a high-fidelity approach to the numerical ... Stefan Hickel, Antoine Devesa, Nikolaus A. Adams. 149 ...

Quality and Reliability of Large-Eddy Simulations - Computational resources have ... optimized discretizations, by Stefan Hickel, Nikolaus A. Adams; Spectral ...

Stefan Hickel (sh@tum.de) Institute of Aerodynamics, Technische Universitaet Muenchen ... Further development of Large Eddy Simulation faces as major obstacle ...

Quality and Reliability of Large-Eddy Simulations - Computational resources have ... optimized discretizations, by Stefan Hickel, Nikolaus A. Adams; Spectral ...

Dissertation von Stefan Hickel. “Implicit turbulence modeling for large-eddy simulation”. Zusammenfassung: In Grobstruktursimulationen turbulenter ...

Part I. Numerical and Mathematical Analysis of Subgrid-Scale-Model and Discretization Errors ... Stefan Hickel, Nikolaus A. Adams ...

Quality and Reliability of Large-eddy Simulations, Johan Meyers, Bernard J. ... of Physically Optimized Discretizations by Stefan Hickel and Nikolaus A. Adams ...

... Analysis of truncation errors and design of physically optimized discretizations, by Stefan Hickel, Nikolaus A. Adams; Spectral behavior of various ...

Dr.-Ing. Stefan Hickel. Rudolf-Schmidt-Burkhardt Gedächtnispreis. Dissertation "Implicite turbulence modeling for large-eddy simulation" Zusammenfassung>>

紀伊國屋書店 Quality and Reliability of Large-Eddy Simulations (ERCOFTAC Series) Vol. ... Discretizations Stefan Hickel Nikolaus A. Adams Spectral Behavior of Various ...

ERCOFTAC (European Research Community on Flow, Turbulence and Combustion) was ... Optimized Discretizations. Stefan Hickel, Nikolaus A. Adams . . . . . . 49 ...

Part I. Numerical and Mathematical Analysis of Subgrid-Scale-Model and Discretization Errors ... Stefan Hickel, Nikolaus A. Adams ...

Stefan Hickel. 1 , BinQian Zhang. 2 , and Nikolaus A. Adams. 1. 1. Institute of Aerodynamics, Technische Universit"at M"unchen, 85748 Garching, Germany ...

Startseite workflows diss Dissertation eingespielt Stefan Hickel. Originaltitel: Implicit Turbulence Modeling for Large-Eddy Simulation. Übersetzter Titel: ...

Turbulence modeling and the numerical discretization of the Navier-Stokes equations are strongly coupled in large-eddy simulations. The truncation error of common approximations for the convective terms can outweigh the effect of a physically sound subgrid-scale model. The subject of this thesis is the analysis and the control of local truncation errors in large-eddy simulations. We show that physical reasoning can be incorporated into the design of discretization schemes. Using systematic procedures, a nonlinear discretization method has been developed where numerical and turbulence-theoretical modeling are fully merged. The truncation error itself functions as an implicit turbulence model accurately representing the effects of unresolved turbulence. Various applications demonstrate the efficiency and reliability of the new method as well as the superiority of an holistic approach. Keywords: turbulence, transition, truncation error, implicit large eddy simulation, subgrid-scale modeling.

Further development of large-eddy simulation (LES) faces as major obstacles the strong coupling between subgrid-scale (SGS) modeling and the truncation error of the numerical discretization. One can exploit this link by developing discretization methods where the truncation error itself functions as an implicit SGS model. The adaptive local deconvolution method (ALDM) is an approach to LES of turbulent flows that represents a full coupling of SGS model and discretization scheme. To provide evidence for the validity of this new SGS model, well resolved large-eddy simulations of a fully turbulent flat-plate boundary-layer flow subjected to a constant adverse pressure gradient are conducted. Flow parameters are adapted to an available experiment. The Reynolds number based on the local free-stream velocity and momentum thickness is 670 at the inflow and 5100 at the separation point. Clauser’s pressure-gradient parameter increases monotonically from 0 up to approximately 100 since a constant pressure gradient is prescribed. The adverse pressure gradient leads to a highly unsteady and massive separation of the boundary layer. The numerical predictions agree well with theory and experimental data. Keywords: Large-eddy simulation; Subgrid-scale modeling; Boundary layer; Transition; Separation

Subgrid-scale models in LES operate on a range of scales which is marginally resolved by the discrete approximation. Accordingly, the discrete approximation method and the subgrid-scale model are linked. One can exploit this link by developing discretization methods from subgrid-scale models, or vice versa. Approaches where SGS models and numerical discretizations are fully linked are called implicit SGS models. Different approaches to SGS modeling can be taken. Mostly, given nonlinearly stable discretizations schemes for the convective fluxes are used as main element of implicit SGS models. Recently we have proposed to design nonlinear discretization schemes in such a way that their truncation error functions as SGS model in regions where the flow is turbulent and as a second-order accurate discretization in regions where the flow is laminar. In this paper we review the current status on this so-called adaptive local deconvolution method (ALDM) and provide some application results.

The subgrid-scale (SGS) model in a large-eddy simulation (LES) operates on a range of scales which is marginally resolved by discretization schemes. Accordingly, the discretization scheme and the subgrid-scale model are linked. One can exploit this link by developing discretization methods from subgrid-scale models, or the converse. Approaches where SGS models and numerical discretizations are fully merged are called implicit LES (ILES). Recently, we have proposed a systematic framework for the design, analysis, and optimization of nonlinear discretization schemes for implicit LES. In this framework parameters inherent to the discretization scheme are determined in such a way that the numerical truncation error acts as a physically motivated SGS model. The resulting so-called adaptive local deconvolution method (ALDM) for implicit LES allows for reliable predictions of isotropic forced and decaying turbulence and of unbounded transitional flows for a wide range of Reynolds numbers. In the present paper, ALDM is evaluated for the separated flow through a channel with streamwise-periodic constrictions at two Reynolds numbers Re = 2,808 and Re = 10,595. We demonstrate that, although model parameters of ALDM have been determined for isotropic turbulence at infinite Reynolds number, it successfully predicts mean flow and turbulence statistics in the considered physically complex, anisotropic, and inhomogeneous flow regime. It is shown that the implicit model performs at least as well as an established explicit model.

Further development of large-eddy simulation (LES) faces as major obstacles the strong coupling between subgrid-scale (SGS) modeling and the truncation error of the numerical discretization. One can exploit this link by developing discretization methods where the truncation error itself functions as an implicit SGS model. The name “implicit LES” is used for approaches that merge the SGS model and numerical discretization. In this paper, the implicit SGS modeling environment provided by the adaptive local deconvolution method is extended to LES of passive-scalar mixing. The resulting adaptive advection algorithm is discussed with respect to its numerical and turbulence-theoretical background. We demonstrate that the new method allows for reliable predictions of the turbulent transport of passive scalars in isotropic turbulence and in turbulent channel flow for a wide range of Schmidt numbers.

The adaptive local deconvolution method (ALDM) provides a systematic framework for the implicit large-eddy simulation (ILES) of turbulent flows. Exploiting numerical truncation errors, the subgrid scale model of ALDM is implicitly contained within the discretization. An explicit computation of model terms therefore becomes unnecessary. Subject of the present paper is the efficient implementation and the application to large-scale computations of this method. We propose a modification of the numerical algorithm that allows for reducing the amount of computational operations without affecting the quality of the LES results. Computational results for isotropic turbulence and plane channel flow show that the proposed simplified adaptive local deconvolution (SALD) method performs similarly to the original ALDM and at least as well as established explicit models.