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  • Cited by 8
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    This chapter has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Fureby, C. 2017. Whither Turbulence and Big Data in the 21st Century?. p. 375.

    Larsson, A. Zettervall, N. Hurtig, T. Nilsson, E. J. K. Ehn, A. Petersson, P. Alden, M. Larfeldt, J. and Fureby, C. 2017. Skeletal Methane–Air Reaction Mechanism for Large Eddy Simulation of Turbulent Microwave-Assisted Combustion. Energy & Fuels, Vol. 31, Issue. 2, p. 1904.

    Uritsky, Vadim M. Roberts, Merrill A. DeVore, C. Richard and Karpen, Judith T. 2017. Reconnection-driven Magnetohydrodynamic Turbulence in a Simulated Coronal-hole Jet. The Astrophysical Journal, Vol. 837, Issue. 2, p. 123.

    Fernandez, Pablo Nguyen, Cuong Roca, Xevi and Peraire, Jaime 2016. Implicit large-eddy simulation of compressible flows using the Interior Embedded Discontinuous Galerkin method.

    Fedina, E. and Fureby, C. 2011. A comparative study of flamelet and finite rate chemistry LES for an axisymmetric dump combustor. Journal of Turbulence, Vol. 12, Issue. , p. N24.

    Uranga, A. Persson, P.-O. Drela, M. and Peraire, J. 2011. Implicit Large Eddy Simulation of transition to turbulence at low Reynolds numbers using a Discontinuous Galerkin method. International Journal for Numerical Methods in Engineering, Vol. 87, Issue. 1-5, p. 232.

    Feymark, Andreas Alin, Niklas Bensow, Rickard and Fureby, Christer 2010. LES of an Oscillating Cylinder in a Steady Flow.

    Fedina, Ekaterina Fureby, Christer and Helte, Andreas 2010. Predicting Mixing and Combustion in the Afterburn Stage of Air Blasts.

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  • Print publication year: 2007
  • Online publication date: January 2010

4 - Numerics for ILES

Summary

Introduction

Large eddy simulation (LES) has emerged as the next-generation simulation tool for handling complex engineering, geophysical, astrophysical, and chemically reactive flows. As LES moves from being an academic tool to being a practical simulation strategy, the robustness of the LES solvers becomes a key issue to be concerned with, in conjunction with the classical and well-known issue of accuracy. For LES to be attractive for complex flows, the computational codes must be readily capable of handling complex geometries. Today, most LES codes use hexahedral elements; the grid-generation process is therefore cumbersome and time consuming. In the future, the use of unstructured grids, as used in Reynolds-averaged Navier–Stokes (RANS) approaches, will also be necessary for LES. This will particularly challenge the development of high-order unstructured LES solvers. Because it does not require explicit filtering, Implicit LES (ILES) has some advantages over conventional LES; however, numerical requirements and issues are otherwise virtually the same for LES and ILES. In this chapterwe discuss an unstructured finite-volume methodology for both conventional LES and ILES, that is particularly suited for ILES. We believe that the next generation of practical computational fluid dynamics (CFD) models will involve structured and unstructured LES, using high-order flux-reconstruction algorithms and taking advantage of their built-in subgrid-scale (SGS) models.

ILES based on functional reconstruction of the convective fluxes by use of high-resolution hybrid methods is the subject of this chapter. We use modified equation analysis (MEA) to show that the leading-order truncation error terms introduced by such methods provide implicit SGS models similar in form to those of conventional mixed SGS models.

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Implicit Large Eddy Simulation
  • Online ISBN: 9780511618604
  • Book DOI: https://doi.org/10.1017/CBO9780511618604
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