An a posteriori-implicit turbulent model with automatic dissipation adjustment for Large Eddy Simulation of compressible flows
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An a posteriori-implicit turbulent model with automatic dissipation adjustment for Large Eddy Simulation of compressible flowsAutor(es)
Fecha
2020Cita bibliográfica
NOGUEIRA, Xesús, et al. An a posteriori-implicit turbulent model with automatic dissipation adjustment for Large Eddy Simulation of compressible flows. Computers & Fluids, 2020, vol. 197, p. 104371. https://doi.org/10.1016/j.compfluid.2019.104371
Resumen
[Abstract] In this work we present an a posteriori high-order finite volume scheme for the computation of compressible turbulent flows. An automatic dissipation adjustment (ADA) method is combined with the a posteriori paradigm, in order to obtain an implicit subgrid scale model and preserve the stability of the numerical method. Thus, the numerical scheme is designed to increase the dissipation in the control volumes where the flow is under-resolved, and to decrease the dissipation in those cells where there is excessive dissipation. This is achieved by adding a multiplicative factor to the dissipative part of the numerical flux. In order to keep the stability of the numerical scheme, the a posteriori approach is used. It allows to increase the dissipation quickly in cells near shocks if required, ensuring the stability of the scheme. Some numerical tests are performed to highlight the accuracy and robustness of the proposed numerical scheme.
Palabras clave
High-order methods
Compressible flows
Computational fluid dynamics
Implicit large eddy simulation
A posteriori shock capturing
Compressible flows
Computational fluid dynamics
Implicit large eddy simulation
A posteriori shock capturing
Descripción
© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/(opens in new tab/window)
https://www.elsevier.com/about/policies-and-standards/sharing . This is an accepted version of the following published document: https://doi.org/10.1016/j.compfluid.2019.104371
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