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A priori analysis of subgrid-scale terms in compressible transcritical real gas flows

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A priori analysis of subgrid-scale terms in compressible transcritical real gas flows

Abstract

Of interest to the research community dealing with real gas flows, this study analyzes the influence of the physical complexity of real gases on the amplitude of subgrid-scale (SGS) terms present in the filtered Navier–Stokes equations to be solved in large eddy simulations. The direct numerical simulation results of three academic configurations (homogeneous isotropic turbulence, mixing layer, and channel flow) are filtered from the largest scale in the domain down to the Kolmogorov length scale. The analysis of the filtered flow variables consistently shows that the SGS turbulent stress and the SGS pressure cannot be neglected in the momentum equation. In the total energy equation, SGS pressure work and SGS internal and kinetic fluxes are found to be significant in the inertial zone of the turbulent kinetic energy spectrum. Since in the inertial zone, which corresponds to large filter sizes, specific models have not yet been designed for some of these terms, this study calls for such a modeling effort that will benefit the real gas and organic Rankine cycles research communities.
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... Therefore, LES has a wide range of applications. [8][9][10] The rise of machine learning has injected new vitality into the study of LES modeling. [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] Gamahara and Hattori developed a data-driven SGS model using DNS data of channel turbulence, based on an artificial neural network (ANN). ...
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