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Complex models such as NLEVM and second-moment closures are far from being numerically robust, and significant efforts still need to be spent with respect to improving both their accuracy and efficiency Implementation of NLEVM in conjunction with Godunov-type methods and implicit schemes has been presented by the author and his collaborators in the recent past for both steady and unsteady compressible flows (30), (48) Results from dynamic-stall simulations around an oscillating aerofoil are shown in Fig 19 We note that similar vortex flow phenomena occur in both oscillating and ramping aerofoils (Fig 19) The results for the oscillating aerofoil correspond to subsonic flow conditions (Mra = 02, Re = 106) with mean incidence angle o = 15 degrees, amplitude, and reduced-frequency of oscillations i = 10 degrees and /* = 01, respectively.

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Took Sergio's answer and made some extension methods. I also changed the accumulation of strings into an iterator. public static class ...

Maas, 394 Mabbott, 49, 212, 213, 214, 215, 216 MacAllister, 237, 238, 239 Maccini, 54, 520 MacDonald, 499, 498 Machemer, 337 Maciag, 365

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The computations for the unsteady airloads have been compared with the corresponding experimental results from (50) The NLEVM provides overall better results but the differences between experiments and computations are still substantial Moreover, long computing times can be required in the case of complex models such as NLEVM or second-moment closures It has also been found (48) that in many flow cases the one-equation Spalart-Allmaras model (52) can provide similar results to the NLEVM This can also be seen in the results (Fig 110) from transonic buffet computations (53), where similar predictions for the buffet onset are obtained by the one-equation Spalart-Allmaras (52) and a non-linear eddy-viscosity model (47) Concerning the LES approach the main issue is to account for the unresolved small scales In the context of LES the unresolved structures are represented by a subgrid scale model (SGS).

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The modelling difficulties, particularly in wall bounded flows, seem to be similar to those encountered in the RANS approach Additionally, LES requires fully three-dimensional unsteady computations to be performed, though some successful two-dimensional simulations of flows with large separation have also been reported (55) Yet, the classical LES approach resorts to very fine meshes, though coarser than those used in DNS The objective of DNS is to resolve all scales of turbulent motion down to the Kolmogorov eddy Adequate resolution must ensure that simulated structures are correct and not numerical artifacts However, currently DNS for turbulent flows of engineering interest is not feasible due to the lack of adequate computing resources In the case of simulations of complex engineering flows the question is also whether one needs to simulate the flow down to the smallest scale.

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The Kolmogorov spectrum (56) describes how the energy density of turbulent structures decreases rapidly with increasing the wave number, where the Kolmogorov scale is the scale at which the viscous dissipation dominates the inertial flow of the fluid The downward transfer of energy from large to small scales is called the turbulent cascade process The latter stops at the Kolmogorov scale, where an eddy is so small that it diffuses rapidly Previous computations, experiments and theoretical analysis (see eg (1) has shown that the physics of the turbulent cascade is controlled by the macroscopic scales of the flow and the process of dissipation of this energy.

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