Abstract

The quantitative measure of dissipative properties of different numerical schemes is crucial to computational methods in the field of aerospace applications. Therefore, the objective of the present study is to examine the resolving power of Monotonic Upwind Scheme for Conservation Laws (MUSCL) scheme with three different slope limiters: one second-order and two third-order used within the framework of Implicit Large Eddy Simulations (ILES). The performance of the dynamic Smagorinsky subgrid-scale model used in the classical Large Eddy Simulation (LES) approach is examined. The assessment of these schemes is of significant importance to understand the numerical dissipation that could affect the accuracy of the numerical solution. A modified equation analysis has been employed to the convective term of the fully-compressible Navier–Stokes equations to formulate an analytical expression of truncation error for the second-order upwind scheme. The contribution of second-order partial derivatives in the expression of truncation error showed that the effect of this numerical error could not be neglected compared to the total kinetic energy dissipation rate. Transitions from laminar to turbulent flow are visualized considering the inviscid Taylor–Green Vortex (TGV) test-case. The evolution in time of volumetrically-averaged kinetic energy and kinetic energy dissipation rate have been monitored for all numerical schemes and all grid levels. The dissipation mechanism has been compared to Direct Numerical Simulation (DNS) data found in the literature at different Reynolds numbers. We found that the resolving power and the symmetry breaking property are enhanced with finer grid resolutions. The production of vorticity has been observed in terms of enstrophy and effective viscosity. The instantaneous kinetic energy spectrum has been computed using a three-dimensional Fast Fourier Transform (FFT). All combinations of numerical methods produce a k − 4 spectrum at t * = 4 , and near the dissipation peak, all methods were capable of predicting the k − 5 / 3 slope accurately when refining the mesh.

Highlights

  • IntroductionThe complexity of modelling turbulent flows is perhaps best illustrated by the wide variety of approaches that are still being developed in the turbulence modelling community

  • The complexity of modelling turbulent flows is perhaps best illustrated by the wide variety of approaches that are still being developed in the turbulence modelling community.The Reynolds-Averaged Navier–Stokes (RANS) approach is the most popular tool used in industry for the study of turbulent flows

  • The eight-fold symmetry of the Taylor–Green vortex is clearly visible in Figure 2a, where the initial two-dimensional vorticity field features a symmetry in all planes located at a distance π in the computational domain

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Summary

Introduction

The complexity of modelling turbulent flows is perhaps best illustrated by the wide variety of approaches that are still being developed in the turbulence modelling community. The Reynolds-Averaged Navier–Stokes (RANS) approach is the most popular tool used in industry for the study of turbulent flows. RANS is based on the idea of dividing the instantaneous parameters into fluctuations and mean values. The Reynolds stresses that appear in the conservation laws need to be modelled using semi-empirical turbulence models. Direct Numerical Simulation (DNS) is another approach used to study turbulent flows where all the scales of motion are resolved. It should be noted that even using the highest performance computers, it is very difficult to study high Reynolds number

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