A High-Order Algorithm for Compressible LES in CAA Applications

Abstract

A high-order finite-difference algorithm is proposed in the aim of LES and CAA applications. The subgrid scale dissipation is performed by the explicit high-order numerical filter used for numerical stability purpose. A shock-capturing non-linear filter is also implemented to deal with compressible discontinuous flows. In order to tackle complex geometries, an overset-grid approach is used. High-order interpolations make it possible to ensure the communication between overlapping domains. The whole algorithm is first validated on canonical flow problems to illustrate both its properties for shock-capturing as well as for accurate wave propagation. Then, the influence of the multi-domain approach on the high-order spatial accuracy is assessed. Afterwards, the algorithm is extended to dynamic mesh applications with overlapping grids. Finally, two industrial cases are presented to highlight the potential of the proposed algorithm.

Numerical study of self-induced transonic flow oscillations behind a sudden duct enlargement

“…Moreover, the symmetrical flow regime B is preferred for this aspect ratio h / H. The pressure in the corner p w measured 3 as a function of the outflow pressure p e is displayed in Fig. 19 teresis region is narrower than for the previous cases R2-R5, as shown in Fig. 13.…”

“…Fluid-structure interaction problems involving relative motion of multiple bodies can also be simulated. 19 For communication between grid boundaries that do not coincide, a high-order interpolation is used. Lagrangian polynomials were found by Sherer and Scott 20 to be best suited in terms of accuracy, execution time, and implementation aspects for the high-order overset grid approach.…”

A parametric study of the noise radiated by the flow around multiple bodies: direct noise computation of the influence of the separating distance in rod-airfoil flow configurations

“…4 To keep accuracy at its highest level, Lagrangian interpolation is performed thanks to 4th-order polynomials. 11 Finally, time integration of the solution is carried out by a 4th-order 6-step low-storage Runge-Kutta scheme, whose coefficients have been optimized in the Fourier space. 1 Subgrid-scale modeling is performed using explicit filtering of the flow variables.…”

Numerical Insight into Sound Sources of a Rod-Airfoil Flow Configuration Using Direct Noise Calculation

“…3 To keep accuracy at its highest level, Lagrangian interpolation is performed thanks to 4th-order polynomials. 10 Finally, time integration of the solution is carried out by a 4th-order 6-step low-storage Runge-Kutta scheme, whose coefficients have been optimized in the Fourier space. 1 Subgrid-scale modeling is performed using explicit filtering of the flow variables.…”