DNS 1-5 Computational Details

Front Page

Description

Computational Details

Quantification of Resolution

Statistical Data

Instantaneous Data

Storage Format

Computational Details

This section provides details of the computational approach used for the simulation of the present flow problem. Firstly, the main numerical features of the code MIGALE are given. Then, information about the computational grid is provided. Finally, the statistical quantities and their computation are explained.

Computational approach

The CFD code MIGALE can solve both compressible and incompressible flow problems and implements different flow models ranging from the Euler to the RANS equations. The solver uses the Discontinuous Galerkin (DG) method for the spatial discretization of the governing equations, here the compressible Navier-Stokes equations. The discontinuous nature of the numerical solution requires introducing a special treatment of the inviscid interface flux and of the viscous flux. For the former it is common practice to use suitably defined numerical flux functions, which ensure conservation and account for wave propagation. To this purpose, in the compressible case, the exact Riemann solver of Gottlieb and Groth [1] is mainly used. For the latter, the 2nd-scheme of Bassi and Rebay (BR2) is employed [2]. The devised method uses hierarchical and orthonormal polynomial basis functions defined in the physical (mesh) space and relies for the time integration on, primarily, high-order Rosenbrock linearly-implicit schemes. The Jacobian matrix of the spatial discretization is computed analytically and linear systems are solved using preconditioned GMRES methods from the PETSc library (Portable Extensible Toolkit for Scientific Computations) [4]. For production runs time integration is coupled with time-step adaptation strategies able to improve the robustness and the efficiency in terms of time-to-solution of simulations, [5].

For the present computation the fourth-order DG spatial discretization is combined with the fifth-order eight stages Rosenbrock-type scheme of Di Marzo [6].

References

[1] J.J.Gottlieb, C.P.T.Groth, “Assessment of Riemann solvers for unsteady one-dimensional inviscid flows of perfect gases”, J. Comput. Phys. 78, 1988

[2] F. Bassi, S.Rebay, G.Mariotti, S.Pedinotti, M.Savini, “A high-order accurate discontinuous finite element method for inviscid and viscous turbomachinery flows”, in: R. Decuypere, G. Dibelius (Eds.), Proceedings of the 2nd European Conference on Turbomachinery Fluid Dynamics and Thermodynamics, Technologisch Instituut, Antwerpen, Belgium, 1997

[3] Bassi, F., Botti, L., Colombo, A., Ghidoni, A., Massa, F., “Linearly implicit Rosenbrock-type Runge-Kutta schemes applied to the Discontinuous Galerkin solution of compressible and incompressible unsteady flows”, Computers and Fluids, 2015

[4] PETSc Web page

[5] G. Noventa, F. Massa, S. Rebay, F. Bassi, A. Ghidoni, “Robustness and efficiency of an implicit time-adaptive discontinuous Galerkin solver for unsteady flows”, Computers & Fluids, 2020

[6] Di Marzo, G., “RODAS5(4) - Méthodes de Rosenbrock d'ordre 5(4) adaptées aux problèmes différentiels-algébriques", MSc Mathematics Thesis, Faculty of Science, University of Geneva, 1993

Spatial and temporal resolution, grids

Computational domain extends in stream direction from $x/H=-12.7$ to $x/H=24.0$ and has a spanwise width equal to $\Delta z/H=3$. Top boundary is located at normal coordinate $y/H=181.6$. The grid is made of roughly 15 million elements with quadratic edges, resulting in more than 300 million Degrees of Freedom (DoF) per equation. Fig. 3 and Fig. 4 show details of the grid above the rounded step (lateral view) and the wall region (top view), respectively. In Fig. 4 a “sacrificial buffer” created downstream of the rounded step, i.e., for $x/H>13.8$, is clearly visible. This mesh coarsening is applied to reduce the solution gradients, thus mitigating spurious perturbations possibly originating at the outlet boundary.

Figure 3: Detail of the computational grid above the rounded step (lateral view)

Figure 4: Detail of the computational grid above the wall region, downstream the rounded step (top view)

For the temporal integration, a fifth order linearly implicit Rosenbrock scheme is applied with an adaptive time stepping technique. The resulting average time step is roughly $\Delta t\approx 1/110\,CTU$, being $CTU$ the convective time unit defined with respect to the reference velocity and the step height. In Tab. 3 are reported the wall space and time resolution at the checkpoint ($x/H=-3.51$). Here, in order to account of the high order nature of the numerical schemes employed, the wall resolution is obtained as

$\Delta x^{+}={{\dfrac {1}{\sqrt[{3}]{N_{DoF}}}}{\dfrac {\Delta x}{\delta _{\nu }}}},\qquad \Delta t^{+}={{\dfrac {1}{q}}{\dfrac {\Delta t\,u_{\tau }}{\delta _{\nu }}}}$,

being $N_{DoF}$ the number of Degrees of Freedom per equation and $q$ the time integration order (here $N_{DoF}=20$ and $q=5$).

The flow has been simulated for $40\,CTU$ with a DG polynomial approximation of degree 1. After that, the polynomial degree has been increased to 3 and the simulation has been continued for $50\,CTU$ before gathering statistics for and additional $75\,CTU$.

${\Delta x^{+}}$	${\Delta y_{1}^{+}}$	${\Delta z^{+}}$	${\Delta t^{+}}$
${17.8}$	${18.6}$	${1.30}$	${0.27}$

Table 3: Wall space and time resolution at the checkpoint ($x/H=-3.51$)

Computation of statistical quantities

Describe how the averages and correlations are obtained from the instantaneous results and how terms in the budget equations are computed, in particular if there are differences to the proposed approach in Introduction.

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Contributed by: Francesco Bassi, Alessandro Colombo, Francesco Carlo Massa — Università degli studi di Bergamo (UniBG)

Front Page

Description

Computational Details

Quantification of Resolution

Statistical Data

Instantaneous Data

Storage Format

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