نتایج جستجو برای: direct numerical simulation dns
تعداد نتایج: 1204992 فیلتر نتایج به سال:
The paper presents a method to perform direct numerical simulations (DNS) of a jet actuator flow inside a turbulent flat plate boundary layer (TBL). A structured finite difference method is used for the simulations. The numerical scheme is adapted to account for the large scale differences both in geometric and fluid dynamic aspect. Analytical mesh transformations have been implemented to resol...
This paper focusses on high order compact schemes for direct numerical simulation (dns) and large eddy simulation (les) for flow separation, transition, tip vortex, and flow control. We discuss the fundamental issues of high quality grid generation, high order schemes for curvilinear coordinates, the cfl condition for complex geometry, and high-order weighted compact schemes for shock capturing...
In this paper, we present uncertainties of statistical quantities direct numerical simulations (DNS) with small errors. The are analysed for channel flow and a separation case in confined backward facing step (BFS) geometry. infinite has two homogeneous directions is usually exploited to speed-up the convergence results. As show, such procedure reduces results by up an order magnitude. This eff...
The Lagrangian vortex method offers an alternative numerical approach for direct numerical simulation of turbulence. The fact that it uses the fast multipole method (FMM)—a hierarchical algorithm for N-body problems with highly scalable parallel implementations—as numerical engine makes it a potentially good candidate for exascale systems. However, there have been few validation studies of Lagr...
The build-up of soot deposits on cold wall surfaces is a problem of unknown significance for combustion applications. Soot deposits are due to thermophoretic transport and are generally ignored in theoretical and numerical analysis. We examine here the relationship between the rate of soot deposition and the wall convective heat flux, using both Direct Numerical Simulation (DNS) and Large Eddy ...
Computational fluid dynamics (CFD) is increasingly used to simulate complex industrial systems. Most CFD analysis relies on the Reynolds-averaged Navier-Stokes (RANS) approach and traditional two-equation turbulence models. Higher-fidelity approaches to the simulation of turbulence such as wallresolved large eddy simulation (LES) and direct numerical simulation (DNS) remain limited to smaller a...
In this note, the importance of spectral properties viscous flux discretization in solving compressible Navier-Stokes equations for turbulent flow simulations is discussed. We studied six different methods, divided into two classes, with poor and better representation at high wavenumbers. Both theoretical numerical results have revealed that method wavenumbers, denoted as $\alpha$-damping type ...
Since the direct numerical simulation (DNS) of aeroacoustic noise requires the numerical solution of the compressible Navier-Stokes equations in a large computational domain, it is computationally too demanding to solve computational aeroacoustics (CAA) applications using this technique only. In this paper a number of different hybrid approaches, where the computational domain is split into a s...
Mach wave radiation in a turbulent fully expanded supersonic jet is revisited. Our goal is to determine the extent to which predictions for the radiated sound that are based on linearized analysis agree with solution of the full nonlinear equations. To this end, we solve the linearized Navier-Stokes equations (LNS) with precisely the same mean flow and inflow disturbances as a previous direct n...
The goal of this work is to develop low order dynamical systems models for the unsteady aerodynamic forces on small wings and to better understand the physical characteristics of unsteady laminar separation. Reduced order models for a fixed, high angle of attack flat plate are obtained through Galerkin projection of the governing Navier-Stokes equations onto POD modes. Projected models are comp...
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