DNS of a counter-flow channel configuration

Mean flow and turbulence statistics of a compressible turbulent counter-flow channel configuration. This dataset is based on direct numerical simulations conducted using OpenSBLI (https://opensbli.github.io/), a Python-based automatic source code generation and parallel computing framework for finite difference discretisation.

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# Please cite the following paper when publishing using this dataset:  
# Title: Direct numerical simulation of compressible turbulence in a counter-flow channel configuration 
# Authors: Arash Hamzehloo, David Lusher, Sylvain Laizet and Neil Sandham
# Journal: Physical Review Fluids 
# DOI: https://doi.org/10.1103/PhysRevFluids.6.094603 
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Please note:

• Tables 1 and 2 of the above paper provide more detailed information on the counter-flow channels of this dataset. 
• Each folder name of this dataset includes the Mach number, Reynolds number, domain size and grid resolution of a particular case, respectively.
• In each file, the first column contains the grid-point coordinates in the wall-normal direction (\(y\)) with the channel centreline located at \(y=0\). 
• The mean stresses are defined as \(\langle u_i^{\prime}u_j^{\prime}\rangle=\langle u_i u_j \rangle - \langle u_i \rangle \langle u_j \rangle \). Angle brackets denote averages over the homogeneous spatial directions (streamwise \(x\) and spanwise \(z\)) and time.
• The Favre average is related to the Reynolds average as \(\langle \rho \rangle \{u_i^{\prime\prime}u_j^{\prime\prime}\}=\langle \rho u_i u_j \rangle - \langle \rho \rangle \langle u_i \rangle \langle u_j \rangle\).
• The mean Mach number is defined as \(\langle M \rangle = {\sqrt{\langle u \rangle^2+\langle v \rangle^2+\langle w \rangle^2}}/{{\langle a \rangle}}\) where \(a\) is the local speed of sound.
• The turbulent Mach number is defined as \(M_t = {\sqrt{\langle u^{\prime}u^{\prime} \rangle+\langle v^{\prime}v^{\prime} \rangle+\langle w^{\prime}w^{\prime} \rangle}}/{{\langle a \rangle}}\).

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Details of the OpenSBLI framework, its numerical methodology and existing flow configurations can be found in the following papers:

1.  OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids. (link)
2.  OpenSBLI: A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures. (link)
3.  On the performance of WENO/TENO schemes to resolve turbulence in DNS/LES of high‐speed compressible flows. (link)