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:

 OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids. (link)

 OpenSBLI: A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures. (link)

 On the performance of WENO/TENO schemes to resolve turbulence in DNS/LES of high‐speed compressible flows. (link)