DNS of a counter-flow channel configuration
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. #============================================================================================== # 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 # ============================================================================================== 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 \(M_t = {\sqrt{\langle u^{\prime}u^{\prime} \rangle+\langle v^{\prime}v^{\prime} \rangle+\langle w^{\prime}w^{\prime} \rangle}}/{{\langle a \rangle}}\). # ============================================================================================== 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)
Lusher, David
44ff9096-3c84-440a-9f64-946636aff985
Hamzehloo, Arash
456b886d-3edb-4dd3-9512-0cb0fb5cf146
Laizet, Sylvain
b5c2e5cf-1d8d-4615-9d18-f086b008ae51
Sandham, Neil
0024d8cd-c788-4811-a470-57934fbdcf97
Lusher, David
44ff9096-3c84-440a-9f64-946636aff985
Hamzehloo, Arash
456b886d-3edb-4dd3-9512-0cb0fb5cf146
Laizet, Sylvain
b5c2e5cf-1d8d-4615-9d18-f086b008ae51
Sandham, Neil
0024d8cd-c788-4811-a470-57934fbdcf97
Abstract
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. #============================================================================================== # 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 # ============================================================================================== 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 \(M_t = {\sqrt{\langle u^{\prime}u^{\prime} \rangle+\langle v^{\prime}v^{\prime} \rangle+\langle w^{\prime}w^{\prime} \rangle}}/{{\langle a \rangle}}\). # ============================================================================================== 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)
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Published date: 25 March 2021
Identifiers
Local EPrints ID: 472159
URI: http://eprints.soton.ac.uk/id/eprint/472159
PURE UUID: 4d94ed64-d2e8-4568-960b-19978268cd4e
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Date deposited: 28 Nov 2022 17:58
Last modified: 06 May 2023 01:36
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Contributors
Contributor:
David Lusher
Contributor:
Arash Hamzehloo
Contributor:
Sylvain Laizet
Contributor:
Neil Sandham
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