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Merge pull request #322 from CFD-GO/develop
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‎.github/workflows/test.yml

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name: Testing the test
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on: [ push ]
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jobs:
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test:
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runs-on: ${{ matrix.os }}
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strategy:
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matrix:
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os: [ubuntu-latest, macos-latest]
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steps:
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- uses: CFD-GO/action_TCLB_test@master
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with:
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repository: ${{ github.repository }}
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ref: ${{ github.ref }}
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install: true

‎.travis.yml

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env:
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secure: "gDINAbE+apFUrReGDClqtSd4ir1ivFww/EjslD2XA8igmwELA0Kkom3z+X6HiMjlPaNLK5oRoyD7BkFSJ9Sf1i6z2+iLVmqJoOLaexZXM09C557Xmh38DisHTvQf6IVg0TRvQ8DEGDfFMrNr5jjDpXdPYs2sVJPW1Mi0Hwehtvt1Siuxr8bkoa/p6qZLbmhYl6ETGqFXDMmRWKFMaJpJ38BScwWIPgVqwSOcejhEdaPUuGtOYSirUhUDWoSQmOUPfbHfadIAT9+OPDY4p91eQmDQGNj9ZgWMvU8dECrrzE2Z6UfbO+swXmfMWe0BYwEpcGtYMG19y6dEKh4TmrEPR8Y/9SaVFiY/PPm906agKeJdGwHdokYqcjB/STSR83ni+b3qAfIgwYW2pcSMSEpbn+kUp70k9emV3KVJVIg3G/s4fEC1bip5wkBAYInPGa+FmNJTM8Y3iSHeQmuv2zia5od5RJDZg98kf0nXv9iEWEYrQl2KkEGNPK+bsWinA0KES1cZ21aMnPENf7mhyOsUUEYX4oCCxzzR16PCWWx4b7E4SBDweU5DfsEuwByjAImTOArSuofv1QnXynmDDD5W3TVDqx+067pMCE4FLV1yWqqrnaoPpWeWGlhTQStbO3xYSNgUNMma8pYEQStTpdkgXt4gx6RHaCjZwZ/FZx1rZRk="
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script:
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- tools/install.sh rpackage jsonlite
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- tools/install.sh rpackage yaml
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- tools/install.sh rpackage XML
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- tools/install.sh --rpackage jsonlite
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- tools/install.sh --rpackage yaml
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- tools/install.sh --rpackage XML
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- make configure
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- ./configure --disable-cuda
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- mkdir -p wiki/xml wiki/images wiki/schema

‎README.md

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CudneLB - the templated version
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===
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- [![Build Status](https://travis-ci.org/CFD-GO/TCLB.svg?branch=develop)](https://travis-ci.org/CFD-GO/TCLB) [![codecov](https://codecov.io/gh/CFD-GO/TCLB/branch/master/graph/badge.svg)](https://codecov.io/gh/CFD-GO/TCLB) [![documentation](https://raw.githubusercontent.com/CFD-GO/documents/master/assets/documentation.svg?sanitize=true)](https://docs.tclb.io/) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3672102.svg)](https://doi.org/10.5281/zenodo.3672102) - Stable release [(`master` branch)](https://github.com/CFD-GO/TCLB/tree/master)
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- [![Build Status](https://travis-ci.org/CFD-GO/TCLB.svg?branch=develop)](https://travis-ci.org/CFD-GO/TCLB) [![codecov](https://codecov.io/gh/CFD-GO/TCLB/branch/develop/graph/badge.svg)](https://codecov.io/gh/CFD-GO/TCLB) [![documentation](https://raw.githubusercontent.com/CFD-GO/documents/master/assets/documentation.svg?sanitize=true)](https://develop.docs.tclb.io/) - Current release [(`develop` branch)](https://github.com/CFD-GO/TCLB/tree/develop)
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CudneLB is a MPI+CUDA or MPI+CPU high-performance CFD simulation code, based on Lattice Boltzmann Method.
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![TCLB Solver Header](https://raw.githubusercontent.com/CFD-GO/documents/master/assets/header.png)
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TCLB Solver
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===
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TCLB is a MPI+CUDA or MPI+CPU high-performance Computational Fluid Dynamics simulation code, based on the Lattice Boltzmann Method.
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It provides a clear interface for calculation of complex physics, and the implementation of new models.
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## Installation
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- Stable release [(`master` branch)](https://github.com/CFD-GO/TCLB/tree/master):<br/>[![Build Status](https://travis-ci.org/CFD-GO/TCLB.svg?branch=master)](https://travis-ci.org/CFD-GO/TCLB) [![codecov](https://codecov.io/gh/CFD-GO/TCLB/branch/master/graph/badge.svg)](https://codecov.io/gh/CFD-GO/TCLB) [![documentation](https://raw.githubusercontent.com/CFD-GO/documents/master/assets/documentation.svg?sanitize=true)](https://docs.tclb.io/) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3672102.svg)](https://doi.org/10.5281/zenodo.3973739)
9+
- Current release [(`develop` branch)](https://github.com/CFD-GO/TCLB/tree/develop):<br/>[![Build Status](https://travis-ci.org/CFD-GO/TCLB.svg?branch=develop)](https://travis-ci.org/CFD-GO/TCLB) [![codecov](https://codecov.io/gh/CFD-GO/TCLB/branch/develop/graph/badge.svg)](https://codecov.io/gh/CFD-GO/TCLB) [![documentation](https://raw.githubusercontent.com/CFD-GO/documents/master/assets/documentation.svg?sanitize=true)](https://develop.docs.tclb.io/)
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Just clone the repo (or download the [zip file](https://github.com/CFD-GO/TCLB/archive/master.zip)):
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## How to use it
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**Install**
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```bash
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git clone https://github.com/CFD-GO/TCLB.git
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cd TCLB
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```
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If you want a more recent (but less stable) version, you could try the development branch:
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**Configure**
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```bash
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git clone -b develop https://github.com/CFD-GO/TCLB.git
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cd TCLB
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make configure
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./configure --enable-graphics --with-cuda-arch=sm_30
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```
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**Compile**
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```bash
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make d2q9
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```
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**Run**
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```bash
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CLB/d2q9/main example/flow/2d/karman.xml
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```
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### Dependencies
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## More information
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27-
You'll need:
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- [R](https://www.r-project.org/)
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- packages for R: [optparse](https://cran.r-project.org/package=optparse), [numbers](https://cran.r-project.org/package=numbers), [rtemplate](https://github.com/llaniewski/rtemplate), [gvector](https://github.com/llaniewski/gvector), [polyAlgebra](https://github.com/llaniewski/polyAlgebra)
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- [nVidia CUDA](https://developer.nvidia.com/cuda-zone) (if you want to use GPU)
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- [python](https://www.python.org/), [numpy](http://www.numpy.org/) (if you want to use the integrated python interpreter)
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- [python](https://www.python.org/), [sympy](http://www.sympy.org/) and R package: [rPython](https://cran.r-project.org/package=rPython) (if you want to develop a model using python instead of R)
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- [MPI](https://en.wikipedia.org/wiki/Message_Passing_Interface) (e.g. [OpenMPI](http://www.open-mpi.org/))
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### Documentation
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35-
You can install many of these with the tools/install.sh script (note it requires sudo):
36+
The documentation (including tutorials) is published at
37+
[docs.tclb.io](https://docs.tclb.io/).
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37-
```bash
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sudo tools/install.sh cuda 6.5-14 # only if your GPU supports cuda
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sudo tools/install.sh r
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sudo tools/install.sh openmpi
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tools/install.sh rdep
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sudo tools/install.sh python-dev
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tools/install.sh rpython
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sudo tools/install.sh module # only on CentOS
45-
```
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For the `develop` version, the most recent documentation can be found at
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[develop.docs.tclb.io](https://develop.docs.tclb.io/).
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42+
You can contribute to the documentation at
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[CFD-GO/TCLB_docs](https://github.com/CFD-GO/TCLB_docs).
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The `install.sh` script is designed to work on Ubuntu (e.g. on the [Travis-CI](https://travis-ci.org/CFD-GO/TCLB) VMs).
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The `install.sh` script should work on CentOS.
49-
You can install the **`sudo`** parts by yourself, and use script to install R packages: rdep and rpython.
45+
### Supported architectures
46+
This code is designed to run on **Linux**. We strongly recommend using Linux for compilation, computation and postprocessing.
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48+
Nevertheless, TCLB can be compiled on Windows (CPU only), using the [Windows Subsystem for Linux](https://pl.wikipedia.org/wiki/Windows_Subsystem_for_Linux). It also can be compiled on MacOS (also CPU only). Both Debian and Red Hat based Linux distributions are supported by the `install.sh` script described below, as is MacOS (with `brew` package manager).
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50+
### Dependencies
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52-
### Compilation
53-
This should work:
52+
For the code to compile and work you'll need a few things:
53+
- [R](https://www.r-project.org/) and some R packages ([optparse](https://cran.r-project.org/package=optparse), [numbers](https://cran.r-project.org/package=numbers), [rtemplate](https://github.com/llaniewski/rtemplate), [gvector](https://github.com/llaniewski/gvector), [polyAlgebra](https://github.com/llaniewski/polyAlgebra))
54+
- [MPI](https://en.wikipedia.org/wiki/Message_Passing_Interface). We recommend [OpenMPI](http://www.open-mpi.org/)
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- To use your GPU, you'll need [nVidia CUDA](https://developer.nvidia.com/cuda-zone)
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- To integrate TCLB with R, you'll need R package [rinside](https://github.com/eddelbuettel/rinside)
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- To integrate TCLB with Python, you'll need [python](https://www.python.org/), [numpy](http://www.numpy.org/) with libraries and headers
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- To develop a model using Python, you'll need [python](https://www.python.org/), [sympy](http://www.sympy.org/) and R package: [rPython](https://cran.r-project.org/package=rPython)
59+
60+
You can install many of these with the provided `tools/install.sh` script (note that this requires sudo):
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```bash
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module load mpi/openmpi-x86_64 # only on CentOS
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make configure
57-
./configure --enable-double --enable-graphics --with-cuda-arch=sm_20
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# only CPU ./configure --enable-double --disable-cuda
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make d2q9
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sudo tools/install.sh essentials # Installs essential system packages needed by TCLB
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sudo tools/install.sh r # Installs R
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sudo tools/install.sh openmpi # Installs OpenMPI
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tools/install.sh rdep # Installs needed R packages
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sudo tools/install.sh cuda # Installs CUDA (we recommend to do it on your own)
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sudo tools/install.sh python-dev # Installs Python libraries with headers
6068
```
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## Usage
70+
You can run the `tools/install.sh` script with the `--dry` option, which will print the commands to run, so you can run them on your own.
71+
*We do not recommend running anything with sudo without checking*
72+
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### `develop` Branch:
74+
If you want a more recent version, you could try the development branch with `git checkout develop`
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64-
This should also work:
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### CPU
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To compile the code for CPU, you can use the `--disable-cuda` option for `./configure`:
78+
```
79+
./configure --disable-cuda
80+
```
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### Parallel run
82+
To run TCLB in parallel (both on multiple CPU and multiple GPU), you can use the standard syntax of MPI parallel run:
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```bash
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CLB/d2q9/main example/flow/2d/karman.xml
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mpirun -np 8 CLB/d2q9/main example/flow/2d/karman.xml
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```
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## Documentation
87+
### Running on clusters
88+
To assist with using TCLB on HPC clusters (SLURM/PBS), there are scripts provided in the [TCLB_cluster](https://github.com/CFD-GO/TCLB_cluster) repository.
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The documentation (including tutorials) is published at
72-
[docs.tclb.io](https://docs.tclb.io/). You can contribute at
73-
[CFD-GO/TCLB_docs](https://github.com/CFD-GO/TCLB_docs).
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### LBM-DEM computation
91+
TCLB code can be coupled with Discrete Element Method (DEM) codes, to enable computation of flow with particles.
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75-
For the `develop` version, most recent documentation can be found at
76-
[develop.docs.tclb.io](https://develop.docs.tclb.io/).
93+
The DEM codes that TCLB can be integrated with are:
94+
- [LIGGGHTS](https://www.cfdem.com/liggghts-open-source-discrete-element-method-particle-simulation-code)
95+
- [LAMMPS](https://lammps.sandia.gov/)
96+
- [ESYS-Particle](https://launchpad.net/esys-particle)
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98+
Refer to the documentation for instructions on compilation and coupling.
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## About
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102+
### Authors
77103

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## Authors
104+
TCLB began development in 2012 with the aim at providing a framework for efficient CFD computations with LBM, mainly for research.
79105

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Author: [Łukasz Łaniewski-Wołłk](https://github.com/llaniewski)
81107

@@ -91,9 +117,11 @@ Contributors:
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* [Paweł Obrępalski](https://github.com/PabloOb)
92118
* [Grzegorz Gruszczyński](https://github.com/ggruszczynski)
93119

94-
Developed at: [C-CFD Group](https://c-cfd.meil.pw.edu.pl/) at [Warsaw University of Technology](http://pw.edu.pl/) from 2012
120+
Developed at:
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- [Zakład Aerodynamiki](https://meil.pw.edu.pl/ZA/) at [Politechnika Warszawska (Warsaw University of Technology)](http://pw.edu.pl/)
122+
- [School of Mechanical & Mining Engineering](https://www.mechmining.uq.edu.au/) at [University of Queensland](http://uq.edu.au/)
95123

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## License
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### License
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This software is distributed under the [GPL v3 License](LICENSE).
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‎example/article/ThermocapillaryFlow/BubbleInteraction_catalyst.py

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#--------------------------------------------------------------
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# Global timestep output options
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timeStepToStartOutputAt=0
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forceOutputAtFirstCall=False
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# Global screenshot output options
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imageFileNamePadding=0
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rescale_lookuptable=False
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# Whether or not to request specific arrays from the adaptor.
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requestSpecificArrays=False
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# a root directory under which all Catalyst output goes
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rootDirectory=''
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# makes a cinema D index table
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make_cinema_table=False
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#--------------------------------------------------------------
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# Code generated from cpstate.py to create the CoProcessor.
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# paraview version 5.8.0
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#--------------------------------------------------------------
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from paraview.simple import *
27+
from paraview import coprocessing
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# ----------------------- CoProcessor definition -----------------------
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def CreateCoProcessor():
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def _CreatePipeline(coprocessor, datadescription):
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class Pipeline:
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# state file generated using paraview version 5.8.0
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# ----------------------------------------------------------------
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# setup the data processing pipelines
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# ----------------------------------------------------------------
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# trace generated using paraview version 5.8.0
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#
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# To ensure correct image size when batch processing, please search
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# for and uncomment the line `# renderView*.ViewSize = [*,*]`
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#### disable automatic camera reset on 'Show'
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paraview.simple._DisableFirstRenderCameraReset()
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# create a new 'XML Partitioned Image Data Reader'
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# create a producer from a simulation input
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recalcitrantBubble_interaction_smooth_main_VTK_P00_00000530pvti = coprocessor.CreateProducer(datadescription, 'input')
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# create a new 'Cell Data to Point Data'
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cellDatatoPointData1 = CellDatatoPointData(Input=recalcitrantBubble_interaction_smooth_main_VTK_P00_00000530pvti)
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cellDatatoPointData1.CellDataArraytoprocess = ['PhaseField', 'T', 'U']
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# create a new 'Iso Volume'
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isoVolume1 = IsoVolume(Input=cellDatatoPointData1)
58+
isoVolume1.InputScalars = ['POINTS', 'PhaseField']
59+
isoVolume1.ThresholdRange = [0.0, 0.5]
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# create a new 'Connectivity'
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connectivity1 = Connectivity(Input=isoVolume1)
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# ----------------------------------------------------------------
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# finally, restore active source
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SetActiveSource(connectivity1)
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# ----------------------------------------------------------------
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# Now any catalyst writers
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cSVWriter1 = servermanager.writers.CSVWriter(Input=connectivity1)
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coprocessor.RegisterWriter(cSVWriter1, filename='Connectivity1_%t.csv', freq=1, paddingamount=0, DataMode='None', HeaderType='None', EncodeAppendedData=None, CompressorType='None', CompressionLevel='None')
72+
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return Pipeline()
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class CoProcessor(coprocessing.CoProcessor):
76+
def CreatePipeline(self, datadescription):
77+
self.Pipeline = _CreatePipeline(self, datadescription)
78+
79+
coprocessor = CoProcessor()
80+
# these are the frequencies at which the coprocessor updates.
81+
freqs = {'input': [1]}
82+
coprocessor.SetUpdateFrequencies(freqs)
83+
if requestSpecificArrays:
84+
arrays = [['PhaseField', 1], ['T', 1], ['U', 1]]
85+
coprocessor.SetRequestedArrays('input', arrays)
86+
coprocessor.SetInitialOutputOptions(timeStepToStartOutputAt,forceOutputAtFirstCall)
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if rootDirectory:
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coprocessor.SetRootDirectory(rootDirectory)
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if make_cinema_table:
92+
coprocessor.EnableCinemaDTable()
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94+
return coprocessor
95+
96+
97+
#--------------------------------------------------------------
98+
# Global variable that will hold the pipeline for each timestep
99+
# Creating the CoProcessor object, doesn't actually create the ParaView pipeline.
100+
# It will be automatically setup when coprocessor.UpdateProducers() is called the
101+
# first time.
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coprocessor = CreateCoProcessor()
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104+
#--------------------------------------------------------------
105+
# Enable Live-Visualizaton with ParaView and the update frequency
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coprocessor.EnableLiveVisualization(False, 1)
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108+
# ---------------------- Data Selection method ----------------------
109+
110+
def RequestDataDescription(datadescription):
111+
"Callback to populate the request for current timestep"
112+
global coprocessor
113+
114+
# setup requests for all inputs based on the requirements of the
115+
# pipeline.
116+
coprocessor.LoadRequestedData(datadescription)
117+
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# ------------------------ Processing method ------------------------
119+
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def DoCoProcessing(datadescription):
121+
"Callback to do co-processing for current timestep"
122+
global coprocessor
123+
124+
# Update the coprocessor by providing it the newly generated simulation data.
125+
# If the pipeline hasn't been setup yet, this will setup the pipeline.
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coprocessor.UpdateProducers(datadescription)
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# Write output data, if appropriate.
129+
coprocessor.WriteData(datadescription);
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# Write image capture (Last arg: rescale lookup table), if appropriate.
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coprocessor.WriteImages(datadescription, rescale_lookuptable=rescale_lookuptable,
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image_quality=0, padding_amount=imageFileNamePadding)
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# Live Visualization, if enabled.
136+
coprocessor.DoLiveVisualization(datadescription, "localhost", 22222)

‎example/multiphase/d3q27_pf_velocity/BubbleMa001.xml renamed to ‎example/article/ThermocapillaryFlow/BubbleMa001.xml

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<?xml version="1.0"?>
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<CLBConfig version="2.0" output="/scratch/eait/uqtmitc3/thermocapillary/" permissive="true">
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<!-- MODEL: d3q27_pf_thermocapillary
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First test of temp field
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<CLBConfig version="2.0" output="output/" permissive="true">
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<!--
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MODEL: d3q27_pf_velocity_thermo
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Purpose: test bubble migration for paper,
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T. Mitchell et al. Computational modelling of
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three-dimensional thermocapillary flow of
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recalcitrant bubbles using a coupled lattice
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Boltzmann-finite difference method, PRE
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Created: 17/04/2020
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Responsible: @TravisMitchell
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-->
@@ -23,22 +31,22 @@
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<Param name="CenterZ" value="80"/>
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<Param name="BubbleType" value="-1"/>
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<Param name="Density_h" value="1"/>
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<Param name="Density_l" value="1"/>
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<Param name="Density_l" value="1"/>
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<Param name="Viscosity_h" value="0.1"/>
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<Param name="Viscosity_l" value="0.1"/>
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<Param name="sigma" value="5e-3"/>
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<Param name="M" value="0.05"/>
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<Param name="IntWidth" value="4"/>
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<Param name="T_init" value="16"/>
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<Param name="T_ref" value="16"/>
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<Param name="dT" value="0.1"/>
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<Param name="sigma_T" value="-2.5e-4"/>
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<Param name="T_init" value="0" zone="BottomWall"/>
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<Param name="T_init" value="32" zone="TopWall"/>
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<Param name="cp_h" value="1"/>
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<Param name="cp_l" value="1"/>
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<Param name="k_h" value="0.1"/>
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<Param name="k_l" value="0.1"/>
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<Param name="T_init" value="16"/>
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<Param name="T_ref" value="16"/>
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<Param name="dT" value="0.1"/>
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<Param name="sigma_T" value="-2.5e-4"/>
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<Param name="T_init" value="0" zone="BottomWall"/>
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<Param name="T_init" value="32" zone="TopWall"/>
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<Param name="cp_h" value="1"/>
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<Param name="cp_l" value="1"/>
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<Param name="k_h" value="0.1"/>
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<Param name="k_l" value="0.1"/>
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</Model>
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<Init/>
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<Container>

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