Big Fluid and Particle Simulator

In brief, this code runs pseudospectral direct numerical simulations (DNS) of the incompressible Navier-Stokes equations, using FFTW 3, and it can integrate particle trajectories in the resulting fields.

The Navier-Stokes solver has been extensively tested (tests are included in the repository), and it is working as expected. Parameters and statistics are stored in HDF5 format, together with code information, so simulation data should be "future proof" --- suggestions of possible improvements to the current approach are always welcome.

The primary aim of bfps is to reduce the time spent on setting up and baby sitting DNS, as well as simplify the analysis of the generated data. The wish is that this Python package provides an easy and general way of constructing efficient specialized DNS C++ codes for different turbulence problems encountered in research. At the same time, the package should provide a unified way of postprocessing, and accessing the postprocessing results. The code therefore consists of two main parts: the pure C++ code, a set of loosely related "building blocks", and the Python code, which can generate C++ code using the pure classes, but with a significant degree of flexibility.

The code user is expected to write a small python script that will properly define the DNS they are interested in running. That code will generate an executable that can then be run directly on the user's machine, or submitted to a queue on a cluster.

Installation

So far, the code has been run on laptops, desktops, and a couple of clusters (biggest run so far was 1536^3 on 16 nodes of 32 cores each, with about 11 seconds per time step, for a simple incompressible Navier-Stokes problem). Postprocessing data may not be very computationally intensive, depending on the amount of data involved.

Postprocessing only

Use a console; navigate to the bfps folder, and type:

python setup.py install

(add --user or sudo as appropriate). setup.py should tell you about the various packages you need.

Full installation

If you want to run simulations on the machine where you're installing, you will need to call compile_library before installing. Your machine needs to have an MPI compiler installed, the HDF5 C library and FFTW >= 3.4. The file machine_settings_py.py should be modified appropriately for your machine (otherwise the compile_library command will most likely fail). This file will be copied the first time you run setup.py into $HOME/.config/bfps/machine_settings.py, where it will be imported from afterwards --- any future edits must be made to the new file. You may, obviously, edit it afterwards and rerun the compile_library command as needed.

python setup.py compile_library
python setup.py install

Documentation

While the code is not fully documented yet, basic information is already available, and it is recommended that you generate the manual and go through it carefully. Please don't be shy about asking for specific improvements to the current text. In order to generate the manual, navigate to the repository folder, and execute the following commands:

cd documentation
make latexpdf

Optionally, html documentation can be generated instead if needed, just type make html instead of make latexpdf.

Comments

• particles: initialization of multistep solvers is done with lower order methods, so direct convergence tests will fail.
• Code is used mainly with Python 3.4 and 3.5. In principle it should be easy to maintain compatibility with Python 2.7.x, but as of bfps 1.8 this is no longer a main concern.