mattflow 1.4.2

A CFD python package for the Shallow Water Equations

MattFlow

A CFD python package for the Shallow Water Equations

MattFlow simulates the surface of the water after any initial conditions, such as drops or stones falling on.

---

requirements	os
python3	GNU/Linux
click >= 7.0	Windows
joblib >= 0.13.2	OSX
matplotlib >= 3.3.1
numba >= 0.51.2
numpy >= 1.18.5
ffmpeg (optional)

Install

$ conda create --name mattflow -y
$ conda activate mattflow
$ conda install -c mattasa mattflow

$ pip install mattflow

Usage

$ mattflow [OPTIONS]

Options:
  -m, --mode [drop|drops|rain]    [default: drops]
  -d, --drops INTEGER             number of drops to generate  [default: 5]
  -s, --style [water|contour|wireframe]
                                  [default: wireframe]
  --rotation / --no-rotation      rotate the domain  [default: True]
  -b, --basin                     render the fluid basin
  --show / --no-show              [default: True]
  --save
  --format [mp4|gif]              [default: mp4]
  --fps INTEGER                   [default: 18]
  --dpi INTEGER                   [default: 75]
  --fig-height INTEGER            figure height (width is 1.618 * height)
                                  [default: 18]
  --help                          Show this message and exit.

Swallow Water Equations

SWE is a simpified CFD problem which models the surface of the water, with the assumption
that the horizontal length scale is much greater than the vertical length scale.

SWE is a coupled system of 3 hyperbolic partial differential equations, that derive from the
conservation of mass and the conservation of linear momentum (Navier-Stokes) equations, in
case of a horizontal stream bed, with no Coriolis, frictional or viscours forces (wiki).

where:
η : height
u : velocity along the x axis
υ : velocity along the y axis
ρ : density
g : gravity acceleration

Structure

0. configuration of the simulation via a config file
1. pre-process
   structured/cartesian mesh
2. solution
   supported solvers:
   • Lax-Friedrichs Riemann    | O(Δt, Δx², Δy²)
   • 2-stage Runge-Kutta         | O(Δt², Δx², Δy²)  | default
   • MacCormack           | O(Δt², Δx², Δy²)  | experimental
3. post-processing
   matplotlib animation

Configuration options

• mesh sizing
• domain sizing
• initial conditions (single drop, multiple drops, rain)
• boundary conditions (currently: reflective)
• solver
• multiprocessing
• plotting style
• animation options

Currently, the simulation can be configured at the config.py module.

TODO

1. CI
2. GUI
3. Consider Cythonizing or moving to C++
4. Higher order schemes
5. Include source terms
6. Include viscous models
7. Algorithm that converts every computational second to a real-time second, modifying the fps at
   the post-processing animation, because each iteration uses different time-step (CFL condition).
8. Moving objects inside the domain
9. Unstructured mesh
10. 3D CFD

License

GNU General Public License v3.0

Special thanks to Marios Mitalidis for the valuable feedback.

Start the flow!

(C) 2019, Athanasios Mattas
[e-mail]