https://github.com/stefanmeili/fastfd

A library for building finite difference simulations
https://github.com/stefanmeili/fastfd

cupy electromagnetic-simulation engineering-design engineering-tools finite-difference finite-difference-simulations fluid-dynamics heat-transfer mechanical-engineering partial-differential-equations pde pde-solver physics-simulation process-simulation python scipy simulation

Last synced: 3 months ago
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A library for building finite difference simulations

• Host: GitHub
• URL: https://github.com/stefanmeili/fastfd
• Owner: stefanmeili
• License: mit
• Created: 2021-03-07T23:32:30.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2021-04-22T21:43:51.000Z (almost 4 years ago)
• Last Synced: 2024-10-31T08:42:09.561Z (3 months ago)
• Topics: cupy, electromagnetic-simulation, engineering-design, engineering-tools, finite-difference, finite-difference-simulations, fluid-dynamics, heat-transfer, mechanical-engineering, partial-differential-equations, pde, pde-solver, physics-simulation, process-simulation, python, scipy, simulation
• Language: Python
• Homepage:
• Size: 60.2 MB
• Stars: 31
• Watchers: 3
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# FastFD

A finite differences simulation library.

This package lets you quickly build simple numerical simulations.

## Features

 * Quickly build finite difference simulations with an arbitrary number of domains, scalars, dimensions and boundary conditions.

 * Concise, clear syntax.

 * Build models for CPU or GPU using Scipy or Cupy sparse libraries.

 * Arbitrary derivative order and approximation accuracy.

 * Partial model updates minimize overheads in iterative solutions.

 * Implicit transient simulation.

## Installation

```

pip install fastfd

```

## Usage

```python

# Import fastfd and select the scipy sparse library (or cupy for GPU support)

import fastfd as ffd

ffd.sparse_lib('scipy')

import numpy as np

# Define axes

x = ffd.LinearAxis('x', start = 0, stop = 1, num = 201)

y = ffd.LinearAxis('y', start = 0, stop = 1, num = 201)

# Define scalars

T = ffd.Scalar('T', [x, y], accuracy = 4)

# Define the model

model = ffd.FDModel([T])

# Set model governing equations (thermal diffusion)

model.update_equations({

    'Conductivity': ((T.d('x', 2) + T.d('y', 2)), 0),

})

# Set model boundary conditions

model.update_bocos({

    'Tx=1 adiabatic': (T.i[-1, :], T.d('x')[-1, :], 0),

    'Ty=1 adiabatic': (T.i[:, -1], T.d('y')[:, -1], 0),

    'Tx=0 sinewave': (T.i[0, :], T.i[0, :], 100 * np.sin(x.coords * 2*np.pi)),

    'Ty=0 sinewave': (T.i[:, 0], T.i[:, 0], -100 * np.sin(y.coords * 2*np.pi)),

})

# Solve the model

result = model.solve()

```



    



## GPU

FastFD can be set to use the Cupyx sparse libraries, though support is still a little rough around the edges. The current

version of Cupy (8.5) only supports a least squares solver ('lsqr') which is much slower than the default 'spsolve'.

However, spsolve will be implemented in the upcoming release of Cupy 9.0.

## Example Notebooks

See example notebooks here:  ./docs/examples  for a more detailed explanation of how to use.