parametric-plasma-source

Python package, C++ source and build files for parametric plasma source for use in fusion neutron transport calculations with OpenMC.

The plasma source is based on a paper by C. Fausser et al

Installation

Installing from PyPI

pip install parametric_plasma_source

Installing from source

Installation of the parametric plasma source from source requires cmake to build the underlying C++ code. This can be obtained from your OS's package manager by e.g. sudo apt-get install cmake or from cmake source.

If you intend to develop the code then it is recommended to work in a virtual environment.

The requirements for developing the code can be installed by running:

pip install -r requirements-develop.txt

The package can be built and installed in editable mode by:

pip install -e .

Usage

The parametric plasma source can be sampled either directly in Python 3, sampled in an OpenMC simulation, or sampled using OpenMC via a standalone executable without simulation.

For a better understanding of the varibles take a look at the C. Fausser et al paper.

Sampling in Python

The parametric plasma source can be imported an used in Python 3 in the following manner:

from parametric_plasma_source import PlasmaSource
from random import random

plasma_params = {
    "elongation": 1.557,
    "ion_density_origin": 1.09e20,
    "ion_density_peaking_factor": 1,
    "ion_density_pedestal": 1.09e20,
    "ion_density_separatrix": 3e19,
    "ion_temperature_origin": 45.9,
    "ion_temperature_peaking_factor": 8.06,
    "ion_temperature_pedestal": 6.09,
    "ion_temperature_separatrix": 0.1,
    "major_radius": 9.06,
    "minor_radius": 2.92258,
    "pedestal_radius": 0.8 * 2.92258,
    "plasma_id": 1,
    "shafranov_shift": 0.44789,
    "triangularity": 0.270,
    "ion_temperature_beta": 6,
}

my_plasma = PlasmaSource(**plasma_params)
sample = my_plasma.sample([random(), random(), random(), random(), random(), random(), random(), random()])
particle_x, particle_y, particle_z = sample[0], sample[1], sample[2]
particle_x_dir, particle_y_dir, particle_z_dir = sample[3], sample[4], sample[5]
particle_energy_mev = sample[6]

Sampling in OpenMC

The parametric plasma source also contains a plugin library for OpenMC to allow the source to be sampled in an OpenMC simulation.

When using the OpenMC sampling the inputs must be provided in meters where applicable (the sampling will convert to cm).

from parametric_plasma_source import PlasmaSource, SOURCE_SAMPLING_PATH
import openmc

plasma_params = {
    "elongation": 1.557,
    "ion_density_origin": 1.09e20,
    "ion_density_peaking_factor": 1,
    "ion_density_pedestal": 1.09e20,
    "ion_density_separatrix": 3e19,
    "ion_temperature_origin": 45.9,
    "ion_temperature_peaking_factor": 8.06,
    "ion_temperature_pedestal": 6.09,
    "ion_temperature_separatrix": 0.1,
    "major_radius": 9.06,
    "minor_radius": 2.92258,
    "pedestal_radius": 0.8 * 2.92258,
    "plasma_id": 1,
    "shafranov_shift": 0.44789,
    "triangularity": 0.270,
    "ion_temperature_beta": 6,
}

my_plasma = PlasmaSource(**plasma_params)
settings = openmc.Settings()
settings.run_mode = "fixed source"
settings.batches = 10
settings.particles = 1000
source = openmc.Source()
source.library = SOURCE_SAMPLING_PATH
source.parameters = str(my_plasma)
settings.source = source
settings.export_to_xml()

Sampling using Executable

It is also possible to generate a source outside of OpenMC by creating the source_generator executable by running cmake -H. -Bbuild and then cmake --build build or cmake --build build --target source_generator. The source_generator can then be run as below:

Usage:
source_generator [OPTIONS]

Options:
 -l,--library      Source library, mandatory
 -n,--particles    Number of particles, default 1000
 -o,--output       Output directory, default {current directory}
 -v,--verbosity    Verbosity, default 5

This will use OpenMC commands to sample the source generated using the specified library with the specified number of particles and output the resulting initial_source.h5 file in the requested output directory. The initial_source.h5 can then be analysed to check the properties of the source being generated.

Running Tests

The tests are run by executing pytest tests from within your virtual environment.