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Merge branch 'master' into source_sampling_executable
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‎.flake8‎

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[flake8]
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max-line-length = 88
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exclude = __init__.py

‎.github/workflows/python.yml‎

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name: Python package
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on:
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push:
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branches: [ master ]
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pull_request:
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branches: [ master ]
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jobs:
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build_and_test:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: [3.6, 3.7, 3.8]
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install OpenMC
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run: |
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sudo apt-get install -y g++ cmake libhdf5-dev
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git clone --recurse-submodules https://github.com/openmc-dev/openmc.git
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cd openmc
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git checkout
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mkdir build && cd build
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cmake ..
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make
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sudo make install
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- name: Install plasma source
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run: |
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pip install -r requirements-develop.txt
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python setup.py bdist_wheel
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python -m pip install --verbose dist/*.whl
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- name: Run tests
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run: |
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pytest tests
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- name: Upload wheel artifact
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uses: actions/upload-artifact@v2
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with:
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name: dist
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path: dist

‎.gitignore‎

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# Python
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__pycache__/
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*.py[cod]
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.venv
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source_generator
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# Output files
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# Outputs
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*.xml
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*.h5
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# VS Code
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.vscode

‎CMakeLists.txt‎

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add_library(source_sampling SHARED ${source_sampling_SOURCES})
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find_library(OPENMC_LIB openmc HINTS ${OPENMC_LIB_DIR})
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set_target_properties(source_sampling PROPERTIES PREFIX "")
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set_target_properties(source_sampling PROPERTIES POSITION_INDEPENDENT_CODE ON)
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target_include_directories(source_sampling PUBLIC ${OPENMC_INC_DIR})
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target_include_directories(source_sampling PUBLIC ${OPENMC_DIR}/vendor/pugixml)
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target_link_libraries(source_sampling ${OPENMC_LIB} gfortran)
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find_library(OPENMC_LIB openmc HINTS ${OPENMC_LIB_DIR} OPTIONAL)
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if (OPENMC_LIB)
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set_target_properties(source_sampling PROPERTIES PREFIX "")
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set_target_properties(source_sampling PROPERTIES POSITION_INDEPENDENT_CODE ON)
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target_include_directories(source_sampling PUBLIC ${OPENMC_INC_DIR})
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target_include_directories(source_sampling PUBLIC ${OPENMC_DIR}/vendor/pugixml)
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target_link_libraries(source_sampling ${OPENMC_LIB} gfortran)
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endif()
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# Build plasma_source Python bindings
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list(APPEND plasma_source_pybind_SOURCES

‎README.md‎

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# parametric-plasma-source
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![Python package](https://github.com/DanShort12/parametric-plasma-source/workflows/Python%20package/badge.svg)
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Python package, C++ source and build files for parametric plasma source for use in fusion neutron transport calculations with OpenMC.
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The plasma source is based on a paper by [C. Fausser et al](https://www.sciencedirect.com/science/article/pii/S0920379612000853)
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# Installation
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## Installation
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### Installing from PyPI
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```pip install parametric_plasma_source```
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# Usage
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### Installing from source
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The parametric plasma source can be imported an used in Python 3 in the following manner.
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Installation of the parametric plasma source from source requires cmake to build the underlying C++ code. This can be obtained from
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your OS's package manager by e.g. `sudo apt-get install cmake` or from cmake source.
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```
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from parametric_plasma_source import Plasma
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my_plasma = Plasma(major_radius=6,
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minor_radius=1.5,
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elongation = 2.0,
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triangularity = 0.55)
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my_plasma.export_plasma_source('custom_openmc_plasma_source.so')
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```
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If you intend to develop the code then it is recommended to work in a virtual environment.
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In the above example the major_radius, minor_radius, elongation and triangularity while the other varibles are kept as the default values.
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The requirements for developing the code can be installed by running:
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There are a number of additional arguments that can be passed to the Plasma class on construction. Units are in SI (e.g. meters not cm)
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```pip install -r requirements-develop.txt```
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```
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ion_density_pedistal = 1.09e+20
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ion_density_seperatrix = 3e+19
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ion_density_origin = 1.09e+20
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ion_temperature_pedistal = 6.09
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ion_temperature_seperatrix = 0.1
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ion_temperature_origin = 45.9
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pedistal_radius = 0.8
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ion_density_peaking_factor = 1
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ion_temperature_peaking_factor = 8.06
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minor_radius = 1.56
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major_radius = 2.5
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elongation = 2.0
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triangularity = 0.55
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shafranov_shift = 0.0
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number_of_bins = 100
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plasma_type = 1
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```
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The package can be built and installed in editable mode by:
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```pip install -e .```
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## Usage
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The parametric plasma source can be sampled either directly in Python 3 or sampled in an OpenMC simulation.
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For a better understanding of the varibles take a look at the [C. Fausser et al](https://www.sciencedirect.com/science/article/pii/S0920379612000853) paper.
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## Building and Running
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### Sampling in Python
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The parametric plasma source can be imported an used in Python 3 in the following manner:
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```[python]
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from parametric_plasma_source import PlasmaSource
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from random import random
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plasma_params = {
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"elongation": 1.557,
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"ion_density_origin": 1.09e20,
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"ion_density_peaking_factor": 1,
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"ion_density_pedestal": 1.09e20,
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"ion_density_separatrix": 3e19,
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"ion_temperature_origin": 45.9,
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"ion_temperature_peaking_factor": 8.06,
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"ion_temperature_pedestal": 6.09,
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"ion_temperature_separatrix": 0.1,
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"major_radius": 9.06,
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"minor_radius": 2.92258,
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"pedestal_radius": 0.8 * 2.92258,
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"plasma_id": 1,
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"shafranov_shift": 0.44789,
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"triangularity": 0.270,
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"ion_temperature_beta": 6,
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}
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my_plasma = PlasmaSource(**plasma_params)
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sample = my_plasma.sample([random(), random(), random(), random(), random(), random(), random(), random()])
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particle_x, particle_y, particle_z = sample[0], sample[1], sample[2]
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particle_x_dir, particle_y_dir, particle_z_dir = sample[3], sample[4], sample[5]
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particle_energy_mev = sample[6]
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```
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Note: When building using the `Makefile` you may need to update the `OPENMC_DIR` parameter to select a relevant directory to obtain the OpenMC libraries and includes from.
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### Sampling in OpenMC
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The parametric plasma source also contains a plugin library for OpenMC to allow the source to be sampled in an OpenMC simulation.
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When using the OpenMC sampling the inputs must be provided in meters where applicable (the sampling will convert to cm).
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```[python]
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from parametric_plasma_source import PlasmaSource, SOURCE_SAMPLING_PATH
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import openmc
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plasma_params = {
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"elongation": 1.557,
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"ion_density_origin": 1.09e20,
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"ion_density_peaking_factor": 1,
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"ion_density_pedestal": 1.09e20,
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"ion_density_separatrix": 3e19,
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"ion_temperature_origin": 45.9,
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"ion_temperature_peaking_factor": 8.06,
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"ion_temperature_pedestal": 6.09,
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"ion_temperature_separatrix": 0.1,
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"major_radius": 9.06,
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"minor_radius": 2.92258,
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"pedestal_radius": 0.8 * 2.92258,
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"plasma_id": 1,
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"shafranov_shift": 0.44789,
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"triangularity": 0.270,
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"ion_temperature_beta": 6,
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}
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my_plasma = PlasmaSource(**plasma_params)
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settings = openmc.Settings()
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settings.run_mode = "fixed source"
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settings.batches = 10
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settings.particles = 1000
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source = openmc.Source()
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source.library = SOURCE_SAMPLING_PATH
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source.parameters = str(my_plasma)
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settings.source = source
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settings.export_to_xml()
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```
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The OpenMC plugin that samples the plasma source is built by running `make` or `make source_sampling` from within the parametric-plasma-source directory. This will generate the `source_sampling.so` shared object library, which can be referenced by the `library` attribute in the `source` element within the settings.xml being used for the run.
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### Sampling using Executable
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It is also possible to generate a source outside of OpenMC by creating the `source_generator` executable by running `make` or `make source_generator` from within the parameteric-plasma-source directory. The `source_generator` can then be run as below:
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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:
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```bash
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Usage:
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```
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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.
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## Running Tests
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The tests are run by executing `pytest tests` from within your virtual environment.

‎data/example_source.txt‎

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major_radius=4.5, minor_radius=1.5, elongation=2, triangularity=0.55, shafranov_shift=0, pedestal_radius=1.2, ion_density_pedestal=1.09e+20, ion_density_separatrix=3e+19, ion_density_origin=1.09e+20, ion_density_alpha=1, ion_temperature_pedestal=6.09, ion_temperature_separatrix=0.1, ion_temperature_origin=45.9, ion_temperature_alpha=8.06, ion_temperature_beta=6, plasma_type=plasma, plasma_id=1, number_of_bins=100, minimum_toroidal_angle=0, maximum_toroidal_angle=360

‎examples/build_and_run_model.py‎

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"""
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OpenMC Plasma Source example.
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An example of how to generate a settings file containing the parameterised
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plasma source sampling library and how to generate the parameterisation in the
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OpenMC settings.xml file.
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"""
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from parametric_plasma_source import PlasmaSource, SOURCE_SAMPLING_PATH
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import openmc
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plasma_params = {
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"elongation": 1.557,
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"ion_density_origin": 1.09e20,
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"ion_density_peaking_factor": 1,
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"ion_density_pedestal": 1.09e20,
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"ion_density_separatrix": 3e19,
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"ion_temperature_origin": 45.9,
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"ion_temperature_peaking_factor": 8.06,
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"ion_temperature_pedestal": 6.09,
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"ion_temperature_separatrix": 0.1,
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"major_radius": 9.06,
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"minor_radius": 2.92258,
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"pedestal_radius": 0.8 * 2.92258,
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"plasma_id": 1,
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"shafranov_shift": 0.44789,
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"triangularity": 0.270,
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"ion_temperature_beta": 6,
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}
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plasma = PlasmaSource(**plasma_params)
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# Create a single material
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iron = openmc.Material()
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iron.set_density("g/cm3", 5.0)
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iron.add_element("Fe", 1.0)
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mats = openmc.Materials([iron])
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# Create a 5 cm x 5 cm box filled with iron
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cells = []
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inner_box1 = openmc.ZCylinder(r=600.0)
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inner_box2 = openmc.ZCylinder(r=1400.0)
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outer_box = openmc.model.rectangular_prism(4000.0, 4000.0, boundary_type="vacuum")
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cells += [openmc.Cell(fill=iron, region=-inner_box1)]
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cells += [openmc.Cell(fill=None, region=+inner_box1 & -inner_box2)]
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cells += [openmc.Cell(fill=iron, region=+inner_box2 & outer_box)]
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geometry = openmc.Geometry(cells)
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# Tell OpenMC we're going to use our custom source
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settings = openmc.Settings()
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settings.run_mode = "fixed source"
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settings.batches = 10
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settings.particles = 1000
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source = openmc.Source()
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source.library = SOURCE_SAMPLING_PATH
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source.parameters = str(plasma)
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settings.source = source
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# Finally, define a mesh tally so that we can see the resulting flux
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mesh = openmc.RegularMesh()
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mesh.lower_left = (-2000.0, -2000.0)
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mesh.upper_right = (2000.0, 2000.0)
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mesh.dimension = (50, 50)
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tally = openmc.Tally()
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tally.filters = [openmc.MeshFilter(mesh)]
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tally.scores = ["flux"]
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tallies = openmc.Tallies([tally])
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model = openmc.model.Model(
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materials=mats, geometry=geometry, settings=settings, tallies=tallies
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)
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model.run()

‎examples/plot_flux.py‎

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import matplotlib as mpl
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import matplotlib.pyplot as plt
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import numpy as np
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import openmc
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mpl.use("TkAgg")
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# Get the flux from the statepoint
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with openmc.StatePoint("statepoint.10.h5") as sp:
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flux = np.log(sp.get_tally(scores=["flux"]).mean)
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flux.shape = (50, 50)
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# Plot the flux
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fig, ax = plt.subplots()
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ax.imshow(flux, origin="lower", extent=(-2000.0, 2000.0, -2000.0, 2000.0))
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ax.set_xlabel("x [cm]")
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ax.set_ylabel("y [cm]")
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plt.show()

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