Basic Operation¶

SERPENT produces a burned material file, containing the evolution of material properties through burnup for all burned materials present in the problem. The DepletionReader is capable of reading this file, and storing the data inside DepletedMaterial objects. Each such object has methods and attributes that should ease analysis.

>>> import serpentTools
>>> from serpentTools.settings import rc


Note

The preferred way to read your own output files is with the read() function. The readDataFile() function is used here to make it easier to reproduce the examples

>>> depFile = 'demo_dep.m'


The materials read in from the file are stored in the materials dictionary, where the keys represent the name of specific materials, and the corresponding values are the depleted material.

>>> dep.materials
{'fuel0': <serpentTools.objects.materials.DepletedMaterial at 0x7f8f8dccde80>,
'bglass0': <serpentTools.objects.materials.DepletedMaterial at 0x7f8f8f42f518>,
'total': <serpentTools.objects.materials.DepletedMaterial at 0x7f8f8dce7940>}


Metadata, such as the isotopic vector and depletion schedule are also present on the reader

>>> dep.names
['Xe135', 'I135', 'U234', 'U235', 'U236', 'U238', 'Pu238',
'Pu239', 'Pu240', 'Pu241', 'Pu242', 'Np237', 'Am241', 'Am243',
'Cm243', 'Cm244', 'Cm245', 'Cs133', 'Nd143', 'Sm147', 'Sm149',
'Sm150', 'Sm151', 'Sm152', 'Eu153', 'Gd155', 'Mo95', 'Tc99',
'Ru101', 'Rh103', 'Ag109', 'Cd113', 'lost', 'total']
>>> dep.burnup
array([0.  , 0.02, 0.04, 0.06, 0.08, 0.1 , 0.12, 0.14, 0.16, 0.18, 0.2 ,
0.22, 0.24, 0.26, 0.28, 0.3 , 0.32, 0.34, 0.36, 0.38, 0.4 , 0.42,
0.44, 0.46, 0.48, 0.5 , 0.52, 0.54, 0.56, 0.58, 0.6 , 0.62, 0.64,
0.66, 0.68, 0.7 , 0.72, 0.74, 0.76, 0.78, 0.8 , 0.82, 0.84, 0.86,
0.88, 0.9 , 0.92, 0.94, 0.96, 0.98, 1.  , 1.02, 1.04, 1.06, 1.08,
1.1 , 1.12, 1.14, 1.16, 1.18, 1.2 , 1.22, 1.24, 1.26, 1.28, 1.3 ,
1.32, 1.34, 1.36, 1.38, 1.4 , 1.42])
>>> dep.zais
[541350, 531350, 922340, 922350, 922360, 922380, 942380,
942390, 942400, 942410, 942420, 932370, 952410, 952430,
962430, 962440, 962450, 551330, 601430, 621470, 621490,
621500, 621510, 621520, 631530, 641550, 420950, 430990,
441010, 451030, 471090, 481130, 666, 0]


Depleted Material Objects¶

As mentioned before, all the material data is stored inside these DepletedMaterial objects. These objects share access to the metadata of the reader as well.

>>> fuel = dep.materials['fuel0']
>>> fuel.burnup
array([0.         0.00702676 0.0144405  0.0218803  0.0297245  0.0370823
0.0447201  0.0513465  0.0590267  0.0671439  0.073392   0.0802637
0.0887954  0.0974604  0.104807   0.111528   0.119688   0.128006
0.135704   0.143491   0.150545   0.157608   0.165391   0.172872
0.180039   0.188011   0.195215   0.202291   0.20963    0.216895
0.224651   0.232139   0.23904    0.246076   0.25422    0.262011
0.269681   0.276981   0.284588   0.291835   0.299661   0.30727
0.314781   0.322364   0.329404   0.336926   0.34438    0.352246
0.360913   0.367336   0.37415    0.381556   0.388951   0.396286
0.404159   0.412113   0.419194   0.426587   0.43425    0.442316
0.449562   0.456538   0.465128   0.472592   0.479882   0.487348
0.494634   0.502167   0.508326   0.515086   0.522826   0.530643])
>>> fuel.days is dep.days
True


Materials can also be obtained by indexing directly into the reader, with

>>> dep["fuel0"] is dep.materials["fuel0"] is dep.get("fuel0")
True


All of the variables present in the depletion file for this material are present, stored in the data dictionary. A few properties commonly used are accessible as attributes as well.

>>> fuel.data.keys()
dict_keys(['volume', 'burnup', 'adens', 'mdens', 'a', 'h', 'sf', 'gsrc', 'ingTox', 'inhTox'])
[[0.00000e+00 2.43591e-09 4.03796e-09 ... 4.70133e-09 4.70023e-09
4.88855e-09]
[0.00000e+00 6.06880e-09 8.11783e-09 ... 8.05991e-09 8.96359e-09
9.28554e-09]
[4.48538e-06 4.48486e-06 4.48432e-06 ... 4.44726e-06 4.44668e-06
4.44611e-06]
...
[0.00000e+00 3.03589e-11 7.38022e-11 ... 1.62829e-09 1.63566e-09
1.64477e-09]
[0.00000e+00 1.15541e-14 2.38378e-14 ... 8.60736e-13 8.73669e-13
8.86782e-13]
[6.88332e-02 6.88334e-02 6.88336e-02 ... 6.88455e-02 6.88457e-02
6.88459e-02]]
True


Similar to the original file, the rows of the matrix correspond to positions in the isotopic vector, and the columns correspond to positions in burnup/day vectors.

>>> fuel.mdens.shape  # rows, columns
(34, 72)
>>> fuel.burnup.shape
(72,)
>>> len(fuel.names)
34


Data Retrieval¶

At the heart of the DepletedMaterial is the getValues() method. This method acts as an slicing mechanism that returns data for a select number of isotopes at select points in time. getValues() requires two arguments for the units of time requested, e.g. days or burnup, and the name of the data requested. This second value must be a key in the data dictionary.

Specific days or values of burnup can be passed with the timePoints keyword. This will instruct the slicing tool to retrieve data that corresponds to values of days or burnup in the timePoints list. By default the method returns data for every time point on the material unless timePoints is given. Similarly, one can pass a string or list of strings as the names or zai arguments and obtain data for those specific isotopes. Data for every isotope is given if names or zai are not given.

>>> dayPoints = [0, 5, 10, 30]
>>> iso = ['Xe135', 'Sm149']
>>> zai = [541350, 621490]
>>> isoVals = fuel.getValues('days', 'a', dayPoints, iso)
>>> print(isoVals.shape)
>>> zaiVals = fuel.getValues('days', 'a', dayPoints, zai=zai)
print(isoVals - zaiVals)
(2, 4)
[[0.00000e+00 3.28067e+14 3.24606e+14 3.27144e+14]
[0.00000e+00 0.00000e+00 0.00000e+00 0.00000e+00]]
[[ 0.  0.  0.  0.]
[ 0.  0.  0.  0.]]


The DepletedMaterial uses this slicing for the built-in plot() method, which takes similar slicing arguments to getValues().

By default, the plot method will plot data for all isotopes present, leading to very busy plots. The plots can be cleaned up by passing isotope names or ZZAAAI identifiers to the names or zai arguments, respectively.

>>> fuel.plot('burnup', 'ingTox', names='Xe135');

>>> fuel.plot('burnup', 'mdens', zai=[541350, 531350]);


This type of plotting can also be applied to the DepletedMaterial level, with similar options for formatting and retrieving data. The materials to be plotted can be filtered using the materials argument. The labelFmt argument can be used to apply a consistent label to each unique plot. This argument supports brace-delimited formatting, and will automatically replace strings like {mat} with the name of the material. The table below contains the special strings and their replacements

String

Replacement

{mat}

Name of the material

{iso}

Name of the isotope, e.g. 'U235'

{zai}

ZZAAAI of the isotope, e.g. 922350

>>> dep.plot('burnup', 'adens', names=iso,
...          materials=['fuel0', 'total'],
...          labelFmt="{mat}: {iso} // {zai}", loglog=True);


Settings¶

The DepletionReader also has a collection of settings to control what data is stored. If none of these settings are modified, the default is to store all the data from the output file. The settings that control the depletion reader are

Below is an example of configuring a DepletionReader that only stores the burnup days, and atomic density for all materials that begin with bglass followed by at least one integer.

>>> rc['depletion.processTotal'] = False
>>> rc['depletion.materials'] = [r'bglass\d+']
dict_keys(['bglass0'])
>>> bglass.data.keys()


Integration with pandas¶

If you have the pandas package installed, you can use the toDataFrame() method to create tabulated data. The method will retrieve data for all isotopes unless the names or zai arguments are provided. For compactness, only a few isotopes will be retrieved here.

>>> fuel.toDataFrame("adens", names=["U235", "Pu239", "Xe135"]).head()
Isotopes U235 Pu239 Xe135
Time [d]
0.0 0.000558 0.000000e+00 0.000000e+00
0.5 0.000558 6.374580e-09 2.435910e-09
1.0 0.000558 2.590310e-08 4.037960e-09
1.5 0.000558 5.728820e-08 4.620920e-09
2.0 0.000557 9.927160e-08 4.789480e-09


Arguments can also be used to control the time values in the index and column structure:

>>> fuel.toDataFrame("adens", zai=[922350, 942390, 541350], time="burnup")
Isotope ZAI 922350 942390 541350
Burnup [MWd/kgU]
0.0 0.000558 0.000000e+00 0.000000e+00
0.5 0.000558 6.374580e-09 2.435910e-09
1.0 0.000558 2.590310e-08 4.037960e-09
1.5 0.000558 5.728820e-08 4.620920e-09
2.0 0.000557 9.927160e-08 4.789480e-09


Conclusion¶

The DepletionReader is capable of reading and storing all the data from the SERPENT burned materials file. Upon reading, the reader creates custom DepletedMaterial objects that are responsible for storing and retrieving the data. These objects also have a handy plot() method for quick analysis. Use of the rc settings control object allows increased control over the data selected from the output file.

References¶

1. J. Leppänen, M. Pusa, T. Viitanen, V. Valtavirta, and T. Kaltiaisenaho. “The Serpent Monte Carlo code: Status, development and applications in 2013.” Ann. Nucl. Energy, 82 (2015) 142-150