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OpenMC/examples/jupyter/candu.ipynb
Paul Romano bc09d1ef55 adding back files to be reviewed
2019-10-28 11:55:45 -05:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In this example, we will create a typical CANDU bundle with rings of fuel pins. At present, OpenMC does not have a specialized lattice for this type of fuel arrangement, so we must resort to manual creation of the array of fuel pins."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from math import pi, sin, cos\n",
"import numpy as np\n",
"import openmc"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's begin by creating the materials that will be used in our model."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"fuel = openmc.Material(name='fuel')\n",
"fuel.add_element('U', 1.0)\n",
"fuel.add_element('O', 2.0)\n",
"fuel.set_density('g/cm3', 10.0)\n",
"\n",
"clad = openmc.Material(name='zircaloy')\n",
"clad.add_element('Zr', 1.0)\n",
"clad.set_density('g/cm3', 6.0)\n",
"\n",
"heavy_water = openmc.Material(name='heavy water')\n",
"heavy_water.add_nuclide('H2', 2.0)\n",
"heavy_water.add_nuclide('O16', 1.0)\n",
"heavy_water.add_s_alpha_beta('c_D_in_D2O')\n",
"heavy_water.set_density('g/cm3', 1.1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With our materials created, we'll now define key dimensions in our model. These dimensions are taken from the example in section 11.1.3 of the [Serpent manual](http://montecarlo.vtt.fi/download/Serpent_manual.pdf)."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"# Outer radius of fuel and clad\n",
"r_fuel = 0.6122\n",
"r_clad = 0.6540\n",
"\n",
"# Pressure tube and calendria radii\n",
"pressure_tube_ir = 5.16890\n",
"pressure_tube_or = 5.60320\n",
"calendria_ir = 6.44780\n",
"calendria_or = 6.58750\n",
"\n",
"# Radius to center of each ring of fuel pins\n",
"ring_radii = np.array([0.0, 1.4885, 2.8755, 4.3305])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To begin creating the bundle, we'll first create annular regions completely filled with heavy water and add in the fuel pins later. The radii that we've specified above correspond to the center of each ring. We actually need to create cylindrical surfaces at radii that are half-way between the centers."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# These are the surfaces that will divide each of the rings\n",
"radial_surf = [openmc.ZCylinder(r=r) for r in\n",
" (ring_radii[:-1] + ring_radii[1:])/2]\n",
"\n",
"water_cells = []\n",
"for i in range(ring_radii.size):\n",
" # Create annular region\n",
" if i == 0:\n",
" water_region = -radial_surf[i]\n",
" elif i == ring_radii.size - 1:\n",
" water_region = +radial_surf[i-1]\n",
" else:\n",
" water_region = +radial_surf[i-1] & -radial_surf[i]\n",
" \n",
" water_cells.append(openmc.Cell(fill=heavy_water, region=water_region))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's see what our geometry looks like so far. In order to plot the geometry, we create a universe that contains the annular water cells and then use the `Universe.plot()` method. While we're at it, we'll set some keyword arguments that can be reused for later plots."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x154b1fe8f438>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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ksYj4dNudRsQZ25+T9IikGUn3RcSzbfe7xJWSPiHpGdtPjZ+7MyIezjyOEuyWtG8cyMck3ZKiUa4YBCpX+nIAQMsIAaByhABQOUIAqBwhAFSOEAAqRwgAlSMEgMr9P9Ske2C/wpRUAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plot_args = {'width': (2*calendria_or, 2*calendria_or)}\n",
"bundle_universe = openmc.Universe(cells=water_cells)\n",
"bundle_universe.plot(**plot_args)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we need to create a universe that contains a fuel pin. Note that we don't actually need to put water outside of the cladding in this universe because it will be truncated by a higher universe."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"surf_fuel = openmc.ZCylinder(r=r_fuel)\n",
"\n",
"fuel_cell = openmc.Cell(fill=fuel, region=-surf_fuel)\n",
"clad_cell = openmc.Cell(fill=clad, region=+surf_fuel)\n",
"\n",
"pin_universe = openmc.Universe(cells=(fuel_cell, clad_cell))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x154b1de334a8>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"pin_universe.plot(**plot_args)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The code below works through each ring to create a cell containing the fuel pin universe. As each fuel pin is created, we modify the region of the water cell to include everything outside the fuel pin."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"num_pins = [1, 6, 12, 18]\n",
"angles = [0, 0, 15, 0]\n",
"\n",
"for i, (r, n, a) in enumerate(zip(ring_radii, num_pins, angles)):\n",
" for j in range(n):\n",
" # Determine location of center of pin\n",
" theta = (a + j/n*360.) * pi/180.\n",
" x = r*cos(theta)\n",
" y = r*sin(theta)\n",
" \n",
" pin_boundary = openmc.ZCylinder(x0=x, y0=y, r=r_clad)\n",
" water_cells[i].region &= +pin_boundary\n",
" \n",
" # Create each fuel pin -- note that we explicitly assign an ID so \n",
" # that we can identify the pin later when looking at tallies\n",
" pin = openmc.Cell(fill=pin_universe, region=-pin_boundary)\n",
" pin.translation = (x, y, 0)\n",
" pin.id = (i + 1)*100 + j\n",
" bundle_universe.add_cell(pin)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x154b1ddaadd8>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"bundle_universe.plot(**plot_args)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Looking pretty good! Finally, we create cells for the pressure tube and calendria and then put our bundle in the middle of the pressure tube."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"pt_inner = openmc.ZCylinder(r=pressure_tube_ir)\n",
"pt_outer = openmc.ZCylinder(r=pressure_tube_or)\n",
"calendria_inner = openmc.ZCylinder(r=calendria_ir)\n",
"calendria_outer = openmc.ZCylinder(r=calendria_or, boundary_type='vacuum')\n",
"\n",
"bundle = openmc.Cell(fill=bundle_universe, region=-pt_inner)\n",
"pressure_tube = openmc.Cell(fill=clad, region=+pt_inner & -pt_outer)\n",
"v1 = openmc.Cell(region=+pt_outer & -calendria_inner)\n",
"calendria = openmc.Cell(fill=clad, region=+calendria_inner & -calendria_outer)\n",
"\n",
"root_universe = openmc.Universe(cells=[bundle, pressure_tube, v1, calendria])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's look at the final product. We'll export our geometry and materials and then use `plot_inline()` to get a nice-looking plot."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"geom = openmc.Geometry(root_universe)\n",
"geom.export_to_xml()\n",
"\n",
"mats = openmc.Materials(geom.get_all_materials().values())\n",
"mats.export_to_xml()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"p = openmc.Plot.from_geometry(geom)\n",
"p.color_by = 'material'\n",
"p.colors = {\n",
" fuel: 'black',\n",
" clad: 'silver',\n",
" heavy_water: 'blue'\n",
"}\n",
"p.to_ipython_image()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Interpreting Results\n",
"\n",
"One of the difficulties of a geometry like this is identifying tally results when there was no lattice involved. To address this, we specifically gave an ID to each fuel pin of the form 100\\*ring + azimuthal position. Consequently, we can use a distribcell tally and then look at our `DataFrame` which will show these cell IDs."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"settings = openmc.Settings()\n",
"settings.particles = 1000\n",
"settings.batches = 20\n",
"settings.inactive = 10\n",
"settings.source = openmc.Source(space=openmc.stats.Point())\n",
"settings.export_to_xml()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"fuel_tally = openmc.Tally()\n",
"fuel_tally.filters = [openmc.DistribcellFilter(fuel_cell)]\n",
"fuel_tally.scores = ['flux']\n",
"\n",
"tallies = openmc.Tallies([fuel_tally])\n",
"tallies.export_to_xml()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"openmc.run(output=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The return code of `0` indicates that OpenMC ran successfully. Now let's load the statepoint into a `openmc.StatePoint` object and use the `Tally.get_pandas_dataframe(...)` method to see our results."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"sp = openmc.StatePoint('statepoint.{}.h5'.format(settings.batches))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead tr th {\n",
" text-align: left;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th></th>\n",
" <th colspan=\"2\" halign=\"left\">level 1</th>\n",
" <th colspan=\"2\" halign=\"left\">level 2</th>\n",
" <th colspan=\"2\" halign=\"left\">level 3</th>\n",
" <th>distribcell</th>\n",
" <th>nuclide</th>\n",
" <th>score</th>\n",
" <th>mean</th>\n",
" <th>std. dev.</th>\n",
" </tr>\n",
" <tr>\n",
" <th></th>\n",
" <th>univ</th>\n",
" <th>cell</th>\n",
" <th>univ</th>\n",
" <th>cell</th>\n",
" <th>univ</th>\n",
" <th>cell</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" <tr>\n",
" <th></th>\n",
" <th>id</th>\n",
" <th>id</th>\n",
" <th>id</th>\n",
" <th>id</th>\n",
" <th>id</th>\n",
" <th>id</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>100</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>0</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.207805</td>\n",
" <td>0.007037</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>200</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>1</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.197197</td>\n",
" <td>0.005272</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>201</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.190310</td>\n",
" <td>0.007816</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>202</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>3</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.194736</td>\n",
" <td>0.006469</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>203</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.191097</td>\n",
" <td>0.006431</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>204</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.189910</td>\n",
" <td>0.004891</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>205</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>6</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.182203</td>\n",
" <td>0.003851</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>300</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>7</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.165922</td>\n",
" <td>0.005815</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>301</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>8</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.168933</td>\n",
" <td>0.008300</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>302</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>9</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.159587</td>\n",
" <td>0.003085</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>303</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>10</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.159158</td>\n",
" <td>0.005910</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>304</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>11</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.148537</td>\n",
" <td>0.005308</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>305</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>12</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.150945</td>\n",
" <td>0.006654</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>306</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>13</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.154237</td>\n",
" <td>0.003665</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>307</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>14</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.165888</td>\n",
" <td>0.004733</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>308</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>15</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.156777</td>\n",
" <td>0.006540</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>309</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>16</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.165277</td>\n",
" <td>0.005935</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>310</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>17</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.156528</td>\n",
" <td>0.005732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>311</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>18</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.159610</td>\n",
" <td>0.004584</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>400</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>19</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.096597</td>\n",
" <td>0.004466</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>401</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>20</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.118214</td>\n",
" <td>0.005451</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>402</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>21</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.106167</td>\n",
" <td>0.004722</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>403</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>22</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.110814</td>\n",
" <td>0.004208</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>404</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>23</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.112319</td>\n",
" <td>0.005079</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>405</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>24</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.110232</td>\n",
" <td>0.004153</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>406</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>25</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.099967</td>\n",
" <td>0.005085</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>407</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>26</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.095444</td>\n",
" <td>0.003615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>408</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>27</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.092620</td>\n",
" <td>0.003997</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>409</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>28</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.095517</td>\n",
" <td>0.004022</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>410</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>29</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.113737</td>\n",
" <td>0.009530</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>411</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>30</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.108368</td>\n",
" <td>0.007241</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>412</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>31</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.106990</td>\n",
" <td>0.005716</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>413</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>32</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.112050</td>\n",
" <td>0.005002</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>414</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>33</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.115054</td>\n",
" <td>0.006239</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>415</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>34</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.114394</td>\n",
" <td>0.004919</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>416</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>35</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.114352</td>\n",
" <td>0.005322</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>3</td>\n",
" <td>44</td>\n",
" <td>1</td>\n",
" <td>417</td>\n",
" <td>2</td>\n",
" <td>5</td>\n",
" <td>36</td>\n",
" <td>total</td>\n",
" <td>flux</td>\n",
" <td>0.110890</td>\n",
" <td>0.005051</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" level 1 level 2 level 3 distribcell nuclide score mean \\\n",
" univ cell univ cell univ cell \n",
" id id id id id id \n",
"0 3 44 1 100 2 5 0 total flux 2.08e-01 \n",
"1 3 44 1 200 2 5 1 total flux 1.97e-01 \n",
"2 3 44 1 201 2 5 2 total flux 1.90e-01 \n",
"3 3 44 1 202 2 5 3 total flux 1.95e-01 \n",
"4 3 44 1 203 2 5 4 total flux 1.91e-01 \n",
"5 3 44 1 204 2 5 5 total flux 1.90e-01 \n",
"6 3 44 1 205 2 5 6 total flux 1.82e-01 \n",
"7 3 44 1 300 2 5 7 total flux 1.66e-01 \n",
"8 3 44 1 301 2 5 8 total flux 1.69e-01 \n",
"9 3 44 1 302 2 5 9 total flux 1.60e-01 \n",
"10 3 44 1 303 2 5 10 total flux 1.59e-01 \n",
"11 3 44 1 304 2 5 11 total flux 1.49e-01 \n",
"12 3 44 1 305 2 5 12 total flux 1.51e-01 \n",
"13 3 44 1 306 2 5 13 total flux 1.54e-01 \n",
"14 3 44 1 307 2 5 14 total flux 1.66e-01 \n",
"15 3 44 1 308 2 5 15 total flux 1.57e-01 \n",
"16 3 44 1 309 2 5 16 total flux 1.65e-01 \n",
"17 3 44 1 310 2 5 17 total flux 1.57e-01 \n",
"18 3 44 1 311 2 5 18 total flux 1.60e-01 \n",
"19 3 44 1 400 2 5 19 total flux 9.66e-02 \n",
"20 3 44 1 401 2 5 20 total flux 1.18e-01 \n",
"21 3 44 1 402 2 5 21 total flux 1.06e-01 \n",
"22 3 44 1 403 2 5 22 total flux 1.11e-01 \n",
"23 3 44 1 404 2 5 23 total flux 1.12e-01 \n",
"24 3 44 1 405 2 5 24 total flux 1.10e-01 \n",
"25 3 44 1 406 2 5 25 total flux 1.00e-01 \n",
"26 3 44 1 407 2 5 26 total flux 9.54e-02 \n",
"27 3 44 1 408 2 5 27 total flux 9.26e-02 \n",
"28 3 44 1 409 2 5 28 total flux 9.55e-02 \n",
"29 3 44 1 410 2 5 29 total flux 1.14e-01 \n",
"30 3 44 1 411 2 5 30 total flux 1.08e-01 \n",
"31 3 44 1 412 2 5 31 total flux 1.07e-01 \n",
"32 3 44 1 413 2 5 32 total flux 1.12e-01 \n",
"33 3 44 1 414 2 5 33 total flux 1.15e-01 \n",
"34 3 44 1 415 2 5 34 total flux 1.14e-01 \n",
"35 3 44 1 416 2 5 35 total flux 1.14e-01 \n",
"36 3 44 1 417 2 5 36 total flux 1.11e-01 \n",
"\n",
" std. dev. \n",
" \n",
" \n",
"0 7.04e-03 \n",
"1 5.27e-03 \n",
"2 7.82e-03 \n",
"3 6.47e-03 \n",
"4 6.43e-03 \n",
"5 4.89e-03 \n",
"6 3.85e-03 \n",
"7 5.82e-03 \n",
"8 8.30e-03 \n",
"9 3.09e-03 \n",
"10 5.91e-03 \n",
"11 5.31e-03 \n",
"12 6.65e-03 \n",
"13 3.67e-03 \n",
"14 4.73e-03 \n",
"15 6.54e-03 \n",
"16 5.94e-03 \n",
"17 5.73e-03 \n",
"18 4.58e-03 \n",
"19 4.47e-03 \n",
"20 5.45e-03 \n",
"21 4.72e-03 \n",
"22 4.21e-03 \n",
"23 5.08e-03 \n",
"24 4.15e-03 \n",
"25 5.08e-03 \n",
"26 3.62e-03 \n",
"27 4.00e-03 \n",
"28 4.02e-03 \n",
"29 9.53e-03 \n",
"30 7.24e-03 \n",
"31 5.72e-03 \n",
"32 5.00e-03 \n",
"33 6.24e-03 \n",
"34 4.92e-03 \n",
"35 5.32e-03 \n",
"36 5.05e-03 "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t = sp.get_tally()\n",
"t.get_pandas_dataframe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can see that in the 'level 2' column, the 'cell id' tells us how each row corresponds to a ring and azimuthal position."
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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