openmc-designs/VHTR/VHTR.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "s8q2_PI6vJDd",
    "outputId": "b4a99b1c-90b1-4484-bb73-ed358a0d9b2b"
   },
   "source": [
    "# A VHTR geometry \n",
    "This notebook can be used as a template for modeling VHTR reactors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "ztdDaVCavN_I"
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import openmc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Ran-jogzvQvC",
    "outputId": "422e9494-2575-4625-c4c1-20a55a442142"
   },
   "outputs": [],
   "source": [
    "# Materials definitions\n",
    "\n",
    "fuel = openmc.Material(name='Fuel')\n",
    "fuel.add_element('U', 1.0, enrichment=4.0)\n",
    "fuel.add_nuclide('O16', 2.0)\n",
    "fuel.set_density('g/cm3', 10.41)\n",
    "\n",
    "buffer = openmc.Material(name='Buffer')\n",
    "buffer.add_element('C', 1.0)\n",
    "buffer.set_density('g/cm3', 0.95)\n",
    "buffer.add_s_alpha_beta('c_Graphite')\n",
    "\n",
    "IPyC = openmc.Material(name='Inner PyC')\n",
    "IPyC.add_element('C', 1.0)\n",
    "IPyC.set_density('g/cm3', 1.9)\n",
    "IPyC.add_s_alpha_beta('c_Graphite')\n",
    "\n",
    "SiC = openmc.Material(name = \"SiC\")\n",
    "SiC.add_element(\"Si\", 0.5)\n",
    "SiC.add_element(\"C\", 0.5)\n",
    "SiC.set_density(\"g/cm3\", 3.18)\n",
    "\n",
    "OPyC = openmc.Material(name='Outer PyC')\n",
    "OPyC.add_element('C', 1.0)\n",
    "OPyC.set_density('g/cm3', 1.9)\n",
    "OPyC.add_s_alpha_beta('c_Graphite')\n",
    "\n",
    "graphite = openmc.Material(name='Graphite')\n",
    "graphite.add_element('C', 1.0)\n",
    "graphite.set_density('g/cm3', 1.7)\n",
    "graphite.add_s_alpha_beta('c_Graphite')\n",
    "\n",
    "helium = openmc.Material(name='Helium')\n",
    "helium.add_element('He', 1.0)\n",
    "helium.set_density('g/cm3', 0.000166)\n",
    "\n",
    "b4c = openmc.Material(name='B4C Poison')\n",
    "b4c.add_element('B', 4.0, enrichment=18.7, enrichment_target='B10', enrichment_type='wo')\n",
    "b4c.add_element('C', 1.0)\n",
    "b4c.set_density('g/cm3', 1.82)\n",
    "\n",
    "# Instantiate a Materials collection and export to xml\n",
    "materials_list = [fuel, buffer, IPyC, SiC, OPyC, graphite, helium, b4c]\n",
    "materials_file = openmc.Materials(materials_list)\n",
    "materials_file.export_to_xml()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "id": "OU_alkFfwVGd",
    "outputId": "7c06ff69-2077-456e-b860-9b385465151f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f5702afba10>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 258.065x259.74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Geometry definitions for TRISO particles\n",
    "\n",
    "kernelsph = openmc.Sphere(r=250e-4)\n",
    "buffsph = openmc.Sphere(r=350e-4)\n",
    "IPyCsph = openmc.Sphere(r=390e-4)\n",
    "SiCsph = openmc.Sphere(r=425e-4)\n",
    "OPyCsph = openmc.Sphere(r=470e-4)\n",
    "\n",
    "layers = [kernelsph, buffsph, IPyCsph, SiCsph, OPyCsph]\n",
    "triso_mats = [fuel, buffer, IPyC, SiC, OPyC]\n",
    "triso_cells = []\n",
    "for i in range(5):\n",
    "  if (i == 0):\n",
    "    triso_cells.append(openmc.Cell(fill=triso_mats[0], region=-layers[0]))\n",
    "  else:\n",
    "    triso_cells.append(openmc.Cell(fill=triso_mats[i], region=+layers[i-1] & -layers[i]))\n",
    "\n",
    "triso_universe = openmc.Universe(cells=triso_cells)\n",
    "triso_colors = {triso_cells[0]: (199, 51, 51), triso_cells[1]: (176, 227, 74),\n",
    "                triso_cells[2]: (74, 186, 120), triso_cells[3]: (31, 74, 107),\n",
    "                triso_cells[4]: (74, 186, 120)}\n",
    "triso_universe.plot(width = (0.1, 0.1), colors = triso_colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "iRZUbB1uqld6",
    "outputId": "371a1ccc-3603-447a-8721-2c0090b2448c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Cell\n",
      "\tID             =\t1\n",
      "\tName           =\t\n",
      "\tFill           =\tMaterial 1\n",
      "\tRegion         =\t-1\n",
      "\tRotation       =\tNone\n",
      "\tTemperature    =\tNone\n",
      "\tTranslation    =\tNone\n",
      "\tVolume         =\tNone\n",
      ", Cell\n",
      "\tID             =\t2\n",
      "\tName           =\t\n",
      "\tFill           =\tMaterial 2\n",
      "\tRegion         =\t(1 -2)\n",
      "\tRotation       =\tNone\n",
      "\tTemperature    =\tNone\n",
      "\tTranslation    =\tNone\n",
      "\tVolume         =\tNone\n",
      ", Cell\n",
      "\tID             =\t3\n",
      "\tName           =\t\n",
      "\tFill           =\tMaterial 3\n",
      "\tRegion         =\t(2 -3)\n",
      "\tRotation       =\tNone\n",
      "\tTemperature    =\tNone\n",
      "\tTranslation    =\tNone\n",
      "\tVolume         =\tNone\n",
      ", Cell\n",
      "\tID             =\t4\n",
      "\tName           =\t\n",
      "\tFill           =\tMaterial 4\n",
      "\tRegion         =\t(3 -4)\n",
      "\tRotation       =\tNone\n",
      "\tTemperature    =\tNone\n",
      "\tTranslation    =\tNone\n",
      "\tVolume         =\tNone\n",
      ", Cell\n",
      "\tID             =\t5\n",
      "\tName           =\t\n",
      "\tFill           =\tMaterial 5\n",
      "\tRegion         =\t(4 -5)\n",
      "\tRotation       =\tNone\n",
      "\tTemperature    =\tNone\n",
      "\tTranslation    =\tNone\n",
      "\tVolume         =\tNone\n",
      "]\n"
     ]
    }
   ],
   "source": [
    "print(triso_cells)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "9ZjOD3umK-RO"
   },
   "outputs": [],
   "source": [
    "# Generating TRISO particle lattice in cylindrical pin cell\n",
    "\n",
    "cylsurf = openmc.ZCylinder(r=0.6225)\n",
    "maxz = openmc.ZPlane(z0=1.95, boundary_type='reflective')\n",
    "minz = openmc.ZPlane(z0=-1.95, boundary_type='reflective')\n",
    "\n",
    "lattice_region = -cylsurf & -maxz & +minz\n",
    "triso_outer_radius = 465e-4\n",
    "spheres = openmc.model.pack_spheres(radius=triso_outer_radius, region=lattice_region, pf=0.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "u7tWPGkaQaPP"
   },
   "outputs": [],
   "source": [
    "triso_particles = [openmc.model.TRISO(triso_outer_radius, fill=triso_universe, center=c) for c in spheres]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "OIyhbji9Rvzr",
    "outputId": "4f4e84a2-0b07-4318-c1b6-1b1f55a1a232"
   },
   "outputs": [],
   "source": [
    "vol_triso = 4/3 * 3.14 * triso_outer_radius**3 * len(triso_particles)\n",
    "actual_pf = vol_triso/(3.14 * (0.6225) ** 2 * 3.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "2Z8EXBSgR_yq"
   },
   "outputs": [],
   "source": [
    "lattice_cell = openmc.Cell(region=lattice_region)\n",
    "lower_left, upp_right = lattice_cell.region.bounding_box\n",
    "shape = (4, 4, 4)\n",
    "pitch = (upp_right - lower_left)/shape\n",
    "triso_latt = openmc.model.create_triso_lattice(triso_particles, lower_left, pitch, shape, graphite)\n",
    "lattice_cell.fill = triso_latt\n",
    "\n",
    "lattice_universe = openmc.Universe(cells=[lattice_cell])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "id": "8S3JIn-x9doF",
    "outputId": "da1312f4-92c6-4100-97a2-66af845295f7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f56f8ad9a90>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 258.065x259.74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lattice_universe.plot(width=(1.4,1.4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "id": "yTqFsu7U9Pmf",
    "outputId": "ebd66100-aa13-452b-912a-a1fed9e964f5"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f56f91a37d0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 258.065x259.74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lattice_universe.plot(width=(1.4,1.4), color_by='material', colors = {graphite: (20, 23, 66)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "j3_6A6g-L_d4"
   },
   "source": [
    "**Testing Pin Cell Embedded In Graphite Block**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "t80buCTqL-84"
   },
   "outputs": [],
   "source": [
    "hexaregion = openmc.model.hexagonal_prism(edge_length = 0.85, orientation = 'x', boundary_type='reflective')\n",
    "\n",
    "outer_region = hexaregion & +cylsurf & -maxz & +minz\n",
    "outer_pin_cell = openmc.Cell(fill=graphite, region = outer_region)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "ho_e-y7Cgi_q"
   },
   "outputs": [],
   "source": [
    "pin_cell_universe = openmc.Universe(cells=[lattice_cell, outer_pin_cell])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "id": "76wi7ezZgoHj",
    "outputId": "55590ede-ff67-4a78-96d2-87d902b2c366"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f56f81d46d0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 258.065x259.74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pin_cell_universe.plot(width=(1.8, 1.8), color_by='cell', colors = {outer_pin_cell: (20, 23, 66)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jJasUqJAhn_e"
   },
   "source": [
    "As expected, the outside hexagonal block and the non-triso area of the pin cell are both filled with graphite:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "id": "SnF1LEnihncs",
    "outputId": "f9671980-db4b-4ce0-99a4-867aa59fe5d9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f56f716aa10>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 258.065x259.74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pin_cell_universe.plot(width=(1.9, 1.9), color_by='material', colors = {graphite: (20, 23, 66), fuel: (255, 219, 145)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Mp8W0NWEhzhZ",
    "outputId": "2204e776-fed4-4007-a05d-cba6acb11789"
   },
   "outputs": [],
   "source": [
    "geom = openmc.Geometry(pin_cell_universe)\n",
    "geom.export_to_xml()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OKwVl93-GboP"
   },
   "source": [
    "**Creating Coolant Channels/Cells (Helium fill)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "lLnEBbE3aJqa"
   },
   "outputs": [],
   "source": [
    "small_coolant_surf = openmc.ZCylinder(r=0.6375)\n",
    "big_coolant_surf = openmc.ZCylinder(r=0.79375)\n",
    "\n",
    "small_coolant_cell = openmc.Cell(region=-small_coolant_surf & -maxz & +minz, fill=helium)\n",
    "big_coolant_cell = openmc.Cell(region=-big_coolant_surf & -maxz & +minz, fill=helium)\n",
    "\n",
    "outside_small_cell = openmc.Cell(region=+small_coolant_surf & -maxz & +minz, fill=graphite)\n",
    "outside_big_cell = openmc.Cell(region=+big_coolant_surf & -maxz & +minz, fill=graphite)\n",
    "\n",
    "small_coolant_universe = openmc.Universe(cells=[small_coolant_cell, outside_small_cell])\n",
    "big_coolant_universe = openmc.Universe(cells=[big_coolant_cell, outside_big_cell])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2wVWLYBZAJdL"
   },
   "source": [
    "**Burnable Poison Rod Geometry**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 286
    },
    "id": "aJnsdDgr7KeF",
    "outputId": "f73b7161-dd64-49db-cd48-cde093cb4af9"
   },
   "outputs": [],
   "source": [
    "poison_surf = openmc.ZCylinder(r=0.6375)\n",
    "poison_cell = openmc.Cell(region=-poison_surf & -maxz & +minz, fill=b4c)\n",
    "outside_poison_cell = openmc.Cell(region=+poison_surf & -maxz & +minz, fill=graphite)\n",
    "\n",
    "poison_universe = openmc.Universe(cells=[poison_cell, outside_poison_cell])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FSEppy7-wB1-"
   },
   "source": [
    "**Defining Material Outside Pin Cell For Use in Assemblies**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "id": "ijZDqnyY7Y2f"
   },
   "outputs": [],
   "source": [
    "outer_pin_region = +cylsurf & -maxz & +minz\n",
    "outer_pin_cell = openmc.Cell(fill=graphite, region=outer_pin_region)\n",
    "\n",
    "total_pin_cell_universe = openmc.Universe(cells=[lattice_cell, outer_pin_cell])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "id": "s-DGB0Nf8guO",
    "outputId": "355536e5-e765-4900-9c97-e2ed00503f8f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f56f716b7d0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 258.065x259.74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_pin_cell_universe.plot(width=(1.9, 1.9), color_by='material', colors = {graphite: (20, 23, 66)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LfIatUoiIeSa"
   },
   "source": [
    "**Constructing Geometry of Hexagonal Fuel Assembly**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "gxixGDvIIXnH"
   },
   "outputs": [],
   "source": [
    "outer_graphite_cell = openmc.Cell(fill=graphite)\n",
    "outer_graphite_universe = openmc.Universe(cells=[outer_graphite_cell])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "0lt1V5rQJFlY"
   },
   "outputs": [],
   "source": [
    "assemblylat = openmc.HexLattice(name=\"Assembly\")\n",
    "assemblylat.outer = outer_graphite_universe\n",
    "assemblylat.pitch = (1.9,)\n",
    "assemblylat.center = (0.0, 0.0)\n",
    "assemblylat.orientation = 'x'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "6NyajaT_Dhdf"
   },
   "outputs": [],
   "source": [
    "def repeat_lat_element(n, pad_left, pad_right):\n",
    "  ring = []\n",
    "  for i in range(6):\n",
    "    ring += pad_left\n",
    "    for i in range(n):\n",
    "      ring.extend([total_pin_cell_universe]*2 + [big_coolant_universe])\n",
    "    ring += pad_right\n",
    "\n",
    "  return ring"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "eMfy_09gPIjE"
   },
   "outputs": [],
   "source": [
    "def build_outer_ring(n, insert_poison_rod):\n",
    "  REPEAT_SECTION = 2\n",
    "  ring = []\n",
    "\n",
    "  # burnable poison rods sides\n",
    "  poisonring = []\n",
    "  poisonring += [insert_poison_rod] + [total_pin_cell_universe] + [big_coolant_universe]\n",
    "  for i in range(REPEAT_SECTION):\n",
    "      poisonring.extend([total_pin_cell_universe]*2 + [big_coolant_universe])\n",
    "  poisonring += [total_pin_cell_universe]\n",
    "\n",
    "  # normal sides\n",
    "  base = []\n",
    "  base += [outer_graphite_universe] + [total_pin_cell_universe] + [big_coolant_universe]\n",
    "  for i in range(REPEAT_SECTION):\n",
    "      base.extend([total_pin_cell_universe]*2 + [big_coolant_universe])\n",
    "  base += [total_pin_cell_universe]\n",
    "\n",
    "  ring.extend(poisonring * n + base * (6 - n))\n",
    "\n",
    "  return ring"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "vygU8F5vLG2x"
   },
   "outputs": [],
   "source": [
    "def build_all_rings(insert_poison_rod):\n",
    "  rings = []\n",
    "\n",
    "  outer_ring = build_outer_ring(2, insert_poison_rod)\n",
    "  rings.append(outer_ring)\n",
    "\n",
    "  for i in range(1, 8): # rings 1 through 7\n",
    "    ring_left = []\n",
    "    ring_right = []\n",
    "    if (i % 3 == 1):\n",
    "      ring_left = [big_coolant_universe]\n",
    "      ring_right = [total_pin_cell_universe]*2\n",
    "    elif (i % 3 == 2):\n",
    "      ring_left = [total_pin_cell_universe] + [big_coolant_universe]\n",
    "    else:\n",
    "      ring_right = [total_pin_cell_universe]\n",
    "\n",
    "    n = 0\n",
    "    if (i <= 3):\n",
    "      n = 2\n",
    "    elif (i <= 6):\n",
    "      n = 1\n",
    "    else:\n",
    "      n = 0\n",
    "\n",
    "    cur_ring = repeat_lat_element(n, ring_left, ring_right)\n",
    "    rings.append(cur_ring)\n",
    "\n",
    "  inner_ring = []\n",
    "  for i in range(6):\n",
    "    inner_ring.extend([total_pin_cell_universe] + [small_coolant_universe])\n",
    "  rings.append(inner_ring)\n",
    "  rings.append([outer_graphite_universe]*6)\n",
    "  rings.append([outer_graphite_universe])\n",
    "\n",
    "  return rings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "id": "KAqeuKY2j19E"
   },
   "outputs": [],
   "source": [
    "rings = build_all_rings(poison_universe)\n",
    "assemblylat.universes = rings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "LZWflaDwla6d"
   },
   "outputs": [],
   "source": [
    "assembly_surf = openmc.model.hexagonal_prism(edge_length=21, orientation='x', boundary_type='reflective')\n",
    "assembly_cell = openmc.Cell(fill=assemblylat, region=assembly_surf & +minz & -maxz)\n",
    "assembly_universe = openmc.Universe(cells=[assembly_cell])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 282
    },
    "id": "iMr7NMMTs6kT",
    "outputId": "a1ece088-efa8-4cc1-da2a-258fbe0ac6d6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f56f8001510>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 258.065x259.74 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "assembly_universe.plot(width=(42, 42), color_by='material', colors={helium: (252, 0, 69), graphite: (20, 23, 66), b4c:  (1, 217, 26)})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "pIFgdKfmyY7b",
    "outputId": "b3e9bf24-0450-47ad-9430-023413ec58f6"
   },
   "outputs": [],
   "source": [
    "geom = openmc.Geometry(assembly_universe)\n",
    "geom.export_to_xml()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "id": "RUFinDv9-4AH"
   },
   "outputs": [],
   "source": [
    "# OpenMC simulation parameters\n",
    "\n",
    "batches = 100\n",
    "inactive = 10\n",
    "particles = 5000\n",
    "\n",
    "settings_file = openmc.Settings()\n",
    "settings_file.batches = batches\n",
    "settings_file.inactive = inactive\n",
    "settings_file.particles = particles\n",
    "settings_file.output = {'tallies': True}\n",
    "\n",
    "bounds = [-5, -5, -0.63, 5, 5, 0.63]\n",
    "uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n",
    "settings_file.source = openmc.IndependentSource(space=uniform_dist)\n",
    "\n",
    "settings_file.export_to_xml()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "VHTR.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "openmc-env",
   "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": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}