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    "## Horn Antenna\n",
    "\n",
    "This notebook explores the design and discretization of a horn antenna. As part of our coursework, we will focus on generating a high-quality mesh that captures the geometry of the flared aperture, which is critical for accurate signal radiation. We will implement mesh refinement techniques to ensure the model effectively resolves the electromagnetic fields near the transition. The process concludes by exporting the finalized mesh, formatted for use in the Palace solver, where we will ultimately evaluate the antenna’s performance."
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   "source": [
    "import gmsh\n",
    "import math\n",
    "import os\n",
    "import json\n",
    "from pathlib import Path\n",
    "\n",
    "from palacetoolkit.geometry import xmin, xmax, ymin, ymax, zmin, zmax, extract_tag\n",
    "from palacetoolkit.viz import view_mesh\n",
    "from palacetoolkit.mesh import (\n",
    "    Entity,\n",
    "    run_entity_pipeline,\n",
    "    generate_3d_mesh,\n",
    "    create_graded_mesh\n",
    ")"
   ]
  },
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    "### Parameters:\n",
    " - filename : name of the mesh file to generate (e.g., \"horn_antenna.msh\")\n",
    " - waveguide_length : length of the waveguide section\n",
    " - waveguide_width : width of the waveguide section\n",
    " - waveguide_height : height of the waveguide section\n",
    " - flare_length : length of the flare section\n",
    " - flare_width : width of the flare section at the aperture\n",
    " - flare_height : height of the flare section at the aperture\n",
    " - freq_ghz : frequency of operation in GHz\n",
    " - gui : whether to launch the Gmsh GUI for visualization (True/False)\n",
    " - mesh_order : The order of interpolation for the finite element basis functions."
   ]
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    "filename = \"horn_antenna.msh\"\n",
    "waveguide_length = 0.3\n",
    "waveguide_width = 9.373e-2\n",
    "waveguide_height = 4.166e-2\n",
    "flare_length = 0.84\n",
    "flare_width = 30.0 * 0.0254\n",
    "flare_height = 23.8 * 0.0254\n",
    "freq_ghz = 1.8\n",
    "gui = False\n",
    "mesh_order = 1 \n",
    "\n",
    "# Wavelength in free space (lambda_0 = c / f).\n",
    "c0 = 3e8 \n",
    "wavelength = c0 / (freq_ghz * 1e9)\n",
    "\n",
    "lc = wavelength / 4"
   ]
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   "source": [
    "### Initializing the Modeling Environment"
   ]
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    "gmsh.initialize()\n",
    "gmsh.option.setNumber(\"General.Verbosity\", 5)\n",
    "gmsh.model.add(\"horn_antenna\")\n",
    "kernel = gmsh.model.occ"
   ]
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   "source": [
    "### Geometry Construction and Domain Definition\n",
    "In this step, we build the horn antenna geometry using the OpenCASCADE kernel. We define the waveguide input and the flared aperture as separate surface loops, connect them to form the solid volume, and finally define a surrounding spherical air domain. The geometry is fragmented to ensure consistent meshing across the waveguide and the radiation domain."
   ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "waveguide: [7, 8, 9, 10]\n",
      "flare: [3, 4, 5, 6]\n",
      "waveport: [11]\n"
     ]
    }
   ],
   "source": [
    "# Waveguide internal face\n",
    "kernel.addPoint(-waveguide_width/2, -waveguide_height/2, 0, lc, 1)\n",
    "kernel.addPoint(waveguide_width/2, -waveguide_height/2, 0, lc, 2)\n",
    "kernel.addPoint(waveguide_width/2, waveguide_height/2, 0, lc, 3)\n",
    "kernel.addPoint(-waveguide_width/2, waveguide_height/2, 0, lc, 4)\n",
    "\n",
    "kernel.addLine(1, 2, 1)\n",
    "kernel.addLine(2, 3, 2)\n",
    "kernel.addLine(3, 4, 3)\n",
    "kernel.addLine(4, 1, 4)\n",
    "\n",
    "kernel.addCurveLoop([4, 1, 2, 3], 1)\n",
    "kernel.addPlaneSurface([1], 1)\n",
    "\n",
    "# Flare faces. We only generate the four sides. \n",
    "kernel.addPoint(-flare_width/2, -flare_height/2, flare_length, lc, 5)\n",
    "kernel.addPoint(flare_width/2, -flare_height/2, flare_length, lc, 6)\n",
    "kernel.addPoint(flare_width/2,  flare_height/2, flare_length, lc, 7)\n",
    "kernel.addPoint(-flare_width/2, flare_height/2, flare_length, lc, 8)\n",
    "\n",
    "kernel.addLine(5, 6, 5)\n",
    "kernel.addLine(6, 7, 6)\n",
    "kernel.addLine(7, 8, 7)\n",
    "kernel.addLine(8, 5, 8)\n",
    "\n",
    "# Connect faces\n",
    "kernel.addLine(1, 5, 9)  \n",
    "kernel.addLine(2, 6, 10) \n",
    "kernel.addLine(3, 7, 11) \n",
    "kernel.addLine(4, 8, 12)\n",
    "\n",
    "kernel.addCurveLoop([1, 10, -5, -9], 3)\n",
    "kernel.addPlaneSurface([3], 3)\n",
    "kernel.addCurveLoop([2, 11, -6, -10], 4)\n",
    "kernel.addPlaneSurface([4], 4)\n",
    "kernel.addCurveLoop([3, 12, -7, -11], 5)\n",
    "kernel.addPlaneSurface([5], 5)\n",
    "kernel.addCurveLoop([4, 9, -8, -12], 6)\n",
    "kernel.addPlaneSurface([6], 6)\n",
    "\n",
    "# Surfaces\n",
    "flare = [3, 4, 5, 6]\n",
    "waveguide = kernel.extrude([(2, 1)], 0, 0, -waveguide_length)\n",
    "\n",
    "# Only the 2d surfaces\n",
    "waveguide = [(d, t) for (d, t) in waveguide if d == 2]\n",
    "\n",
    "# Air domain\n",
    "outer_radius = max(1.8 * wavelength, 1.1 * flare_length)\n",
    "air_sphere = kernel.addSphere(0, 0, flare_length/2, outer_radius)\n",
    "\n",
    "# Now, we want the external face of the waveguide to be the waveport, and also we do not want \n",
    "# the 'interior' face. \n",
    "\n",
    "# Finds the face between the waveguide and the flare.\n",
    "def is_internal_face(dimtag):\n",
    "    return math.isclose(zmin(dimtag), 0, abs_tol=1e-6) and math.isclose(zmax(dimtag), 0, abs_tol=1e-6)\n",
    "\n",
    "# Finds the external face.\n",
    "def is_external_face(dimtag):\n",
    "    return math.isclose(zmin(dimtag), -waveguide_length, abs_tol=1e-6) and math.isclose(zmax(dimtag), -waveguide_length, abs_tol=1e-6)\n",
    "\n",
    "# Filter and waveport\n",
    "waveport = [t for (d, t) in waveguide if is_external_face((d, t))]\n",
    "waveguide = [t for (d, t) in waveguide if not (is_internal_face((d, t)) or is_external_face((d, t)))] \n",
    "\n",
    "print(\"waveguide:\", waveguide)\n",
    "print(\"flare:\", flare)  \n",
    "print(\"waveport:\", waveport)"
   ]
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    "### Entities and mesh.\n",
    "\n",
    "Here we generate the entities that later will become the physical groups, generate and \n",
    "refine the mesh if necessary."
   ]
  },
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     "text": [
      "  Physical group 'air_sphere' (dim=3): pg=1, tags=[2]\n",
      "  Physical group 'waveguide' (dim=2): pg=2, tags=[9, 10, 7, 8]\n",
      "  Physical group 'flare' (dim=2): pg=3, tags=[3, 4, 5, 6]\n",
      "  Physical group 'waveport' (dim=2): pg=4, tags=[11]\n",
      "  Physical group 'air_sphere__None' (dim=2): pg=5, tags=[12]\n",
      "[Entity('air_sphere', dim=3, order=2, tags=[2]), Entity('waveguide', dim=2, order=1, tags=[9, 10, 7, 8]), Entity('flare', dim=2, order=1, tags=[3, 4, 5, 6]), Entity('waveport', dim=2, order=1, tags=[11])]\n",
      "  ignoring 3 curves from {'air_sphere__None'}\n",
      "  global: 20 curves, SizeMin=0.0067\n",
      "  ppw_near=25  ppw_far=5\n",
      "  SizeMax=0.0333  transition=0.0417\n"
     ]
    }
   ],
   "source": [
    "# Entity definition\n",
    "entities = [\n",
    "    Entity('air_sphere', dim=3, btype='dielectric', mesh_order=2, tags=[air_sphere], loss_tan=0.0, eps_r=1.0, mu_r=1.0),\n",
    "    Entity('waveguide', dim=2, btype='pec', mesh_order=1, tags=waveguide),\n",
    "    Entity('flare', dim=2, btype='pec', mesh_order=1, tags=flare),\n",
    "    Entity('waveport', dim=2, btype='waveport', mesh_order=1, tags=waveport),\n",
    "]\n",
    "\n",
    "# Boolean operations to guarantee a nice mesh, algo it returns the\n",
    "# physical group map.\n",
    "pg_map = run_entity_pipeline(entities)\n",
    "\n",
    "print(entities)\n",
    "\n",
    "# Refine near the port\n",
    "create_graded_mesh(  wavelength, \n",
    "                     ppw_near=25, \n",
    "                     ppw_far=5, \n",
    "                     set_as_background=True)\n",
    "\n",
    "# Mesh sizes\n",
    "mesh_sizes = {}\n",
    "\n",
    "generate_3d_mesh(entities, mesh_sizes, filename, optimize=True, verbose=False)\n",
    "gmsh.finalize()"
   ]
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     "text": [
      "Loading mesh file: horn_antenna.msh\n",
      "Groups to render transparent: ['air_sphere__None']\n",
      "\n",
      "Mesh loaded successfully with 1 cell blocks\n",
      "Found 34138 triangles total\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Physical group tags in mesh: {2: 'waveguide', 3: 'flare', 4: 'waveport', 5: 'air_sphere__None'}\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize the mesh in the notebook.\n",
    "view_mesh(filename, transparent_groups=[\"air_sphere__None\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
   "id": "b16df631",
   "metadata": {
    "papermill": {
     "duration": 0.002914,
     "end_time": "2026-08-04T14:43:17.471266+00:00",
     "exception": false,
     "start_time": "2026-08-04T14:43:17.468352+00:00",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "### Output configuration for Palace JSON input file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a84b90f0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-08-04T14:43:17.490944Z",
     "iopub.status.busy": "2026-08-04T14:43:17.490773Z",
     "iopub.status.idle": "2026-08-04T14:43:17.494218Z",
     "shell.execute_reply": "2026-08-04T14:43:17.493516Z"
    },
    "papermill": {
     "duration": 0.007717,
     "end_time": "2026-08-04T14:43:17.494721+00:00",
     "exception": false,
     "start_time": "2026-08-04T14:43:17.487004+00:00",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "freq_min = 1.8\n",
    "freq_max = 1.8\n",
    "freq_step = 0.1\n",
    "\n",
    "# absorbing boundary condition order (1 for first-order ABC, 2 for second-order ABC, etc.)\n",
    "abc_order = 2\n",
    "solver_order = 2\n",
    "\n",
    "output_file = \"horn_antenna.json\""
   ]
  },
  {
   "cell_type": "markdown",
   "execution_count": null,
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    "### Generating the Palace Configuration File\n",
    "Finally, we assemble the simulation parameters into a JSON configuration file. This dictionary defines the electromagnetic problem type, assigns material properties to our physical volumes, sets boundary conditions (such as the WavePort excitation and absorbing boundaries), and configures the solver's convergence criteria. This file serves as the definitive input for Palace to execute the full-wave analysis of the horn antenna."
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    "output_stem = Path(filename).stem\n",
    "\n",
    "config = {\n",
    "    \"Problem\": {\"Type\": \"Driven\", \"Verbose\": 2, \"Output\": f\"postpro/{output_stem}\"},\n",
    "    \"Model\": {\"Mesh\": filename, \"L0\": 1.0},\n",
    "    \"Domains\": {\n",
    "        \"Materials\": [{\n",
    "            \"Attributes\": [pg_map[\"air_sphere\"]],\n",
    "            \"Permeability\": 1.0, \"Permittivity\": 1.0, \"LossTan\": 0.0\n",
    "        }]\n",
    "    },\n",
    "    \"Boundaries\": {\n",
    "        \"Absorbing\": {\"Attributes\": [pg_map[\"air_sphere__None\"]], \"Order\": abc_order},\n",
    "        \"PEC\": {\"Attributes\": [pg_map[\"waveguide\"], pg_map[\"flare\"]]},\n",
    "        \"Postprocessing\": {\n",
    "            \"FarField\": {\n",
    "                \"Attributes\": [pg_map[\"air_sphere__None\"]],\n",
    "                \"NSample\": 64000 \n",
    "            }\n",
    "        },\n",
    "        \"WavePort\": [{\n",
    "            \"Index\": 1, \"Attributes\": [pg_map[\"waveport\"]],\n",
    "            \"Mode\": 1, \"Offset\": 0.0, \"Excitation\": True\n",
    "        }]\n",
    "    },\n",
    "    \"Solver\": {\n",
    "        \"Order\": solver_order, \"Device\": \"CPU\",\n",
    "        \"Driven\": {\"MinFreq\": freq_min, \"MaxFreq\": freq_max, \"FreqStep\": freq_step, \"SaveStep\": 1, \"AdaptiveTol\": 0.0001},\n",
    "        \"Linear\": {\"Type\": \"Default\", \"KSPType\": \"GMRES\", \"Tol\": 1e-7, \"MaxIts\": 3000, \"MaxSize\": 1000, \"ComplexCoarseSolve\": True}\n",
    "    }\n",
    "}\n",
    "\n",
    "script_dir = os.getcwd()\n",
    "config_path = os.path.join(script_dir, output_file)\n",
    "with open(config_path, \"w\") as f: json.dump(config, f, indent=2)"
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