{ "cells": [ { "cell_type": "markdown", "id": "c8d99df0", "metadata": { "papermill": { "duration": 0.001442, "end_time": "2026-05-27T20:01:00.696743+00:00", "exception": false, "start_time": "2026-05-27T20:01:00.695301+00:00", "status": "completed" }, "tags": [] }, "source": [ "# Microstrip Modes\n", "\n", "This notebook builds a simple boxed microstrip cross-section (substrate + air + PEC strip conductor), solves eigenmodes with `WaveguideModeSolver`, and plots the first fields." ] }, { "cell_type": "code", "execution_count": 1, "id": "11dc12a7", "metadata": { "execution": { "iopub.execute_input": "2026-05-27T20:01:00.703144Z", "iopub.status.busy": "2026-05-27T20:01:00.702931Z", "iopub.status.idle": "2026-05-27T20:01:01.398253Z", "shell.execute_reply": "2026-05-27T20:01:01.397705Z" }, "papermill": { "duration": 0.698273, "end_time": "2026-05-27T20:01:01.399077+00:00", "exception": false, "start_time": "2026-05-27T20:01:00.700804+00:00", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "from palacetoolkit.mode_solver import WaveguideModeSolver\n", "from palacetoolkit.viz import view_mesh\n", "\n", "import importlib\n", "import inspect\n", "\n", "import gmsh\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import palacetoolkit.utils as ptk_utils\n", "\n", "importlib.reload(ptk_utils)\n", "view_fe_mesh_2d = ptk_utils.view_fe_mesh_2d\n", "view_fields_2d = ptk_utils.view_fields_2d\n", "write_and_finalize_gmsh = ptk_utils.write_and_finalize_gmsh" ] }, { "cell_type": "code", "execution_count": 2, "id": "5249965f", "metadata": { "execution": { "iopub.execute_input": "2026-05-27T20:01:01.405287Z", "iopub.status.busy": "2026-05-27T20:01:01.405029Z", "iopub.status.idle": "2026-05-27T20:01:01.408160Z", "shell.execute_reply": "2026-05-27T20:01:01.407688Z" }, "papermill": { "duration": 0.008402, "end_time": "2026-05-27T20:01:01.408821+00:00", "exception": false, "start_time": "2026-05-27T20:01:01.400419+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WaveguideModeSolver.__init__ signature:\n", "(self, mesh, order=1, mu_inv=1.0, eps=1.0, pec_bdr='all')\n", "\n", "PEC conductor support via boundary attributes: True\n", "The solver enforces PEC by essential DOF elimination on selected boundary attributes.\n" ] } ], "source": [ "sig = inspect.signature(WaveguideModeSolver.__init__)\n", "print(\"WaveguideModeSolver.__init__ signature:\")\n", "print(sig)\n", "print(\"\\nPEC conductor support via boundary attributes:\", \"pec_bdr\" in sig.parameters)\n", "print(\"The solver enforces PEC by essential DOF elimination on selected boundary attributes.\")" ] }, { "cell_type": "code", "execution_count": 3, "id": "2b6408f2", "metadata": { "execution": { "iopub.execute_input": "2026-05-27T20:01:01.412661Z", "iopub.status.busy": "2026-05-27T20:01:01.412505Z", "iopub.status.idle": "2026-05-27T20:01:01.420138Z", "shell.execute_reply": "2026-05-27T20:01:01.419697Z" }, "papermill": { "duration": 0.01015, "end_time": "2026-05-27T20:01:01.420559+00:00", "exception": false, "start_time": "2026-05-27T20:01:01.410409+00:00", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def make_microstrip_mesh(\n", " box_w=8.0,\n", " h_sub=1.0,\n", " h_air=3.0,\n", " strip_w=1.8,\n", " strip_t=0.06,\n", " lc_bulk=0.18,\n", " lc_strip=0.05,\n", " meshsize=1.0,\n", " filename=None,\n", "):\n", " gmsh.initialize()\n", " gmsh.option.setNumber(\"General.Verbosity\", 0)\n", " gmsh.model.add(\"microstrip_modes\")\n", "\n", " sub = gmsh.model.occ.addRectangle(-box_w / 2, -h_sub, 0, box_w, h_sub)\n", " air = gmsh.model.occ.addRectangle(-box_w / 2, 0.0, 0, box_w, h_air)\n", " strip = gmsh.model.occ.addRectangle(-strip_w / 2, 0.0, 0, strip_w, strip_t)\n", "\n", " _, outmap = gmsh.model.occ.fragment([(2, sub), (2, air), (2, strip)], [])\n", " strip_parts = list(outmap[2])\n", " gmsh.model.occ.remove(strip_parts, recursive=True)\n", " gmsh.model.occ.synchronize()\n", "\n", " all_surfs = [t for _, t in gmsh.model.getEntities(2)]\n", " substrate_surfs = []\n", " air_surfs = []\n", " for tag in all_surfs:\n", " _, cy, _ = gmsh.model.occ.getCenterOfMass(2, tag)\n", " if cy < -1e-9:\n", " substrate_surfs.append(tag)\n", " else:\n", " air_surfs.append(tag)\n", "\n", " if not substrate_surfs or not air_surfs:\n", " gmsh.finalize()\n", " raise RuntimeError(\"Failed to classify substrate/air surfaces for microstrip mesh\")\n", "\n", " gmsh.model.addPhysicalGroup(2, substrate_surfs, tag=1, name=\"substrate\")\n", " gmsh.model.addPhysicalGroup(2, air_surfs, tag=2, name=\"air\")\n", "\n", " bnd = gmsh.model.getBoundary([(2, t) for t in substrate_surfs + air_surfs], oriented=False, combined=False)\n", " edge_tags = sorted({abs(t) for _, t in bnd})\n", "\n", " strip_edges = []\n", " ground_edges = []\n", " open_edges = []\n", "\n", " for et in edge_tags:\n", " ex, ey, _ = gmsh.model.occ.getCenterOfMass(1, et)\n", " on_strip_x = abs(ex) <= strip_w / 2 + 1e-6\n", " on_strip_y = (-1e-6 <= ey <= strip_t + 1e-6)\n", " if on_strip_x and on_strip_y:\n", " strip_edges.append(et)\n", " continue\n", "\n", " # Ground plane is the lower boundary of the simulation box.\n", " if abs(ey + h_sub) <= 1e-6:\n", " ground_edges.append(et)\n", " else:\n", " open_edges.append(et)\n", "\n", " if ground_edges:\n", " gmsh.model.addPhysicalGroup(1, ground_edges, tag=1, name=\"ground_plane\")\n", " if strip_edges:\n", " gmsh.model.addPhysicalGroup(1, strip_edges, tag=2, name=\"strip_conductor\")\n", " if open_edges:\n", " gmsh.model.addPhysicalGroup(1, open_edges, tag=3, name=\"open_boundary\")\n", "\n", " if meshsize <= 0:\n", " gmsh.finalize()\n", " raise ValueError(\"meshsize must be positive\")\n", "\n", " lc_bulk_eff = lc_bulk * meshsize\n", " lc_strip_eff = lc_strip * meshsize\n", "\n", " # Use a distance-based field from all curves so refinement occurs\n", " # near any geometry boundary (PEC and domain boundaries).\n", " all_curves = sorted({t for _, t in gmsh.model.getEntities(1)})\n", " dist_field = gmsh.model.mesh.field.add(\"Distance\")\n", " gmsh.model.mesh.field.setNumbers(dist_field, \"CurvesList\", all_curves)\n", " gmsh.model.mesh.field.setNumber(dist_field, \"Sampling\", 200)\n", "\n", " threshold_field = gmsh.model.mesh.field.add(\"Threshold\")\n", " gmsh.model.mesh.field.setNumber(threshold_field, \"InField\", dist_field)\n", " gmsh.model.mesh.field.setNumber(threshold_field, \"SizeMin\", lc_strip_eff)\n", " gmsh.model.mesh.field.setNumber(threshold_field, \"SizeMax\", lc_bulk_eff)\n", " gmsh.model.mesh.field.setNumber(threshold_field, \"DistMin\", 0.0)\n", " gmsh.model.mesh.field.setNumber(threshold_field, \"DistMax\", 0.35 * h_sub)\n", "\n", " gmsh.model.mesh.field.setAsBackgroundMesh(threshold_field)\n", " gmsh.option.setNumber(\"Mesh.CharacteristicLengthFromPoints\", 0)\n", " gmsh.option.setNumber(\"Mesh.CharacteristicLengthFromCurvature\", 0)\n", " gmsh.option.setNumber(\"Mesh.CharacteristicLengthExtendFromBoundary\", 0)\n", " gmsh.option.setNumber(\"Mesh.CharacteristicLengthMin\", lc_strip_eff)\n", " gmsh.option.setNumber(\"Mesh.CharacteristicLengthMax\", lc_bulk_eff)\n", "\n", " gmsh.model.mesh.generate(2)\n", " return write_and_finalize_gmsh(filename, prefix=\"wg_microstrip_\")" ] }, { "cell_type": "code", "execution_count": 4, "id": "1f73ddb2", "metadata": { "execution": { "iopub.execute_input": "2026-05-27T20:01:01.423523Z", "iopub.status.busy": "2026-05-27T20:01:01.423383Z", "iopub.status.idle": "2026-05-27T20:01:01.426244Z", "shell.execute_reply": "2026-05-27T20:01:01.425735Z" }, "papermill": { "duration": 0.004855, "end_time": "2026-05-27T20:01:01.426595+00:00", "exception": false, "start_time": "2026-05-27T20:01:01.421740+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Reference phase window (air to substrate): 1.0000 < kn < 2.1909\n" ] } ], "source": [ "eps_sub = 4.8\n", "eps_air = 1.0\n", "mu_r = 1.0\n", "\n", "omega = 1.0\n", "kn_air = omega * np.sqrt(mu_r * eps_air)\n", "kn_sub = omega * np.sqrt(mu_r * eps_sub)\n", "print(f\"Reference phase window (air to substrate): {kn_air:.4f} < kn < {kn_sub:.4f}\")" ] }, { "cell_type": "code", "execution_count": 5, "id": "d84a7361", "metadata": { "execution": { "iopub.execute_input": "2026-05-27T20:01:01.429366Z", "iopub.status.busy": "2026-05-27T20:01:01.429229Z", "iopub.status.idle": "2026-05-27T20:01:17.994464Z", "shell.execute_reply": "2026-05-27T20:01:17.994054Z" }, "papermill": { "duration": 16.567713, "end_time": "2026-05-27T20:01:17.995440+00:00", "exception": false, "start_time": "2026-05-27T20:01:01.427727+00:00", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loading mesh file: /tmp/wg_microstrip_ftoylzts.msh\n", "Groups to render transparent: ['air_none', 'air_plastic_enclosure']\n", "\n", "Mesh loaded successfully with 2 cell blocks\n", "Found 5778 triangles total\n", "Physical group tags in mesh: {1: 'substrate', 2: 'air'}\n" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " FE spaces: ND dofs = 29424, H1 dofs = 12090, total = 41514\n", " Essential DOFs: ND = 452, H1 = 453, total = 905\n", " Solving eigenvalue problem (omega = 1, sigma = -5.28, size = 41514)...\n", " Found 8 modes:\n", " Mode 1: kn = +2.09668519e+00 -0.00000000e+00j <-- selected\n", " Mode 2: kn = +1.75594546e+00 -0.00000000e+00j\n", " Mode 3: kn = +1.62618335e+00 -0.00000000e+00j\n", " Mode 4: kn = +1.53006718e+00 -0.00000000e+00j\n", " Mode 5: kn = +1.11611961e+00 -0.00000000e+00j\n", " Mode 6: kn = +1.06782134e+00 -0.00000000e+00j\n", " Mode 7: kn = +8.56975748e-01 -0.00000000e+00j\n", " Mode 8: kn = +6.73340532e-01 -0.00000000e+00j\n", "Computed microstrip modes:\n", " Mode 1: kn= +2.096685 -0.000000j [bound/hybrid]\n", " Mode 2: kn= +1.755945 -0.000000j [bound/hybrid]\n", " Mode 3: kn= +1.626183 -0.000000j [bound/hybrid]\n", " Mode 4: kn= +1.530067 -0.000000j [bound/hybrid]\n", " Mode 5: kn= +1.116120 -0.000000j [bound/hybrid]\n", " Mode 6: kn= +1.067821 -0.000000j [bound/hybrid]\n", " Mode 7: kn= +0.856976 -0.000000j [radiative or box mode]\n", " Mode 8: kn= +0.673341 -0.000000j [radiative or box mode]\n" ] } ], "source": [ "mesh_file = make_microstrip_mesh(\n", " box_w=8.0,\n", " h_sub=1.0,\n", " h_air=3.0,\n", " strip_w=1.8,\n", " strip_t=0.06,\n", " lc_bulk=0.18,\n", " lc_strip=0.05,\n", " meshsize=1.0, # decrease for convergence checks (e.g. 0.7, 0.5)\n", ")\n", "view_mesh(mesh_file)\n", "\n", "mu_inv = {1: 1.0 / mu_r, 2: 1.0 / mu_r}\n", "eps = {1: eps_sub, 2: eps_air}\n", "\n", "# WaveguideModeSolver currently supports PEC marking via pec_bdr; it does not\n", "# provide an absorbing boundary-condition model.\n", "pec_bdr = [1, 2] # ground plane + strip conductor\n", "\n", "solver = WaveguideModeSolver(mesh_file, order=2, mu_inv=mu_inv, eps=eps, pec_bdr=pec_bdr)\n", "results = solver.solve(omega, num_modes=8, mode_idx=1)\n", "\n", "print(\"Computed microstrip modes:\")\n", "for i, kn in enumerate(results[\"kn\"], start=1):\n", " if kn_air < kn.real < kn_sub and abs(kn.imag) < 0.1 * abs(kn.real):\n", " mode_type = \"bound/hybrid\"\n", " elif abs(kn.imag) > 0.1 * abs(kn.real):\n", " mode_type = \"evanescent\"\n", " else:\n", " mode_type = \"radiative or box mode\"\n", " print(f\" Mode {i:2d}: kn={kn.real:+10.6f}{kn.imag:+10.6f}j [{mode_type}]\")" ] }, { "cell_type": "code", "execution_count": 6, "id": "306f552b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "\n", "MFEM Warning: 18 points were not found\n", " ... in function: virtual int mfem::Mesh::FindPoints(mfem::DenseMatrix&, mfem::Array&, mfem::Array&, bool, mfem::InverseElementTransformation*)\n", " ... in file: /__w/PyMFEM/PyMFEM/PyMFEM/external/mfem/mesh/mesh.cpp:13515\n", "\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "view_fields_2d(\n", " solver=solver,\n", " results=results,\n", " mesh_file=mesh_file,\n", " eps=eps,\n", " pec_bdr=pec_bdr,\n", " include_streamplot=True,\n", " streamplot_density=1.2,\n", " streamplot_show_arrows=True,\n", " streamplot_normalize=True,\n", " streamplot_seed_from_field=True,\n", " streamplot_seed_frac=0.1,\n", " streamplot_seed_stride=2,\n", " streamplot_mask_weak=True,\n", " streamplot_min_frac=0.1,\n", " num_modes=1,\n", " nx=80,\n", " ny=60,\n", " cmap=\"hot\",\n", " title=\"Microstrip First Modes (Boxed Cross-Section)\",\n", ")" ] }, { "cell_type": "markdown", "id": "7cbf38ee", "metadata": {}, "source": [ "## Validation vs. Hammerstad-Jensen\n", "\n", "To validate loss prediction, we compare **transmission magnitude** estimated from solver-derived effective permittivity against a Hammerstad-Jensen-based dielectric-loss model.\n", "\n", "Validation sweep setup (kept comfortably inside commonly used validity limits):\n", "- Relative permittivity: $2.2 \\le \\varepsilon_r \\le 6.15$\n", "- Width ratio: $0.8 \\le w/h \\le 2.5$\n", "- Thin strip: $t/h = 0.04$\n", "- Low-loss dielectric: $\\tan\\delta = 0.002$\n", "\n", "For each case, we compute:\n", "- Solver-derived: run eigenmode with real $\\varepsilon_r$, infer $\\varepsilon_{\\mathrm{eff,solver}}=(\\Re\\{k_n\\}/\\omega)^2/\\mu_r$, then use low-loss dielectric estimate for $\\alpha$\n", "- HJ-based reference: $|S_{21}|_{\\mathrm{HJ}} \\approx e^{-\\alpha_{\\mathrm{HJ}}L}$ using $\\varepsilon_{\\mathrm{eff,HJ}}$ and a quasi-static dielectric filling factor\n", "- Impedance comparison: two numerical estimates are used: (i) contour-based $Z_{0,VI}=|V/I|$ and (ii) quasi-static energy/capacitance estimate $Z_{0,C}$, both compared to analytic $Z_{0,\\mathrm{HJ}}$\n", "\n", "Low-loss approximation used in this cell:\n", "- For a weakly lossy dielectric, write the propagation constant as $\\gamma = \\alpha + j\\beta$ and use $\\varepsilon = \\varepsilon'(1-j\\tan\\delta_{\\mathrm{eff}})$ with $\\tan\\delta_{\\mathrm{eff}} \\ll 1$.\n", "- First-order expansion gives $\\alpha \\approx \\tfrac{\\beta}{2}\\tan\\delta_{\\mathrm{eff}}$.\n", "- In quasi-TEM form, $\\beta \\approx \\omega\\sqrt{\\mu_r\\varepsilon_{\\mathrm{eff}}}$.\n", "- We estimate $\\tan\\delta_{\\mathrm{eff}} = q\\,\\tan\\delta$ with filling factor $q \\approx (\\varepsilon_{\\mathrm{eff}}-1)/(\\varepsilon_r-1)$.\n", "- Therefore, $\\alpha \\approx \\tfrac{1}{2}\\,\\omega\\sqrt{\\mu_r\\varepsilon_{\\mathrm{eff}}}\\,q\\tan\\delta$ and $|S_{21}| \\approx e^{-\\alpha L}$.\n", "\n", "Note: this eigenmode setup uses PEC conductors and real-valued material tensors, so this section validates **dielectric loss contribution** (not conductor loss)." ] }, { "cell_type": "code", "execution_count": null, "id": "02090b66", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " FE spaces: ND dofs = 29582, H1 dofs = 12128, total = 41710\n", " Essential DOFs: ND = 368, H1 = 369, total = 737\n", " Solving eigenvalue problem (omega = 1, sigma = -2.42, size = 41710)...\n", " Found 8 modes:\n", " Mode 1: kn = +1.38392529e+00 -0.00000000e+00j <-- selected\n", " Mode 2: kn = +1.07672619e+00 -0.00000000e+00j\n", " Mode 3: kn = +1.06539697e+00 -0.00000000e+00j\n", " Mode 4: kn = +8.62195048e-01 -0.00000000e+00j\n", " Mode 5: kn = +7.70162648e-01 -0.00000000e+00j\n", " Mode 6: kn = +4.62361581e-01 -0.00000000e+00j\n", " Mode 7: kn = +6.17026492e-02 +1.07924361e+00j\n", " Mode 8: kn = +6.17026492e-02 -1.07924361e+00j\n", "\n", "\n", "MFEM Warning: 12 points were not found\n", " ... in function: virtual int mfem::Mesh::FindPoints(mfem::DenseMatrix&, mfem::Array&, mfem::Array&, bool, mfem::InverseElementTransformation*)\n", " ... in file: /__w/PyMFEM/PyMFEM/PyMFEM/external/mfem/mesh/mesh.cpp:13515\n", "\n", " FE spaces: ND dofs = 29474, H1 dofs = 12104, total = 41578\n", " Essential DOFs: ND = 432, H1 = 433, total = 865\n" ] } ], "source": [ "def hammerstad_jensen_eps_eff(er, u):\n", " if u <= 0:\n", " raise ValueError(\"u = w/h must be positive\")\n", " a = 1.0 + (1.0 / 49.0) * np.log((u**4 + (u / 52.0) ** 2) / (u**4 + 0.432))\n", " a += (1.0 / 18.7) * np.log(1.0 + u / 18.1)\n", " b = 0.564 * ((er - 0.9) / (er + 3.0)) ** 0.053\n", " return 0.5 * (er + 1.0) + 0.5 * (er - 1.0) * (1.0 + 10.0 / u) ** (-a * b)\n", "\n", "\n", "def hj_dielectric_alpha(omega, er, eeff, tand):\n", " # Quasi-static electric energy filling in substrate.\n", " q = (eeff - 1.0) / max(er - 1.0, 1e-12)\n", " tand_eff = q * tand\n", " beta_hj = omega * np.sqrt(mu_r * eeff)\n", " # Low-loss approximation for attenuation constant.\n", " return 0.5 * beta_hj * tand_eff\n", "\n", "\n", "def hammerstad_jensen_z0(er, u):\n", " eeff = hammerstad_jensen_eps_eff(er, u)\n", " f = 6.0 + (2.0 * np.pi - 6.0) * np.exp(-((30.666 / u) ** 0.7528))\n", " return (60.0 / np.sqrt(eeff)) * np.log(f / u + np.sqrt(1.0 + (2.0 / u) ** 2))\n", "\n", "\n", "def pick_guided_mode(kn_vals, omega, mu_r, eps_air, eps_sub):\n", " k_air = omega * np.sqrt(mu_r * eps_air)\n", " k_sub = omega * np.sqrt(mu_r * eps_sub)\n", " guided = [\n", " kn for kn in kn_vals\n", " if (k_air * 1.001) < kn.real < (k_sub * 0.999) and abs(kn.imag) < 0.05 * max(abs(kn.real), 1e-12)\n", " ]\n", " if guided:\n", " return sorted(guided, key=lambda z: z.real)[-1]\n", " return sorted(kn_vals, key=lambda z: abs(z.imag))[0]\n", "\n", "\n", "def _mode_vectors_from_kn(results, kn_target, solver):\n", " idx = int(np.argmin(np.abs(results[\"kn\"] - kn_target)))\n", " e_vec = results[\"eigenvectors_raw\"][:, idx]\n", " et = e_vec[:solver.nd_size]\n", " en = e_vec[solver.nd_size:]\n", " en_phys = en / (1j * kn_target)\n", " return et, en_phys\n", "\n", "\n", "def _bilinear_sample(X, Y, F, xq, yq):\n", " xs = X[0, :]\n", " ys = Y[:, 0]\n", " if xq < xs[0] or xq > xs[-1] or yq < ys[0] or yq > ys[-1]:\n", " return np.nan + 1j * np.nan\n", " i = int(np.clip(np.searchsorted(xs, xq) - 1, 0, len(xs) - 2))\n", " j = int(np.clip(np.searchsorted(ys, yq) - 1, 0, len(ys) - 2))\n", " x1, x2 = xs[i], xs[i + 1]\n", " y1, y2 = ys[j], ys[j + 1]\n", " tx = 0.0 if x2 == x1 else (xq - x1) / (x2 - x1)\n", " ty = 0.0 if y2 == y1 else (yq - y1) / (y2 - y1)\n", " f11 = F[j, i]\n", " f21 = F[j, i + 1]\n", " f12 = F[j + 1, i]\n", " f22 = F[j + 1, i + 1]\n", " return (\n", " (1 - tx) * (1 - ty) * f11\n", " + tx * (1 - ty) * f21\n", " + (1 - tx) * ty * f12\n", " + tx * ty * f22\n", " )\n", "\n", "\n", "def estimate_vi_impedance(X, Y, Ex, Ey, Ez, kn_mode, omega, mu_r, strip_w, strip_t, h_sub):\n", " # Voltage: line integral of Ey from ground toward strip centerline.\n", " x0 = 0.0\n", " y0 = -h_sub + 0.02 * h_sub\n", " y1 = -0.02 * h_sub\n", " ys = np.linspace(y0, y1, 400)\n", " ey_line = np.array([_bilinear_sample(X, Y, Ey, x0, yy) for yy in ys])\n", " ey_line = np.nan_to_num(ey_line, nan=0.0, posinf=0.0, neginf=0.0)\n", " V = np.trapezoid(ey_line, ys)\n", "\n", " # Reconstruct Ht from curl(E) relations for exp(-j kn z) convention.\n", " dEz_dy, dEz_dx = np.gradient(Ez, Y[:, 0], X[0, :], edge_order=2)\n", " Hx = (1j / (omega * mu_r)) * dEz_dy - (kn_mode / (omega * mu_r)) * Ey\n", " Hy = (kn_mode / (omega * mu_r)) * Ex - (1j / (omega * mu_r)) * dEz_dx\n", "\n", " # Current: Ampere loop integral around strip on a small rectangular contour.\n", " dx = float(np.mean(np.diff(X[0, :])))\n", " dy = float(np.mean(np.diff(Y[:, 0])))\n", " pad = max(2.0 * max(dx, dy), 0.04 * h_sub)\n", " xl = -strip_w / 2 - pad\n", " xr = +strip_w / 2 + pad\n", " yb = -pad\n", " yt = strip_t + pad\n", " nseg = 300\n", "\n", " xt = np.linspace(xl, xr, nseg)\n", " xb = np.linspace(xr, xl, nseg)\n", " yr = np.linspace(yt, yb, nseg)\n", " yl = np.linspace(yb, yt, nseg)\n", "\n", " top_s = np.nan_to_num(np.array([_bilinear_sample(X, Y, Hx, xx, yt) for xx in xt]), nan=0.0, posinf=0.0, neginf=0.0)\n", " right_s = np.nan_to_num(np.array([_bilinear_sample(X, Y, Hy, xr, yy) for yy in yr]), nan=0.0, posinf=0.0, neginf=0.0)\n", " bot_s = np.nan_to_num(np.array([_bilinear_sample(X, Y, Hx, xx, yb) for xx in xb]), nan=0.0, posinf=0.0, neginf=0.0)\n", " left_s = np.nan_to_num(np.array([_bilinear_sample(X, Y, Hy, xl, yy) for yy in yl]), nan=0.0, posinf=0.0, neginf=0.0)\n", " top = np.trapezoid(top_s, xt)\n", " right = np.trapezoid(right_s, yr)\n", " bot = np.trapezoid(bot_s, xb)\n", " left = np.trapezoid(left_s, yl)\n", " I = top + right + bot + left\n", "\n", " z0_vi_norm = abs(V) / max(abs(I), 1e-14)\n", " return z0_vi_norm, abs(V)\n", "\n", "\n", "def estimate_capacitance_impedance(X, Y, Ex, Ey, Ez, er, eps_eff_solver, vmag, eta0):\n", " eps_r = np.where(Y < 0.0, er, 1.0)\n", " e2 = np.abs(Ex) ** 2 + np.abs(Ey) ** 2 + np.abs(Ez) ** 2\n", " e2 = np.nan_to_num(e2, nan=0.0, posinf=0.0, neginf=0.0)\n", " we_density = 0.25 * eps_r * e2\n", " we = np.trapezoid(np.trapezoid(we_density, X[0, :], axis=1), Y[:, 0])\n", " vmag = float(np.nan_to_num(vmag, nan=0.0, posinf=0.0, neginf=0.0))\n", " c_norm = 4.0 * we / max(vmag**2, 1e-14)\n", " z0_c = eta0 * np.sqrt(max(eps_eff_solver, 1e-12)) / max(c_norm, 1e-14)\n", " return z0_c\n", "\n", "\n", "validation_cases = [\n", " {\"eps_sub\": 2.2, \"w_over_h\": 0.8},\n", " {\"eps_sub\": 2.2, \"w_over_h\": 1.6},\n", " {\"eps_sub\": 4.4, \"w_over_h\": 1.0},\n", " {\"eps_sub\": 4.4, \"w_over_h\": 2.0},\n", " {\"eps_sub\": 6.15, \"w_over_h\": 1.2},\n", " {\"eps_sub\": 6.15, \"w_over_h\": 2.5},\n", "]\n", "\n", "h_sub_val = 1.0\n", "h_air_val = 3.0\n", "box_w_val = 8.0\n", "strip_t_val = 0.04 * h_sub_val # t/h = 0.04\n", "tand_sub = 0.002\n", "line_length = 40.0 * h_sub_val\n", "eta0 = 376.730313668\n", "meshsize_val = 1.0\n", "\n", "rows = []\n", "for case in validation_cases:\n", " er = case[\"eps_sub\"]\n", " u = case[\"w_over_h\"]\n", " strip_w = u * h_sub_val\n", "\n", " mesh_case = make_microstrip_mesh(\n", " box_w=box_w_val,\n", " h_sub=h_sub_val,\n", " h_air=h_air_val,\n", " strip_w=strip_w,\n", " strip_t=strip_t_val,\n", " lc_bulk=0.18,\n", " lc_strip=0.05,\n", " meshsize=meshsize_val,\n", " )\n", "\n", " eps_case = {1: er, 2: eps_air}\n", " solver_case = WaveguideModeSolver(mesh_case, order=2, mu_inv=mu_inv, eps=eps_case, pec_bdr=pec_bdr)\n", " res_case = solver_case.solve(omega, num_modes=8, mode_idx=1)\n", "\n", " kn_pick = pick_guided_mode(res_case[\"kn\"], omega, mu_r, eps_air, er)\n", " eps_eff_solver = (kn_pick.real / omega) ** 2 / mu_r\n", " alpha_solver = hj_dielectric_alpha(omega, er, eps_eff_solver, tand_sub)\n", " s21_solver = np.exp(-alpha_solver * line_length)\n", " et_mode, en_mode = _mode_vectors_from_kn(res_case, kn_pick, solver_case)\n", " Xg, Yg, Exg, Eyg, Ezg = solver_case.get_field_on_grid(et_mode, en_mode, nx=120, ny=90)\n", "\n", " eps_eff_hj = hammerstad_jensen_eps_eff(er, u)\n", " alpha_hj = hj_dielectric_alpha(omega, er, eps_eff_hj, tand_sub)\n", " s21_hj = np.exp(-alpha_hj * line_length)\n", " z0_vi_norm, vmag = estimate_vi_impedance(Xg, Yg, Exg, Eyg, Ezg, kn_pick, omega, mu_r, strip_w, strip_t_val, h_sub_val)\n", " z0_vi = eta0 * z0_vi_norm\n", " z0_cap = estimate_capacitance_impedance(Xg, Yg, Exg, Eyg, Ezg, er, eps_eff_solver, vmag, eta0)\n", " z0_hj = hammerstad_jensen_z0(er, u)\n", "\n", " eps_eff_err_pct = 100.0 * (eps_eff_solver - eps_eff_hj) / max(eps_eff_hj, 1e-12)\n", " err_pct = 100.0 * (s21_solver - s21_hj) / max(s21_hj, 1e-12)\n", " z0_vi_err_pct = 100.0 * (z0_vi - z0_hj) / max(z0_hj, 1e-12)\n", " z0_cap_err_pct = 100.0 * (z0_cap - z0_hj) / max(z0_hj, 1e-12)\n", " il_solver_db = -20.0 * np.log10(max(s21_solver, 1e-14))\n", " il_hj_db = -20.0 * np.log10(max(s21_hj, 1e-14))\n", " rows.append((er, u, eps_eff_solver, eps_eff_hj, eps_eff_err_pct, s21_solver, s21_hj, err_pct, z0_vi, z0_cap, z0_hj, z0_vi_err_pct, z0_cap_err_pct, il_solver_db, il_hj_db))" ] }, { "cell_type": "code", "execution_count": 10, "id": "d733a2b3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Validation against Hammerstad-Jensen (dielectric loss via |S21|):\n", "tan(delta)=0.0020, normalized line length L=40.00\n", " er w/h eps_eff_num eps_eff_HJ eps_err[%] |S21|_num |S21|_HJ S21_err[%] Z0_VI[ohm] Z0_C[ohm] Z0_HJ[ohm] Z0_VI_err[%] Z0_C_err[%] IL_num[dB] IL_HJ[dB]\n", " 2.20 0.80 1.915249 1.756003 9.069 0.958658 0.967158 -0.879 125.838 nan 105.120 19.709 nan 0.3667 0.2901\n", " 2.20 1.60 1.994345 1.811757 10.078 0.954271 0.964234 -1.033 91.891 nan 74.765 22.906 nan 0.4066 0.3164\n", " 4.40 1.00 3.847855 3.166083 21.534 0.936391 0.955669 -2.017 97.442 nan 71.100 37.050 nan 0.5709 0.3939\n", " 4.40 2.00 4.054514 3.340487 21.375 0.930197 0.950919 -2.179 66.819 nan 48.745 37.080 nan 0.6285 0.4371\n", " 6.15 1.20 5.520567 4.333185 27.402 0.920814 0.947535 -2.820 80.773 nan 55.855 44.612 nan 0.7166 0.4681\n", " 6.15 2.50 5.805383 4.635310 25.243 0.913997 0.941021 -2.872 51.880 nan 36.316 42.856 nan 0.7811 0.5280\n", "\n", "Mean |rel err| in eps_eff: 19.117%\n", "Max |rel err| in eps_eff: 27.402%\n", "Mean |rel err| in |S21|: 1.967%\n", "Max |rel err| in |S21|: 2.872%\n", "Mean |rel err| in Z0 (V/I): 34.035%\n", "Max |rel err| in Z0 (V/I): 44.612%\n", "Mean |rel err| in Z0 (C): nan%\n", "Max |rel err| in Z0 (C): nan%\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "rows = sorted(rows, key=lambda r: (r[0], r[1]))\n", "case_labels = [f\"er={r[0]:.2f}, w/h={r[1]:.2f}\" for r in rows]\n", "x = np.arange(len(rows))\n", "eps_eff_solver_vals = [r[2] for r in rows]\n", "eps_eff_hj_vals = [r[3] for r in rows]\n", "s21_solver_vals = [r[5] for r in rows]\n", "s21_hj_vals = [r[6] for r in rows]\n", "z0_vi_vals = [r[8] for r in rows]\n", "z0_cap_vals = [r[9] for r in rows]\n", "z0_hj_vals = [r[10] for r in rows]\n", "il_solver_vals = [r[13] for r in rows]\n", "il_hj_vals = [r[14] for r in rows]\n", "\n", "print(\"Validation against Hammerstad-Jensen (dielectric loss via |S21|):\")\n", "print(f\"tan(delta)={tand_sub:.4f}, normalized line length L={line_length:.2f}\")\n", "print(\" er w/h eps_eff_num eps_eff_HJ eps_err[%] |S21|_num |S21|_HJ S21_err[%] Z0_VI[ohm] Z0_C[ohm] Z0_HJ[ohm] Z0_VI_err[%] Z0_C_err[%] IL_num[dB] IL_HJ[dB]\")\n", "for er, u, ee_num, ee_hj, ee_err, s21_s, s21_hj, e_pct, z0_vi_i, z0_c_i, z0_hj_i, z0_e1, z0_e2, il_s, il_hj in rows:\n", " print(f\"{er:5.2f} {u:4.2f} {ee_num:12.6f} {ee_hj:12.6f} {ee_err:10.3f} {s21_s:11.6f} {s21_hj:10.6f} {e_pct:11.3f} {z0_vi_i:11.3f} {z0_c_i:10.3f} {z0_hj_i:11.3f} {z0_e1:13.3f} {z0_e2:11.3f} {il_s:12.4f} {il_hj:11.4f}\")\n", "\n", "abs_eps_err = [abs(r[4]) for r in rows]\n", "abs_s21_err = [abs(r[7]) for r in rows]\n", "abs_z0_vi_err = [abs(r[11]) for r in rows]\n", "abs_z0_cap_err = [abs(r[12]) for r in rows]\n", "print(f\"\\nMean |rel err| in eps_eff: {np.mean(abs_eps_err):.3f}%\")\n", "print(f\"Max |rel err| in eps_eff: {np.max(abs_eps_err):.3f}%\")\n", "print(f\"Mean |rel err| in |S21|: {np.mean(abs_s21_err):.3f}%\")\n", "print(f\"Max |rel err| in |S21|: {np.max(abs_s21_err):.3f}%\")\n", "print(f\"Mean |rel err| in Z0 (V/I): {np.mean(abs_z0_vi_err):.3f}%\")\n", "print(f\"Max |rel err| in Z0 (V/I): {np.max(abs_z0_vi_err):.3f}%\")\n", "print(f\"Mean |rel err| in Z0 (C): {np.mean(abs_z0_cap_err):.3f}%\")\n", "print(f\"Max |rel err| in Z0 (C): {np.max(abs_z0_cap_err):.3f}%\")\n", "\n", "fig, axes = plt.subplots(4, 1, figsize=(10, 14), sharex=True)\n", "axes[0].plot(x, eps_eff_solver_vals, \"o-\", lw=1.8, label=\"Numerical (solver-derived)\")\n", "axes[0].plot(x, eps_eff_hj_vals, \"s--\", lw=1.8, label=\"Analytic (Hammerstad-Jensen)\")\n", "axes[0].set_ylabel(\"Effective Permittivity\")\n", "axes[0].set_title(\"Validation: Numerical vs Analytic\")\n", "axes[0].grid(True, alpha=0.3)\n", "axes[0].legend()\n", "\n", "axes[1].plot(x, s21_solver_vals, \"o-\", lw=1.8, label=\"Numerical (solver-derived)\")\n", "axes[1].plot(x, s21_hj_vals, \"s--\", lw=1.8, label=\"Analytic (Hammerstad-Jensen)\")\n", "axes[1].set_ylabel(\"|S21|\")\n", "axes[1].grid(True, alpha=0.3)\n", "axes[1].legend()\n", "\n", "axes[2].plot(x, z0_vi_vals, \"o-\", lw=1.8, label=\"Numerical V/I\")\n", "axes[2].plot(x, z0_cap_vals, \"d-\", lw=1.9, label=\"Numerical C-method\")\n", "axes[2].plot(x, z0_hj_vals, \"s--\", lw=1.8, label=\"Analytic (Hammerstad-Jensen)\")\n", "axes[2].set_ylabel(\"Z0 [ohm]\")\n", "axes[2].grid(True, alpha=0.3)\n", "axes[2].legend()\n", "\n", "axes[3].plot(x, il_solver_vals, \"o-\", lw=1.8, label=\"Numerical (solver-derived)\")\n", "axes[3].plot(x, il_hj_vals, \"s--\", lw=1.8, label=\"Analytic (Hammerstad-Jensen)\")\n", "axes[3].set_ylabel(\"Insertion Loss [dB]\")\n", "axes[3].set_xlabel(\"Validation case\")\n", "axes[3].grid(True, alpha=0.3)\n", "axes[3].legend()\n", "\n", "axes[3].set_xticks(x)\n", "axes[3].set_xticklabels(case_labels, rotation=25, ha=\"right\")\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 12, "id": "f3512fcf", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[np.float64(125.83823007021324), np.float64(91.89052781525307), np.float64(97.44207221663675), np.float64(66.81916521950247), np.float64(80.77316329572062), np.float64(51.87959650985845)]\n", "[np.float64(nan), np.float64(nan), np.float64(nan), np.float64(nan), np.float64(nan), np.float64(nan)]\n" ] } ], "source": [ "print(z0_vi_vals)\n", "print(z0_cap_vals)" ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "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": "3.12.3" }, "papermill": { "default_parameters": {}, "duration": 20.664912, "end_time": "2026-05-27T20:01:20.669108+00:00", "environment_variables": {}, "exception": null, "input_path": "docs/examples/microstrip_modes.ipynb", "output_path": "docs/examples/microstrip_modes.ipynb", "parameters": {}, "start_time": "2026-05-27T20:01:00.004196+00:00", "version": "2.7.0" } }, "nbformat": 4, "nbformat_minor": 5 }