{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3a3413e6",
   "metadata": {},
   "source": [
    "# Case 14 - Differentially heated square cavity (de Vahl Davis 1983)\n",
    "\n",
    "Validation of the scalar-transport **Boussinesq buoyancy** path against the\n",
    "classic de Vahl Davis (1983) natural-convection benchmark.\n",
    "\n",
    "A square cavity (side $L = 128$) has two opposing vertical walls held at fixed\n",
    "scalar values - hot west ($\\phi = 1$) and cold east ($\\phi = 0$) - and two\n",
    "adiabatic horizontal walls. The scalar `temperature` couples back onto the\n",
    "fluid through the Boussinesq body force\n",
    "\n",
    "$$ \\mathbf{F} = -\\rho_0\\,\\beta\\,(\\phi - \\phi_\\text{ref})\\,\\mathbf{g}, $$\n",
    "\n",
    "with gravity along $-y$, so a hot parcel ($\\phi > \\phi_\\text{ref}$) feels an\n",
    "upward force. The resulting buoyant recirculation is compared to the benchmark\n",
    "across three Rayleigh numbers.\n",
    "\n",
    "## Ra / Pr mapping\n",
    "\n",
    "Fixing the buoyant velocity scale $U = \\sqrt{g\\,\\beta\\,\\Delta T\\,L}$ and the\n",
    "cavity side $L$ (with $\\Delta T = 1$, $\\text{Pr} = 0.71$):\n",
    "\n",
    "$$ \\text{Ra} = \\frac{g\\,\\beta\\,\\Delta T\\,L^3}{\\nu\\,D}, \\quad \\text{Pr} = \\frac{\\nu}{D}, \\quad \\nu = U L \\sqrt{\\text{Pr}/\\text{Ra}}, \\quad D = \\nu/\\text{Pr}. $$\n",
    "\n",
    "$\\beta = U^2/(\\Delta T\\,L)$ is identical for all three runs; only $\\nu$ (fluid\n",
    "$\\tau$) and $D$ (scalar diffusivity) change with Ra. The thermal diffusivity\n",
    "$\\alpha = D$ is used to nondimensionalise the velocities ($u^\\* = u\\,L/\\alpha$).\n",
    "\n",
    "## Acceptance criteria\n",
    "\n",
    "Against `comparison/Differentially_heated_cavity/de_vahl_davis_1983.csv`:\n",
    "\n",
    "- **Nu_avg** (hot-wall average Nusselt number) within **3%** for all Ra.\n",
    "- **Velocity extrema** ($u_\\max$, $v_\\max$) within **5%**.\n",
    "\n",
    "Reference: de Vahl Davis, G. (1983). *Natural convection of air in a square\n",
    "cavity: a bench-mark numerical solution.* Int. J. Numer. Methods Fluids\n",
    "3(3):249-264."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c04aa780",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:43:59.282041Z",
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     "shell.execute_reply": "2026-06-29T17:44:00.340769Z"
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   },
   "outputs": [],
   "source": [
    "import pathlib\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pyvista as pv\n",
    "\n",
    "import nassu.viz as common\n",
    "from nassu.cfg.model import ConfigScheme\n",
    "\n",
    "common.use_style()\n",
    "pv.OFF_SCREEN = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "96441e6e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:00.342379Z",
     "iopub.status.busy": "2026-06-29T17:44:00.342233Z",
     "iopub.status.idle": "2026-06-29T17:44:00.377669Z",
     "shell.execute_reply": "2026-06-29T17:44:00.377407Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+03 (#0): D=0.48038, xdmf=default.volume.default.inst.xdmf"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+04 (#1): D=0.15191, xdmf=default.volume.default.inst.xdmf"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+05 (#2): D=0.04804, xdmf=default.volume.default.inst.xdmf"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "def _find_project_root() -> pathlib.Path:\n",
    "    here = pathlib.Path.cwd().resolve()\n",
    "    for cand in [here, *here.parents]:\n",
    "        if (cand / \"pyproject.toml\").exists() and (cand / \"nassu\").is_dir():\n",
    "            return cand\n",
    "    raise RuntimeError(f\"Could not locate Nassu project root upward from {here}\")\n",
    "\n",
    "\n",
    "project_root = _find_project_root()\n",
    "case_path = (\n",
    "    project_root\n",
    "    / \"validation/thermal/01_differentially_heated_cavity/01_differentially_heated_cavity.nassu.yaml\"\n",
    ")\n",
    "comparison_csv = (\n",
    "    project_root\n",
    "    / \"validation/thermal/01_differentially_heated_cavity/reference/de_vahl_davis_1983.csv\"\n",
    ")\n",
    "\n",
    "# Cavity geometry (lattice units), shared by all three Ra runs.\n",
    "L = 128.0\n",
    "DT = 1.0  # hot - cold scalar difference\n",
    "\n",
    "# The three Ra variants are unrolled from one block; key them by Ra using the\n",
    "# unroll order (1e3, 1e4, 1e5) so the labels line up with the benchmark table.\n",
    "RA_BY_SIM_ID = {0: 1e3, 1: 1e4, 2: 1e5}\n",
    "\n",
    "all_cfgs = ConfigScheme.sim_cfgs_from_file_dct(str(case_path))\n",
    "\n",
    "sims = {}\n",
    "for (name, sim_id), cfg in all_cfgs.items():\n",
    "    ra = RA_BY_SIM_ID[sim_id]\n",
    "    scalar = cfg.models.scalar_transports[\"temperature\"]\n",
    "    diffusivity = float(scalar.adv_diff_equation.D)  # alpha = D (Pr = nu / D)\n",
    "    xdmf_path = pathlib.Path(cfg.output.exports[\"default\"].volumes[\"default\"].inst.xdmf_filename)\n",
    "    if not xdmf_path.is_absolute():\n",
    "        xdmf_path = (project_root / xdmf_path).resolve()\n",
    "    if not xdmf_path.exists():\n",
    "        raise FileNotFoundError(\n",
    "            f\"No instantaneous XDMF for Ra={ra:.0e} (#{sim_id}) at {xdmf_path}.\\n\"\n",
    "            \"Run the case on GPU first: `uv run nassu run \"\n",
    "            \"validation/thermal/01_differentially_heated_cavity/01_differentially_heated_cavity.nassu.yaml`\"\n",
    "        )\n",
    "    reader = pv.get_reader(str(xdmf_path))\n",
    "    sims[ra] = {\"cfg\": cfg, \"reader\": reader, \"D\": diffusivity}\n",
    "    print(f\"Ra={ra:.0e} (#{sim_id}): D={diffusivity:.5f}, xdmf={xdmf_path.name}\")\n",
    "\n",
    "ra_values = sorted(sims.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2d34e3a",
   "metadata": {},
   "source": [
    "## Load the steady-state field\n",
    "\n",
    "Each run exports a handful of late-time snapshots; we take the **last** one as\n",
    "the steady state. The Nassu XDMF is a block-structured `MultiBlock` of\n",
    "cell-centred macros, so we combine the blocks and read the exact cell-centre\n",
    "values straight onto the regular $128\\times128$ lattice at the cavity mid-span\n",
    "($z$ midpoint). Reading the cells directly (rather than interpolating through a\n",
    "point-data probe) preserves the steep near-wall scalar gradient that sets the\n",
    "hot-wall Nusselt number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f3de9299",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:00.378598Z",
     "iopub.status.busy": "2026-06-29T17:44:00.378516Z",
     "iopub.status.idle": "2026-06-29T17:44:00.449679Z",
     "shell.execute_reply": "2026-06-29T17:44:00.449371Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+03: loaded 128x128 steady grid"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+04: loaded 128x128 steady grid"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+05: loaded 128x128 steady grid"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "def load_steady_grid(reader: pv.BaseReader, n: int = 128) -> dict[str, np.ndarray]:\n",
    "    \"\"\"Read the last exported step onto an (n x n) cell-centred grid at mid-span.\n",
    "\n",
    "    The Nassu XDMF is a block-structured ``MultiBlock`` of cell-centred macros.\n",
    "    We combine the blocks and read the exact cell-centre values onto the regular\n",
    "    (n x n) lattice at the central z layer - no interpolation, so the steep\n",
    "    near-wall scalar gradient that sets the Nusselt number is preserved. (An\n",
    "    earlier ``cell_data_to_point_data().sample()`` round trip smeared that\n",
    "    gradient and biased Nu low by ~35%.)\n",
    "\n",
    "    Returns a dict of (n, n) arrays indexed [iy, ix] for phi, ux, uy plus the\n",
    "    1-D cell-centre coordinate arrays xs, ys (both in [0, L]).\n",
    "    \"\"\"\n",
    "    reader.set_active_time_value(max(reader.time_values))\n",
    "    grid = reader.read().combine()\n",
    "    centres = np.asarray(grid.cell_centers().points)\n",
    "\n",
    "    # Mid-span z layer (thin periodic slab): pick the central cell layer.\n",
    "    z_layers = np.unique(centres[:, 2])\n",
    "    in_layer = centres[:, 2] == z_layers[len(z_layers) // 2]\n",
    "\n",
    "    # Cell centres sit at (i + 0.5); map straight to integer lattice indices.\n",
    "    ix = np.rint(centres[:, 0] - 0.5).astype(int)\n",
    "    iy = np.rint(centres[:, 1] - 0.5).astype(int)\n",
    "\n",
    "    out = {\"xs\": np.arange(n) + 0.5, \"ys\": np.arange(n) + 0.5}\n",
    "    for key in (\"temperature_phi\", \"ux\", \"uy\"):\n",
    "        field = np.full((n, n), np.nan)\n",
    "        values = np.asarray(grid.cell_data[key], dtype=float)\n",
    "        field[iy[in_layer], ix[in_layer]] = values[in_layer]  # [iy, ix]\n",
    "        if np.isnan(field).any():\n",
    "            raise ValueError(f\"Missing {key} cells when mapping onto the {n}x{n} grid\")\n",
    "        out[key] = field\n",
    "    return out\n",
    "\n",
    "\n",
    "for ra in ra_values:\n",
    "    sims[ra][\"grid\"] = load_steady_grid(sims[ra][\"reader\"], n=int(L))\n",
    "    print(f\"Ra={ra:.0e}: loaded {int(L)}x{int(L)} steady grid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cbfe9ec",
   "metadata": {},
   "source": [
    "## Diagnostics\n",
    "\n",
    "- **Hot-wall Nusselt number**: $\\text{Nu}(y) = \\dfrac{L}{\\Delta T}\\left.\\dfrac{\\partial\\phi}{\\partial x}\\right|_{x=0}$,\n",
    "  normalised so pure conduction gives $\\text{Nu} = 1$. The local wall gradient is\n",
    "  estimated with a one-sided second-order difference from the first three cell\n",
    "  columns; $\\text{Nu}_\\text{avg}$ is its average over the wall height.\n",
    "- **Velocity extrema**: $u_\\max$ on the vertical mid-plane ($x = L/2$) and\n",
    "  $v_\\max$ on the horizontal mid-plane ($y = L/2$), nondimensionalised by\n",
    "  $\\alpha/L = D/L$ ($u^\\* = u_\\text{lattice}\\,L/D$), with their locations\n",
    "  normalised by $L$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8617d1ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:00.450494Z",
     "iopub.status.busy": "2026-06-29T17:44:00.450422Z",
     "iopub.status.idle": "2026-06-29T17:44:00.455965Z",
     "shell.execute_reply": "2026-06-29T17:44:00.455701Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+03: "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Nu_avg': 1.1227, 'u_max': 3.6364, 'y_umax': 0.1914, 'v_max': 3.692, 'x_vmax': 0.1836}"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+04: "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Nu_avg': 2.3097, 'u_max': 16.5935, 'y_umax': 0.8242, 'v_max': 20.2422, 'x_vmax': 0.1211}"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ra=1e+05: "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Nu_avg': 4.7829, 'u_max': 36.4633, 'y_umax': 0.8555, 'v_max': 72.3986, 'x_vmax': 0.0664}"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "def hot_wall_nusselt(grid: dict[str, np.ndarray]) -> tuple[np.ndarray, np.ndarray, float]:\n",
    "    \"\"\"Local Nu(y) at the hot (west, x=0) wall and the height-averaged Nu_avg.\n",
    "\n",
    "    The local wall-normal gradient d(phi)/dx is approximated with a one-sided\n",
    "    2nd-order stencil on the first three cell columns, whose centres sit at\n",
    "    x = 0.5, 1.5, 2.5 (spacing dx = 1 lattice unit):\n",
    "        dphi/dx ~ (-3 phi0 + 4 phi1 - phi2) / (2 dx)\n",
    "    The flux runs hot -> cold so dphi/dx < 0; Nu = -(L / dT) * dphi/dx flips the\n",
    "    sign and normalises pure conduction (dphi/dx = -dT/L) to Nu = 1.\n",
    "    \"\"\"\n",
    "    phi = grid[\"temperature_phi\"]  # [iy, ix]\n",
    "    ys = grid[\"ys\"]\n",
    "    dx = 1.0\n",
    "    dphidx = (-3.0 * phi[:, 0] + 4.0 * phi[:, 1] - phi[:, 2]) / (2.0 * dx)\n",
    "    nu_local = -(L / DT) * dphidx\n",
    "    nu_avg = float(np.trapezoid(nu_local, ys) / (ys[-1] - ys[0]))\n",
    "    return ys, nu_local, nu_avg\n",
    "\n",
    "\n",
    "def velocity_extrema(grid: dict[str, np.ndarray], diffusivity: float) -> dict[str, float]:\n",
    "    \"\"\"u_max on the vertical mid-plane and v_max on the horizontal mid-plane.\n",
    "\n",
    "    Velocities are nondimensionalised by alpha / L = D / L (u* = u * L / D).\n",
    "    Locations are normalised by L.\n",
    "    \"\"\"\n",
    "    ux = grid[\"ux\"]  # horizontal velocity, [iy, ix]\n",
    "    uy = grid[\"uy\"]  # vertical velocity\n",
    "    xs, ys = grid[\"xs\"], grid[\"ys\"]\n",
    "    scale = L / diffusivity  # alpha = D\n",
    "\n",
    "    # Vertical mid-plane x = L/2: profile of ux along y.\n",
    "    ix_mid = int(L // 2)\n",
    "    ux_col = ux[:, ix_mid]\n",
    "    iy_u = int(np.argmax(np.abs(ux_col)))\n",
    "    u_max = ux_col[iy_u] * scale\n",
    "    y_umax = ys[iy_u] / L\n",
    "\n",
    "    # Horizontal mid-plane y = L/2: profile of uy along x.\n",
    "    iy_mid = int(L // 2)\n",
    "    uy_row = uy[iy_mid, :]\n",
    "    ix_v = int(np.argmax(np.abs(uy_row)))\n",
    "    v_max = uy_row[ix_v] * scale\n",
    "    x_vmax = xs[ix_v] / L\n",
    "\n",
    "    return {\n",
    "        \"u_max\": float(abs(u_max)),\n",
    "        \"y_umax\": float(y_umax),\n",
    "        \"v_max\": float(abs(v_max)),\n",
    "        \"x_vmax\": float(x_vmax),\n",
    "    }\n",
    "\n",
    "\n",
    "for ra in ra_values:\n",
    "    grid = sims[ra][\"grid\"]\n",
    "    ys, nu_local, nu_avg = hot_wall_nusselt(grid)\n",
    "    extrema = velocity_extrema(grid, sims[ra][\"D\"])\n",
    "    sims[ra][\"nu_y\"] = (ys / L, nu_local)\n",
    "    sims[ra][\"metrics\"] = {\"Nu_avg\": nu_avg, **extrema}\n",
    "    print(f\"Ra={ra:.0e}: \", {k: round(v, 4) for k, v in sims[ra][\"metrics\"].items()})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a76ab4c0",
   "metadata": {},
   "source": [
    "## Comparison table\n",
    "\n",
    "Computed vs de Vahl Davis (1983) with relative error, and the tolerance\n",
    "assertions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7b0e2ad6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:00.456691Z",
     "iopub.status.busy": "2026-06-29T17:44:00.456607Z",
     "iopub.status.idle": "2026-06-29T17:44:00.464396Z",
     "shell.execute_reply": "2026-06-29T17:44:00.464115Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Ra quantity  computed  reference  rel_err\n",
      "1e+03   Nu_avg    1.1227     1.1180   0.0042\n",
      "1e+03    u_max    3.6364     3.6490   0.0034\n",
      "1e+03    v_max    3.6920     3.6970   0.0013\n",
      "1e+04   Nu_avg    2.3097     2.2430   0.0297\n",
      "1e+04    u_max   16.5935    16.1780   0.0257\n",
      "1e+04    v_max   20.2422    19.6170   0.0319\n",
      "1e+05   Nu_avg    4.7829     4.5190   0.0584\n",
      "1e+05    u_max   36.4633    34.7300   0.0499\n",
      "1e+05    v_max   72.3986    68.5900   0.0555"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "ref = pd.read_csv(comparison_csv, comment=\"#\")\n",
    "ref = ref.set_index(\"Ra\")\n",
    "\n",
    "CMP = [\"Nu_avg\", \"u_max\", \"v_max\"]\n",
    "\n",
    "rows = []\n",
    "failures = []\n",
    "for ra in ra_values:\n",
    "    m = sims[ra][\"metrics\"]\n",
    "    ref_row = ref.loc[float(ra)]\n",
    "    for key in CMP:\n",
    "        computed = m[key]\n",
    "        reference = float(ref_row[key])\n",
    "        rel_err = abs(computed - reference) / abs(reference)\n",
    "        rows.append(\n",
    "            {\n",
    "                \"Ra\": f\"{ra:.0e}\",\n",
    "                \"quantity\": key,\n",
    "                \"computed\": computed,\n",
    "                \"reference\": reference,\n",
    "                \"rel_err\": rel_err,\n",
    "            }\n",
    "        )\n",
    "\n",
    "table = pd.DataFrame(rows)\n",
    "with pd.option_context(\"display.float_format\", lambda v: f\"{v:.4f}\"):\n",
    "    print(table.to_string(index=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e953f3d0",
   "metadata": {},
   "source": [
    "## Comparison plots\n",
    "\n",
    "The table above, visualised. The left panels overlay the computed metric on the\n",
    "de Vahl Davis (1983) reference across Ra (one panel per quantity, log-x in Ra);\n",
    "the right panel shows the relative error of each metric across Ra."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7c08bd74",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:00.465062Z",
     "iopub.status.busy": "2026-06-29T17:44:00.464996Z",
     "iopub.status.idle": "2026-06-29T17:44:00.917166Z",
     "shell.execute_reply": "2026-06-29T17:44:00.916746Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Lly/Hp59+Ku/wiIiIPkqdSIpraWkBRWaMF/X27Vvk5uaiXr16JR5/6NAhdOjQQfL1h8wUz8rKwtq1a7F48WKoq6uX61iimox9n+qiiuz34ge7SH5yc3Nx5swZWFhY8HOM6gz2e6qr2PdrD/4sqS5iv6e6in2/4mzevBnOzs4AAF1dXWRmZsLPzw/jx4/H2bNnYWxsLO8Qa6SCggKcOXOG93ioWOwf9D7sIxWn+KnTtYyJiQkUFRURFBQkU/fkyRMAQNOmTUs8vl69etDW1pb8U1dXh5KSUrn+CYVCnDp1CkKhsNzH8h//1eR/7Pv8Vxf/VXS/J/nKzc2Fq6srcnNz5R0KUZVhv6e6in2/9uDPkuoi9nuqq9j3K0Z8fDz27dsHDQ0NHD58GLdv38b9+/cxatQopKamYtu2bfIOscYSiURwdXWFSCSSdyhUDbF/0Puwj1ScOpEUV1dXR7t27RAcHIy7d+9K1bm4uAAArK2tSzzezc2tTN/n6NGjHxlp7VAd3ofKjqEiX/9jXqu8x5anfVnbVoefd3VQXd6HmtL3q7Lfl/cY9v26hz/L/1SX96Ey46ip43d5jylL2+ry85a36vI+cPz++GM4ftc9/Fn+p7q8Dxy/P/4Yfo6VT3V4H+rC+P0hx7Pf11yenp7Iy8vD5MmTYWlpCQBQVVXFsmXL0LBhQ1y5cgV5eXnyDpOIiOiD1Yik+Js3b+Dq6gpXV1fcuXMHABAYGCgpi4mJkbR98uSJTBkAjB07FgAwY8YMbN68GcePH8e0adNw5coVGBkZoXfv3iV+/0uXLpUpTv6B9p/q8D7UlAuTj30tXphUH9XlfagpfZ83o6g64c/yP9XlfeBN9Y8/hknxsqsu7wPH748/huN33cOf5X+qy/vA8fvjj+HnWPlUh/ehLozfH3I8+33NJV5ltWfPnlLlAoEAXbt2xdu3bxEZGSmn6IiIiD5ejdhTPDY2Fk5OTlJlbm5ukhncf/zxh2Q/E3d3dzg7O2Pjxo1Se5wMGjQIvr6+OH78OP78809JuY6ODjZt2lTsHuFZWVkAgIyMDPj5+b03ztTU1BLbpaenIzs7G//++2+p+5fXBqW9D7Ulhop8/Y95rfIeW572ZW37vnZ1pe9Xh35fFXFU1OtXZb8v7zEV0fcrst8/ffoUKDImUdmI3y/x+1cafo79py58jtXU8bu8x5SlLfv9f+pCv6/I16/p/b4s7TiGyxfH7/KrC59jHL/L3q6u9HtUk75fF8bvDzme43fNlZiYCAAwMjKSqTM0NJS0admypVSd+L16+PAh0tPTJeUCgQACgaDccbyOViv3MZUpMzPzo19DSUkJIpEImZmZEAqFH/16aklhH/0aFenBgwdV9r3YP96P/aP6qIj+gQruI7W1fzx79gwow/itIKoBi9DHxsZi+/btJdaPHDkSHTt2BAB4eHjg2rVr+O6779C+fXuZtvfu3YO3tzcyMjLQrFkzDB48GLq6usW+7tGjRzFmzJgKPBMiIqIPc+TIEYwePVreYdQYHMOJiKi64Bhedhy/iYiouqiL4/f48eNx9+5d/Pvvv1BXV5eq27NnD9avXw9nZ2f06tVLqo7jNxERVRfvG79rRFJcXpKSkuDu7g5TU1OZPwSIiIiqQlZWFiIjI2Fvbw89PT15h1NjcAwnIiJ54xhefhy/iYhI3ury+O3o6AgvLy/cunVL5tw3bdoEZ2dnHDx4ENbW1lJ1SUlJuHjxIgwNDaGm9v+zND90pjgREVF5lXX8ZlKciIiIiIiIiIiIiKgOW7lyJY4cOYJDhw7ByspKqm7WrFnw8PCAp6en1JalRERENYmivAMgIiIiIiIiIiIiIiL56dChAwDg/PnzUuXJycnw8fGBvr5+sfuNExER1RTK8g6AiIiIiIiIiIiIiIjkp1evXtDR0cHZs2fRuHFjDBgwAMnJyVi/fj3evn2LsWPHQkFBQd5hEhERfTAun17NxMfH49ixYwgJCYG+vj6GDx+Odu3ayTssoiqzdu1aXLx4EWvXroWNjY28wyGqVN27d5cp8/T0hIqKilzioQ+XkZGB48eP49GjR9DS0oK9vT169eol77CIqsypU6ewfft2TJs2DaNHj5Z3OESVasKECQgPD5cq2717N1q3bi23mOjD5Ofnw9XVFbdv34aSkhJsbW0xZMgQKCtz/gDVDQ8ePMCCBQtgZ2eHZcuWyTscokr166+/4urVq1JlTk5OGDBggNxiqo7c3Nwwb948vJsyMDc3x/Hjx6GlpSW32CqLSCTCo0eP8Pz5c3zyySfo27evvENCQUEB/P39ERsbCx0dHVhaWkJdXb3YtgkJCQgODkZqaioMDAzQpk0bqb3d6eMFBgbi6dOn0NLSqhafGSKRCI8fP0ZkZCTq16+Pzz//vEy/m+7u7khLS0OrVq2Yc6pAz549Q2BgIAQCAYYMGSLvcIDCPhseHg5NTU18/vnnqF+/vlS9UCiEq6trsccKBAIMHTq0iiKterzSq0ZSUlLg4OCAwYMHY8SIEXj8+DG+//577Nu3T2YfF6La6M6dO3jw4AGSkpKQnZ0t73CIKl18fDxcXFzQrFkzSRkT4jXT5MmTYWNjg6FDhyI2Nhbz58/HggUL8P3338s7NKJKFxMTgz179kBZWRmZmZnyDoeo0iUlJWHatGno06ePpExXV1euMdGHWbx4MT755BMMGDAAaWlp2L59OwIDA/HLL7/IOzSiSpeZmYnly5ejQYMGSElJkXc4RJUuJSUF/fr1g4ODg6RMW1tbrjFVRwMHDkTDhg3h4uKC0NBQaGhooGvXrpg6dWqtS4i/ffsW69atg6enJxISEgAAn332WaUkxV++fAkfHx/Y2dlBR0en1LbR0dGYMWMGQkJCJGU6OjpYv349unXrJimLiIjAqlWrcOvWLRQUFEjKGzRogB9//BHfffddhZ9HXZKfn4+1a9fC09MTL168AACYmJhUSlI8KSkJXl5e6NGjBxo2bFhq2/j4eEyfPh2BgYGSMi0tLaxZswb9+vUr8Thvb2/8+OOPAIApU6YwKV4B1q1bBw8PD0RHRwOFv6eVkRRPTU2Fh4cHbG1tYWhoWGrb5ORkzJo1C76+vpIydXV1rFixQirRnZ+fX+IDkfXq1WNSnKqGpqYmzpw5A1VVVQBA7969ERQUBHd3dybFqdbLyMjAL7/8gm3btuHrr7+WdzhEVUZXVxcGBgbyDoM+0r59+6RuECQkJODSpUtMilOtV1BQACcnJyxYsAA7d+6UdzhEVUZHR4fjdy3w66+/So3fAoEAa9asYVKc6oS1a9fiyy+/RGRkpLxDIaoympqaHL/LoEuXLujSpYu8w6h0aWlpOHbsGBQUFNC+fXsEBQVV2vd69uwZli1bhjZt2pSaFM/Pz4ejoyPCwsJgbGyMjh07Ijo6Gv/++y9mzZqFCxcuwNjYGAAQHByMmzdvokmTJjA3N4eWlhYiIiIQFBSEFStWwNjYGF27dq20c6rtcnJycOjQIaDwYYl3V4qqSJGRkVi2bBkOHTpUalJcJBJh5syZCAwMROPGjdGlSxe8evUKDx48wLx583D27Fm0atVK5riMjAwsX74cvXr1gpeXV6WdR11z4MABCIVCmJub4+XLl5X2feLj47Fs2TLs2LHjvUnx+fPnw9fXF/r6+rCyskJSUhLu3bsHJycnmJiYoFOnTlLtzczMZMpKWpWitmBS/CMIhUI8fvwY6enpaN269Xuf4nn58iWio6Ohra0Nc3NzKCoqStULBAKpr7OyshAdHS31BBiRvAmFQvj6+uLZs2fQ1tZ+71NDcXFxePDgAXJzc2Fubo4OHToU227VqlUYPHhwsQM3UXUQHx+PGzduIDMzE7169ULTpk1LbJuXl4f79+9LPvNtbW1LvOiZM2cOhEIhmjVrBgcHhzpx4VkdPHv2DAkJCTA2NpaaqV+c5ORkhIWFQVVVFa1bty52Nn/RG+oFBQUIDQ2FqalppcRO9KGCgoLg5+cHoVCI8ePHl7of4Js3b3Dnzh2kpqaiadOmsLS0LHY54YMHD0JXVxf29vZMilO1lJaWhhs3biApKQkdOnQo8W9RFN5k8vf3x/Pnz6Gqqgpra+sSb5xv3rwZmzdvRpMmTTBy5EgMHDiwEs+CxKKiohAVFQVdXV189tlnpbbNzMxEcHAwRCIRWrVqVezstnfLgoOD3/t3AVFVi4qKwu3bt5GTk4PBgwejQYMGJbbNysrCrVu3kJCQgEaNGsHW1rbYG5s+Pj549OgRzpw5Aycnp0o+A6Lyy8nJgY+PD2JiYmBqaoqePXuW2j44OBiPHz+GgoICOnTogBYtWhTb7q+//oKbmxv09PTQv39/jB49mltm1GEaGhpYvnw5+vbti0aNGqFjx47vPSY3NxePHj1CXFwctLS00KVLl/fO/C6Py5cvIywsDFZWVti7d6/k/sOWLVuwc+dO7Nu3DytWrAAKk1nHjh1D586dpV7j8OHD+O2333D9+nUmxT+CQCCAk5MT7OzsYGhoWOwWiO/Kz8/Ho0ePEBsbCw0NDXTq1KlCV5S6ceMGHj9+jDZt2uDIkSOSMf7AgQP4/fffsXv3bmzYsEHmuN9//x2NGzfGpEmTmBSvQAsXLkTv3r3RtGlTDBo0CImJiaW2LygoQEBAACIjI6GmpoYOHTqgUaNGFRaPv78/bt++jebNm+PkyZOoV68eAODMmTNYunQp/vzzT+zZs0fqmM8//xz/+9//KiyGmoCj/gcIDAzEsWPHcO3aNbx58wYA8Mcff5S4NEJKSgqWLFki9YFjZGSEP/74Q2bQQuGHVFBQEJ4/f47BgwdzX0aqFnJzc7FixQqpft+sWbNSk+Lbtm3Dzp07pZbwsbGxwfbt26VuQHl5eeHJkyd17gOYaoarV69i9+7dePTokWRPLQMDgxKT4pGRkXB0dERERISkTENDA6tWrZK5Ye7t7Q0ASE9Px+XLlzF+/HgcOnSo2LGBPl5sbCwOHToET09PxMXFAYVLRi1YsKDY9vn5+Vi5ciVOnz4NoVAIFM4MXL58Ob788kuZ9keOHJEsm/Tpp59iyZIllXxGRGWzefNmnD9/XtLvAWDMmDEl3gD8+++/8csvvyArK0tS1qJFCzg7O0tmJQBAWFgYXFxcStyHikieAgICsHnzZty7dw95eXkAgJkzZ5aYFE9JScH06dPx8OFDSZmysjLmzJmDKVOmSLV1cXFBfn4+srKycO/ePfz000/IzMzEiBEjKvms6qa0tDS4uLjgypUrkmVEe/bsiV27dpV4zN69e7Ft2zbJlkyqqqqYPn06HB0dZdp6eXnh4MGDePXqFTQ0NPiAD1Ubp06dwuHDh6WWz7WysioxKe7r64vZs2cjKSlJUqavr48tW7ZIXV+kp6dj+fLl2LZtm8zkDCJ5e/XqFVavXo2bN2/i7du3AAB7e/sSk+L5+flYsmQJLly4IFU+fPhwrFy5UmpC0i+//ILs7Gzk5eUhMDAQq1evRlxcHH766adKPiuqrurXr1+u++43b97EsmXL8OrVK0mZuro6Fi5cWGH3769fvw4A+PHHH6UeyP/hhx9w6NAhST0K93kvjomJCVC4jDp9OBUVFUyYMKHM7X19fbF48WLExsZKvcasWbMwderUColJfB9x5syZUg+9jRs3Dvv27cP169chEomkHoC/c+cOLl68iL/++uu9SVsqn4kTJ5a5bWBgIBYsWCB1v1hZWRkODg6YO3duhcQj/nyYNm2aJCGOwjFx7969uHPnDnJzc6U+W7Kzs+Hl5YW0tDQYGRmhffv2tf5hMcUytKF3XLx4EWfPnkVaWlqZltyZM2cOvLy8oKmpCUtLSxgZGSE2NhZTp06VujkpNmjQIDg4OGDSpEn4+++/cenSpUo6E6Kyy87OlvR7S0vL9y6jcf78eWzfvh1KSkqwt7fHiBEjoK+vjzt37mD58uWSdqmpqfj111+xevVqXpBTtXTr1i38+++/0NfXf++MpPz8fEyfPh0REREwMzPDqFGj0LVrV7x9+xaLFi2SuqGFwuS6gYEBWrZsiVmzZqFHjx44c+ZMJZ9R3XX//n0cPHgQcXFx711uCIUPqZ04cQKKioro3LkzzM3NkZKSgoULF+L+/fsy7W1tbTFlyhRMmTIFT58+xf79+yvpTIjKx9XVFXFxcbCwsHjvykZBQUFwcnJCVlYWunbtilGjRqFZs2YIDQ3FzJkzJQ+6CYVCLFmyBAsWLOBeylQtBQYGwsfHB+rq6mVahWXJkiV4+PAhGjVqhG+//Rb9+vWDgoIC1q9fD09PT6m2enp6MDAwQLNmzTBq1CiMHz8eJ0+erMSzqduioqKwY8cOhISElGn8PnXqFNatW4ecnBy0adMG7dq1Q15eHjZt2oTjx4/LtLewsMCUKVPg6OgIkUiENWvWVNKZEJWPu7s7QkJCYGJigubNm5faNjk5GdOnT0dSUhLat2+PUaNGoUOHDkhMTMT06dOl9gxftWoVBg0a9N5rGyJ5iI2Nhbu7O4RCIWxtbd/bfsuWLbhw4YJk/9PBgwdLtqd89+Ep8dYnxsbGGDBgAJYsWYLTp09LTeQgKklgYCB++OEHvHr1Cu3atcOgQYPQvXt3CIVC/O9//8PNmzcr5PuEhYVBIBDIPMipoqKCdu3a4eXLl8jIyJCqCw4OxunTp3H06FGsXr0aCxcuhJGREUaNGlUhMdH7hYWFwcHBAbGxsbCwsMCgQYPQq1cvKCoqYsOGDXBzc6uQ7xMaGgoUbnFQlJKSEjp16oSMjAyphzbevn2LZcuWYcGCBaWueEmV68WLF5g4cSIiIiJgbm6OL7/8Er1794aqqiqcnZ0r7FoyLCwMKJz9/a4uXbogLy9PKimPwkkRjo6OWLRoEb7//nvY2dnh9u3bFRJPdVW7U/6VpE2bNvjtt9/Qp08fXL16tcQN6VH4JM6dO3fQokULHD58GA0aNIBIJMLvv/8OFxcX7N69G7/++qvM6wNAjx49kJOTg/3792PQoEGVfl5EpVFVVcWqVavQu3dvNGjQAF988UWp7cUXH7t27ZK0TUlJwbBhw3Dx4kXMmTMHJiYmePbsGZKSkvDDDz9IjhXfaB84cCD38yO569OnD7766it06NABR48eLXWPqStXrkiWudq3b5/kQQ8XFxesWbMGe/fuxR9//FHi8fXr15fMaKKKZ2RkBCcnJ/Tt2xdJSUkYOXJkiW3j4+Nx/Phx6Ojo4NixY5IbkadPn8ayZcuwefNmHDt2TOoYMzMzmJmZAYV7xS9cuBAzZ84sdYlqoqowZ84cWFlZwdDQEBMmTEBCQkKJbffs2QOhUAgnJyfJU/G5ublwcHDAvXv34OXlhT59+iA1NRWPHz/GunXrsG7dOqDwhvyuXbtw+/ZtuLi4VNn5ERWnTZs22Lt3L6ytreHn54dx48aV2DY4OBheXl5o2rQpzpw5g/r16wOFMzGmTp0KZ2dn9O3bt8TjOX5XLm1tbcyaNQt9+/aFsbGxzJ53RQmFQmzduhVKSkrYvXu3ZMnQBw8eYOLEidi6dStGjBghNfuhUaNGkmUL27Zti4EDByIyMpLboJDcjRw5EosWLUKrVq2watUqyY3O4hw/fhypqakYMWIEfvvtN0n58uXLcfLkSZw4cUKyUoI4cfPXX38BhasxAED37t1x48aNSj4rotI1btwYW7ZsQffu3ZGdnQ0bG5sS2759+xaHDx+WJMHFn9thYWEYPnw49u3bh8mTJxe7/RUA1KtXD3l5ecjPzy+xDZHY1q1bgcJlqos+sBEZGYmRI0di//79ki1QU1JScOXKFanjg4ODgcL7RoGBgVJ1Q4YMkfTBlJQU6OjoFDtTU19fHyicYFR0BU4fHx+pe00dO3bEli1bOFO8Cu3cuRM5OTnYsWOH1HXDy5cv8e2332Lfvn2S1SMzMzNlkuRRUVFA4Uzf6OhoqboBAwZIft4pKSlQU1OTmgUsJn4APjU1FY0bNwYArF+/HiYmJvj+++8r/Jyp7Pbs2YO0tDSsXbtWatXd169fY9SoUdi3b5/kHmVubi7+/vtvqePj4+MBALdv35as4CvWp08fye+6+CFIPT09mRiKfn4UZWJigk8//RR5eXkICAjAixcvMG3aNJw+fRqtW7euoHegemFS/AMUt2RqSa5evQoAmD17tqRzKigoYN68eTh37hw8PT0lSXFfX1/Uq1dPsqdybm4u/P39YWRkVCnnQVQeqqqqGD58eJnavnjxAqGhobC0tJRKnuvo6GDixIlYuXIlvL29MXbsWHTs2FFm9k3v3r2xZMkS9OrVq8LPg6i83vcASFHim0gzZsyQWvlg7Nix2L17t2SZIwDw9PREfn4+evfuDRUVFdy6dQuXL1+WeVCKKo6lpSUsLS0BQGpZyeJ4e3sjPz8fY8eOlZqZM2LECJw4cQJ+fn5ITk5GgwYNEBkZiRcvXkgujAsKCnD//n0YGhoyIU7VwjfffFOmdiKRCDdv3oSenh7Gjh0rKVdRUcGMGTNw7949eHt7o0+fPtDR0ZH6TAOAyZMno0+fPqUmH4mqStu2bcvcVjx+T5w4UZIQR+FDyp06dZL6zH/69Cl8fX0xbNgwaGhoIDg4GIcPH+ZDzJXIxMQEM2fOBApvIpbm8ePHSExMRP/+/aX20Pz888/x1VdfwdXVFQ8fPoSVlRVycnLwzz//YNiwYZJ2d+/ehUAgeO+qGkRVoV+/fmVue/PmTSgoKODHH3+UKp89ezZOnz6N69evS5Li586dk5oZK06ilzbhg6iqGBoaSlYFed8DZw8ePEBWVhZGjx4t9SBT8+bN8dVXX+HkyZPw8/ODtbU1MjIy4OzsDAcHB+jo6ODVq1fYsWMHvvjiCybE6b2EQiHu3r0LIyMjxMXF4fTp01L1hoaGePz4seTrly9flviZumPHDpmyokmtgoICqWX/ixKXv7u6QatWrTB8+HBkZWUhPDwc/v7+GD16NA4cOCC1/RVVntu3b6NRo0Z48+aNTP8wMTGBn58f8vPzoaysjDdv3pTYP4pbcdDS0lKSFBeJRCX2D/H9J/H2f76+vvjnn3/w999/896UnN2+fRuffPIJ8vLyiu0fPj4+SE1Nhba2NrKzs0vsH0ePHpUpa926tdTnB4p8VhQlLhP3DyUlJezatUtqe5Lc3FysXr0ax48fx549e4rdn742YFK8komfArO2tpYqV1VVRceOHXH9+nXJDRY9PT04OTnhzZs30NHRQXh4OMzMzLB69Wo5RU/0YcRLuRQ3i0NcJn7KXUVFpdhtCHR0dKCjo1PpsRJVpLCwMCgqKqJjx45S5UpKSmjfvj2uXbuG169fQ1dXFx06dMDatWuxdOlSiEQiqKurY9asWRgyZIjc4qf/Jx6/i5uZYGNjg8DAQISEhMDa2ho6OjpYv349li1bBgMDA0RHR6NevXqlrgpAVB3Fx8cjIyMDlpaWUFJSkqrr2LEjFBUVJeO3oqKizPitrKwMLS2tYp9KJqrOxP26pL9d/fz8EBYWhgYNGsDU1BQXLlxAjx49gMIbD8OGDZNJRJF8lDZ+W1tbw9XVFSEhIbCysoKysjICAwOxefNmGBkZITExEdnZ2di4cSM0NDTkED3RhwsNDYWRkZHMAx26urowMTFBeHi4pOzdNmpqakDh1k5ENcn77j2dPHkSYWFhsLa2hoaGBvT09DBo0CDk5uYiOzsbdnZ2WLp0qRwip5omPT0dOTk5iIiIKPUBInFCW0dHR2Zi0atXr+Dj4wM7Oztoa2tL1amqqkr+X0tLC7GxsTL7QqPILNCis8QBoGvXrlIPA3p4eGDWrFlYv349tmzZ8oFnTWUlFAqRnJwMvOcBs4yMDOjo6EBTU1Omf7x+/RpeXl7o0aOHZEavWNFZ4ZqamsjKykJOTo5Uv0GR/lGvXj3k5ORg6dKl6NSpE3x8fCRtxDPSxUvud+rU6b1btNDHS0xMRGZmZqn9Iy0tDdra2lBRUZHpH2lpafDw8ICtrS2aNGkiVVd0RYiiKwq8e1+maP9A4f2boglxFOZpfvrpJ5w9e1ZmRYvahEnxSvbmzRtoaGhIzTgQEy/RJk6Km5qa4vjx44iOjkZSUhKaNGnCixKqkcTLcBR3U1y87+i7S3UU5eXlxYQ41UipqamoX79+sU+ai38fUlJSoKurCz09Paxbtw55eXnIycmRuagh+RJf0BQ3DovLxG10dHSwfft2JCQkICYmBnp6etyriWok8UXSuxfhKLw4qlevXqnj9/79+2UuzIlqgtL6vnj8Fvd9dXV1LFq0CAsWLEB6errMTU2Sr/KM30pKSvjll18wZ84chIWFQVtbG02bNi12uVKi6qygoADp6elo0aJFsfV6enqIiooqNsECAD///HMVRElU8Uq79/Tu+K2oqIgJEyZgwoQJSElJgba2NmdOUplpaGhAQUEBhoaGMhPfitO4cWOsWrVKqszLyws+Pj6YMWMGPv300xKPNTU1RWhoKMLCwqQ+10UiEYKCgqCtrY1PPvmk1O/fr18/6OnpSc1ep8qjpKQENTU1aGtrS5bQL454RclPPvlEpn/4+vrCy8sLkydPhpWVVYmv0axZM/j7+yMoKEjmgaCgoCAIBAI0adIEUVFRiIyMRGRkJLy8vGRe58aNG7hx4wZWrFjBpHgV0NDQgKqqKnr37l1iG01NTaDwYcV3+0dISAg8PDwwevToUrf1MjU1hbe3N4KCgiQPcYuJtwN93xZRAoEAqqqqyM/PL9O51US82qtk4mUxiiP+IHy3g5mYmMDExKRK4iOqTMVdYJS01E9R4gdGiGoT8e+DSCSSKhcIBFJLrVP1IF5OqLgxXFz27vjdsGFDLrdKtZqCgkKp47f4wTei2kQ8fr/b9xUVFZkQr4aKLgf4rpLGb21t7VL3KSeq7sTXFyUl+BQVFSESiUpMivOzjGq68t574iQMKi8VFRVYWFggPj4es2fPlrnuFwqFiIyMLHFZ6/KwtraGp6cnDhw4IJUYu3jxIhISEtC/f39JWVhYWLEJzaCgILx+/RotW7b86HiobDp27IjAwEA4OjrKLFlfUFCA8PBwSdLzY1hZWcHV1RUuLi5Sf796e3sjLCwMX3zxBZSVlVG/fv1it0EVz0hv1aoV2rZty4R4FenUqRO8vLwwadIkmfdcJBLh+fPnUjO+P5S1tTUOHjwIFxcXdO/eXTI++vv7w9/fH23btpVMyoqIiICxsbHMfc8zZ84gPT1dZhXU2oRJ8UqmqamJ6OjoYpPj4qcVK+IDkag6ES/D8ebNG5k68cyM4lZPIKrpxMtcFfeZL/59KLrsEVVf4rE5NTVV5kGdtLQ0qTZEtYX480k8a7ao/Px8pKeno1mzZnKIjKhyFf3b9d2bERy/axbx2Cweq4vi+E21lZKSEjQ0NIq9/kbhNbimpmaFJGuIqhPxjX3ee6KPcenSJWRkZACF1zwpKSmSPX8bN24sWZbc0dERs2bNwuDBg9G/f3/JbMuoqChcv34dnTt3xvr16z86nsGDB2Pbtm2SxJSVlRWioqJw/PhxAMDYsWMlbVevXo2EhATY2trCyMgIubm5khmlIpEIgwYN+uh46jpPT0/JZ0x2drbUntB6enro1asXAGDatGmYOHEivvnmG9jb26N58+ZQUFBATEwMbty4ATMzM+zateuj47G3t8eGDRvg7u6OqVOnokePHnjx4gWOHTsGABg3bhxQuALWu7ONUWRGevfu3bFgwYKPjqeu8/b2RkJCAlB4/zA3N1fSP7S1tdGvXz8AgIODA65evYoRI0bA3t4eLVq0gEAgQExMDHx8fKCjoyP5Hf8Y3bp1g6mpKW7fvo0JEybAzs4OiYmJkr3Ixf0DAA4fPgwvLy/06tULJiYmyM3Nha+vL7y9vQEA33333UfHU10xKV7JTExMEBgYiNDQULRu3VqqLjg4GAKBAI0bN5ZbfESVQfyHYXHL9AQEBACFy70Q1TampqYIDAzEkydP0K5dO6m6wMBAaGpqciZxDSF+sjc4OBjm5uZSdeL9SrlEOtU2jRs3hpqammSsLurJkycQCoUcv6lWEv/tGhAQIPPkvvj3wczMTC6xUfmIV1wLDg7Gl19+KVUnHr+5KhvVRs2aNcOzZ8+QmpoqNfM7PT0dkZGRMvejiGoD8d+ljx8/lpo9C957onLYuHEjoqOjJV/HxcVJ9v3t2bOnJCner18//PTTT1i3bp1M8kpZWbnELSzKS1tbGxs2bMCPP/4Id3d3uLu7A4UrIsybNw9dunSRtDU3N8ft27cREhIi8zrDhw/H5MmTKySmumznzp2SZafFxP2jU6dOkqS4jY0NVq5ciZUrV0qSomKKioqwt7evkHjU1dWxefNmODo6wtvbW5LABIApU6bI7BFNlevAgQO4c+eOVJm4f7Rs2VKSFG/Xrh3WrVuHpUuXwtXVVaq9goICRo4cWSHxCAQCbNq0CZMnT8bdu3dx9+5dSd2oUaMwePBgyddmZmY4deqUJGEupqysjLlz55a61HtNx6R4JevSpQvc3Nxw4sQJrFixQlL+8OFDhISEwNLSknuWUa1jamoKQ0ND3Lp1C0+fPpXslZObm4tDhw4BAGxtbeUcJVHFs7W1xT///IO9e/di69atkvKLFy/ixYsXsLOz475lNcTnn38OADh58iQGDRok+bnFx8fj2rVr0NXVZYKEah1FRUVYWVnB29sbFy9elEoo7d27F+D4TbWUra0ttm7dikOHDmHgwIFQUVEBCh9ou3PnDszMzLi9Tw3RqVMnKCkp4fz583B0dISGhgYAICcnB+fOnYOCggI6d+4s7zCJKpyNjQ2CgoKwf/9+zJ07V1Lu4uKC/Px8fPHFF3KNj6gyfP7551BWVsa5c+fg4OAgWe0lMTERf/31F9TU1Lg9Br3XgAED8Pr162Lr3n2gaPz48bC3t8eVK1cQGRkJFRUVNG3aFL169Xrv34qNGzfG8OHDy7R8f7du3XDp0iX8888/iIuLg46ODuzs7GBhYSHVbvHixRg9ejS8vb0RGRkJkUgEIyMjdOvWjctiV5C+ffuWuAf8uxMlRowYgV69esHd3R0REREQCAQwMjJCjx49YGRkVOr30dfXx/Dhw6Gvr//emDp37izpH1FRUahfvz569eqFDh06vPdY8fd5dyIPfZgePXrA0NCw2Lp3PxMGDhwIGxsbeHh4IDQ0FIqKijA2NsYXX3zx3ge4tLW1MXz48BK/V1EWFha4dOkSLly4gIiICGhqaqJbt26wtLSUajdmzBj0798fV69eRUREBPLy8mBqaoq+ffvW+km8CqJ3Nzel90pOTkZgYCAAwMfHBwcPHsTkyZNhbW0NAGjbti0++eQToHD5STs7O6SlpWHUqFHo1q0b4uLi4OzsjOTkZGzatAkDBw6U6/kQldX58+clS1Bt3boVampqmDp1KgDAwMBA6slcFxcXrFmzBtra2hg2bBjq16+PS5cuITg4GDY2NnBxcZHbeRCVR1RUFLy8vAAAfn5+cHd3xzfffINWrVoBhRdQ4j90srKy0K9fPyQkJMDGxga2traIjY2Fq6sr8vLycPToUamneqlqZWdn4/79+wCA8PBwrFmzBgMGDMA333wDAGjevLnkD8yCggIMGTIEISEh6N27N4YOHYr09HTs3bsXERERmD59OmbPni3X8yEqq5s3byIsLAwAcPz4cURGRmLJkiVQUFCAmpoaRo0aJWl7+/ZtTJw4EQKBAMOGDZM85Hb37l0YGhri8uXLkoQhUXWWmpqKc+fOAQCio6Nx9OhRdO3aFd26dQMKE0jisRwARo4ciX///RcWFhawt7dHamoqTp8+jfT0dPz2228YMWKE3M6F/vtsys/PR25uLmbMmIF27dph1qxZQOFN5qJ7Zs6ePRuXL19G+/btMXbsWCgoKODYsWN4+PAh7OzssH37djmeCVHZBQQE4OHDh0Dh8q0PHjzApEmTJNceI0eOhLq6OgAgNjYWAwYMQG5uLgYMGIDPPvsMT548gZubG1RVVeHu7l7rb3BS7XHo0CEUFBQgKysLmzdvRuvWrfH1118DAD799FNYWVlJ2i5duhRnzpyBoaEhhg4dCpFIhHPnzuHly5cYN24cli5dKsczISIiouqGSfEP4OXlBUdHxxLrDxw4IDWLxsPDA/PmzUNeXp5Uu6+//hq///57pcZKVJGGDBmCZ8+eFVtnaWmJw4cPS74uKCjA4sWLcf78eal2ZmZmcHFx4WwbqjEuX75cavLz3US3v78/HB0dpfbkVVRUxPz58+Hg4FDp8VLJYmNj0adPnxLrnZycMGHCBMnXT548wfjx42X2Je3cuTP2798PNTW1So2XqKIsWLAAFy5cKLZOR0cH9+7dkyr7888/sXXrVhQUFEjKdHV1sWvXLrRt27bS4yWqCGFhYaU+fLxixQqpfdJiYmIwadIkqeUzUZh0+vXXX7nSi5x17NgRb9++LbZu+PDhUnsmJiYmYvTo0YiKipJqZ2RkhGPHjvE6hGqM3bt3Y8OGDSXW+/j4SM0oc3Nzg5OTE7KzsyVlampqWLt2rczS0kTVmYWFBYRCYbF1o0ePxvLlyyVfZ2RkYMqUKfDz85NqZ2NjA2dnZ16zERERkRSu2/0BdHV1JfuJFEc8S1ysX79++Ouvv3D69GlER0dDW1sbvXv3luwpQFRTfPXVVzJLbYi9u2SMoqIi1q1bh5EjR+Lu3bvIzc2Fubk57OzsoKqqWkURE308U1NTjBs3rsT6d2+sduzYEZcvX4a7uztiYmIkn/kVtb8UfTg1NbVSx+93l7OysLDAP//8g5MnTyIkJAQqKiqwtrbG119/DYFAUAURE1WMbt26yfx9KiZeWrioH374AX369MH169eRmpqKpk2bwt7eXmqPUqLqTkdHp9Txu+gscQAwNjbG+fPnJcvZqaqqwtbWlsuuVhO2trZSib6iis4SR+GykK6urjh16hT+/fdfoHA1t++++w5aWlpVEi9RRWjbtm2pn2PiWeJiAwcORIcOHeDh4YGEhAQ0bNgQ9vb2nCFONc64ceNKTIq/u/KalpYWjhw5guvXr+Px48dQUFBAhw4d0KNHDz7QRkRERDI4U5yIiIiIiIiIiIiIiIiIiGotRXkHQEREREREREREREREREREVFmYFCciIiIiIiIiIiIiIiIiolqLSXEiIiIiIiIiIiIiIiIiIqq1mBQnIiIiIiIiIiIiIiIiIqJai0lxIiIiIiIiIiIiIiIiIiKqtZgUJyIiIiIiIiIiIiIiIiKiWktZ3gEQERERERERERERERER1QavX7/GunXrpMoUFBSgpqaGxo0bw9LSEh06dJBbfER1FZPiRERERERERERERERERBUgIyMD586dK7WNjY0Ntm7divr161dZXER1nYJIJBLJOwgiIiIiIiIiIiIiIiKimi4qKgr9+vUDAKxcuRLKyv/NT339+jUePHgAb29vAIC9vT22bt0q11iJ6hImxYmo3Pz9/fHixQupMmVlZdSvXx/m5ubQ1dWVW2xERERUvNDQUAQHB0uVKSoqQktLC2ZmZjA0NJRbbERERFS8+Ph4+Pr6SpUpKChAU1MTRkZGMDMzg4KCgtziIyIiIllFk+KPHz+GqqqqVP327duxbds2KCkp4e7du5wtTlRFuHw6EZXboUOH4ObmVmydgoICvvjiCyxfvhxNmzat8tiIiIioeB4eHtiyZUuJ9Z999hmWLl2Kzp07V2lcREREVLKAgADMmzevxHojIyPMnz8fAwcOrNK4iIiI6MMNGTIE27Ztg1AoRFxcnExSPDMzE97e3ggPD0dCQgLU1dXRunVr2NnZQUtLS25xE9V0TIoT0Qdr0aIFzM3NAQA5OTmIiYlBSEgIfHx8MHr0aPzzzz/Q0dGRd5hERERURKNGjSSJb6FQiJcvXyIwMBBBQUGYNGkSTp06hVatWsk7TCIiIipCQ0MDPXv2BAAUFBQgKSkJjx8/RmxsLObNmweBQAA7Ozt5h0lERERlkJmZKfn/evXqSdUdPXoUf/zxB7Kzs2WOW7NmDdavX4/u3btXSZxEtQ2T4kT0wfr27Yu5c+dKlXl7e2P69OlITEzEmTNn4ODgILf4iIiISFabNm2wadMmqbLg4GCMGzcOKSkp2L9/P9auXSu3+IiIiEiWnp6ezPidkJCASZMm4fnz5/jzzz+ZFCciIqoBsrKysHnzZgCAqakpmjRpIlUfFhYGdXV1DBo0CMbGxtDR0cHr169x8+ZN+Pv7Y/bs2XB3d0fDhg3ldAZENReT4kRUoXr06IFu3brBy8sLT548KbaNUChEVFQU4uLikJOTAwMDA7Ru3RrKyvxIIiIikodWrVrh22+/xe7du0scvwEgJiYGsbGxyMjIgK6uLj799FOoq6tXaaxERET0n4YNG2Lq1KlYuHAhnj59ioKCAigqKsq0S0hIQHR0NJKTk1G/fn1YWFhw71IiIqIqsmzZMigpKQEAkpOT8ejRI6SkpEBDQwMrV66UGbvHjh2LJUuWQEVFRap8xowZWL58OU6ePInz589zMhrRB2AGiogqnKamJlC4v3hROTk52LhxIy5evIjExESpOj09PcyZMwcjRoyo0liJiIjoPyWN3wCwe/dunD17FpGRkVLlGhoamDBhAmbOnCm5yCciIqKqIx6/lZSUIBKJpOrOnz+PQ4cOISAgQKpcIBBg8ODBWLp0qeR4IiIiqhznz5+XKWvatCn27dsHY2NjmbpmzZohJycHnp6eCAgIwJs3b5CbmwsAePnyJQDg2bNnVRA5Ue3DpDgRVaikpCTcvn0bAGBhYSFVl5aWBhcXF6iqqsLc3ByGhobIy8tDeHg4Xrx4gWXLlkFFRQVDhgyRU/RERER1U25uLtzd3YFixm8A2LdvHzIyMmBmZgZDQ0MoKSkhJiYGYWFh2LlzJ/Lz8zF//nw5RE5ERFS3XbhwAQBgbm4u84Da6dOnERAQAGNjYxgaGkJTUxOvXr3CkydPcPbsWSQnJ8PZ2VlOkRMREdUNK1euhLKyMvLz8xEREQFXV1dERUVhzZo12LFjh8yD6X5+fpg7dy5evXpV4mtmZGRUQeREtQ+T4kT0wcLCwnDx4kWgcBZ4VFSU5MLayMgI3377rVR7NTU1/PzzzxgyZAjq1asnKReJRDh//jwWLVqEHTt2MClORERUieLj4yXjd35+Pl6+fInz588jLCwM9erVw5QpU2SOmT59Ovr3749GjRpJlT948ADTpk2Di4sLpk6dKjW+ExERUcV5+/atZPwuKChAYmIiPD098fDhQygrK2P27NkyxwwdOhQrVqxA8+bNpcojIiLg4OAALy8vBAYGok2bNlV2HkRERHXNkCFDoKqqKvl67NixGD58OK5evYqjR49izJgxkrqMjAzMmDEDycnJMDMzQ8+ePWFoaAg1NTUoKioiJCQEBw4ckFkdhojKhklxIvpgV65cwZUrV2TKR4wYgdmzZ8vcGK9Xr55kkA8PD0dMTAwyMzMhEomgrKwMXV1dREVFISkpCXp6elV2HkRERHVJYGAg5s2bJ1Peo0cPLFq0SObGOQCMHz8eAPDixQuEh4cjPT0dBQUFAABTU1MEBQUhMDAQNjY2VXAGREREdU9SUlKx43ebNm2wePFiWFpaytQNGzYMKNy/NDg4GGlpacjPzwcAtG7dGrGxsXj48CGT4kRERFWoSZMmWLRoERYvXozt27dj6NCh0NLSAgDcvHkTycnJ+Oyzz3D8+HGpZDoAnDhxQk5RE9UOTIoT0Qdr0aIFzM3NAQApKSl49OgRMjMzERAQAEVFxWKPcXNzw4YNGxAbG1vi6yYnJzMpTkREVEkaNWqEzp07AwAyMzMRFBSEpKQkPHnyRJLoftfDhw+xatUqBAUFlfi6ycnJlRYzERFRXaehoYGePXsCALKzsxESEoLY2FiEh4cjKyur2GMiIyOxcuVK3Lp1q8QZZRy/iYiIqt7gwYOxa9cuhIeH4+jRo5g2bRoAIDExEQDQqVMnmYQ4AHh5eVV5rES1CZPiRPTB+vbti7lz50q+Tk1NxYwZM/DgwQMsWrQI+/btk2p/5coVSXsdHR2Ym5tDR0cHysr/fRTdunULqampEAqFVXwmREREdUebNm2wadMmyde5ubn45Zdf4OrqipkzZ+Lvv/+Gurq6pD4kJAQTJ05ETk4ONDQ00KpVK+jq6kJFRQUA8OjRI8TFxUlmnhEREVHF09PTkxq/CwoKsHfvXmzYsAFz587FhQsXYGhoKKlPTU3FmDFjkJiYCIFAgFatWkFfXx9qampQUFBAREQEnj59yutvIiIiOVBUVMS0adOwePFiuLi4YNy4cVBXV5dMFPP29sbMmTOho6MDABAKhXB2dsb169flHDlRzcakOBFVGG1tbWzcuBH9+/eHj48PPD090bdvX0n9nj17AAAODg6YN28elJSUpI7v06cPUlNTqzxuIiKiukxFRQW//vor/P39ERERARcXF/zwww+S+oMHDyInJwd9+/bFhg0boKamJnW8o6Mj4uLi5BA5ERFR3aWoqIipU6fCz88PXl5e2LBhAzZu3CipP3fuHBITE2FhYYG9e/dCV1dX6viNGzfi6dOncoiciIiIAGDQoEHYvn07YmJicOLECUycOBHdu3dHgwYNEB0djT59+ki2R3n69ClevnyJFi1aIDQ0VN6hE9VYxa9vTET0gRo2bIgJEyYAALZu3Sq1RFt4eDgAYOrUqTIJ8cTERN5QJyIikhMVFRXMnj0bALB//35kZGRI6sTj98SJE2US4nl5eaUuqU5ERESVa/78+VBQUICbmxueP38uKReP3yNGjJBJiAOAv79/lcZJRERE0pSVlTF16lQAwL59+5CTkwMtLS3s3LkTBgYGyMjIwLVr13Dt2jUkJCRgzJgxmD9/vrzDJqrROFOciCrc+PHj4eLiguDgYFy7dg19+vQBAKipqSE9PR3Pnz9Hly5dJO1zc3OxfPnyEvc4IyIiospnb2+P5s2bIywsDEeOHIGjoyMASJZSf3f8FolE2LhxIxISEuQWMxERUV3XsmVL2NnZwcPDA87OztiwYQNQZPwubjaZq6sr7t+/X+WxEhER1RW6urpYs2YNUJj8LsnQoUMhEAggEomQmpqKhg0bomPHjrhy5Qr8/PyQkJAAbW1ttG3bFg0aNEB8fDzWrFmDxo0bV+HZENUeTIoTUYXT1tbG999/jz179uDPP/+UJMW7desGV1dXzJgxA6NGjULTpk3x4sULXLx4EREREdDQ0MDbt2/lHT4REVGdJN7TbNGiRZI9zTQ0NNC1a1fcunULa9asQWhoKCwsLPD69Wt4eXnBz8+P4zcREZGc/fDDD/Dw8ICbmxtmzpyJZs2aoWvXrnBxccGxY8eQlpYGS0tLvH37Fg8ePICnpyfHbyIiokqkpaWFb7755r3tVFRU8PXXXxdbbm1tLVPeqFGjMr0uERWPy6cTUaWYOHEi1NXVERAQgJs3bwIA5s2bB1NTU6SkpMDZ2RlOTk7Ytm0boqOjsWTJEjRr1kzeYRMREdVpgwYNgomJCd68eYMTJ04AAMaMGQMrKyvk5OTgyJEj+Omnn7Bhwwb4+flh1KhR6Nevn7zDJiIiqtMsLCzQs2dPFBQUYPfu3UDhQ+nffvstRCIRLly4gJ9//hlr1qyBp6cnvvjiCzg4OMg7bCIiIiKiKsWZ4kRUbh07dgQAtGrVqsQ2urq6WLBgAR4+fIjQ0FB069YN+vr6OHfuHP7++28EBAQAAIyNjWFvbw8zMzO8efMGTZs2Rf369avsXIiIiOqKli1bYuDAgWjbtm2JbZSUlLB48WJcvHgRr169AgqfUN+/fz/c3d1x79495OTkwMDAAL1790b79u1x7Ngx5ObmwtDQsArPhoiIqG5o1KgRBg4cCD09vVLb/fjjj9DQ0EB+fj6ys7OhpqaGlStXwt7eHtevX0daWhp0dXVhbW2N7t274/r16xg4cCBat25dZedCRERERCRPCiJu4ktERERERERERERERERERLUUl08nIiIiIiIiIiIiIiIiIqJai0lxIiIiIiIiIiIiIiIiIiKqtZgUJyIiIiIiIiIiIiIiIiKiWotJcSIiIiIiIiIiIiIiIiIiqrWYFCciIiIiIiIiIiIiIiIiolqLSXEiIiIiIiIiIiIiIiIiIqq1mBQnIiIiIiIiIiIiIiIiIqJai0lxIiIiIiIiIiIiIiIiIiKqtZgUJyIiIiIiIiIiIiIiIiKiWotJcSIiIiIiIiIiIiIiIiIiqrWYFCciIiIiIiIiIiIiIiIiolqLSXEiIiIiIiIiIiIiIiIiIqq1mBQnIiIiIiIiIiIiIiIiIqJai0lxIiIiIiIiIiIiIiIiIiKqtf4PJErg1l/WTdwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 2000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = {\"Nu_avg\": r\"$\\mathrm{Nu}_\\mathrm{avg}$\", \"u_max\": r\"$u_\\max^*$\", \"v_max\": r\"$v_\\max^*$\"}\n",
    "ra_arr = np.array([float(ra) for ra in ra_values])\n",
    "\n",
    "fig, axes = plt.subplots(1, len(CMP) + 1, figsize=(5 * (len(CMP) + 1), 5))\n",
    "\n",
    "# One panel per quantity: computed vs de Vahl Davis reference across Ra.\n",
    "for ax, key in zip(axes[:-1], CMP):\n",
    "    computed = np.array([sims[ra][\"metrics\"][key] for ra in ra_values])\n",
    "    reference = np.array([float(ref.loc[ra][key]) for ra in ra_values])\n",
    "    ax.plot(ra_arr, reference, label=\"de Vahl Davis 1983\", **common.markers.exp(\"s\", markersize=9))\n",
    "    ax.plot(ra_arr, computed, label=\"Nassu\", **common.markers.sim(\"o\"))\n",
    "    ax.set_xscale(\"log\")\n",
    "    ax.set_xlabel(\"Ra\")\n",
    "    ax.set_ylabel(labels[key])\n",
    "    ax.set_title(labels[key])\n",
    "    ax.legend()\n",
    "\n",
    "# Relative error of every metric across Ra.\n",
    "ax = axes[-1]\n",
    "width = 0.8 / len(CMP)\n",
    "x = np.arange(len(ra_values))\n",
    "for i, key in enumerate(CMP):\n",
    "    rel_err = np.array(\n",
    "        [\n",
    "            abs(sims[ra][\"metrics\"][key] - float(ref.loc[ra][key])) / abs(float(ref.loc[ra][key]))\n",
    "            for ra in ra_values\n",
    "        ]\n",
    "    )\n",
    "    ax.bar(x + (i - (len(CMP) - 1) / 2) * width, 100 * rel_err, width, label=labels[key])\n",
    "ax.set_xticks(x)\n",
    "ax.set_xticklabels([f\"{ra:.0e}\" for ra in ra_values])\n",
    "ax.set_xlabel(\"Ra\")\n",
    "ax.set_ylabel(\"relative error (%)\")\n",
    "ax.set_title(\"Relative error vs de Vahl Davis 1983\")\n",
    "ax.legend()\n",
    "\n",
    "fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f97119f",
   "metadata": {},
   "source": [
    "## Isotherms and streamlines\n",
    "\n",
    "Steady scalar field (isotherms) with the buoyant recirculation overlaid as\n",
    "streamlines, one panel per Ra. The recirculation tightens and the thermal\n",
    "boundary layers thin as Ra increases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "099e43a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:00.918020Z",
     "iopub.status.busy": "2026-06-29T17:44:00.917925Z",
     "iopub.status.idle": "2026-06-29T17:44:01.307712Z",
     "shell.execute_reply": "2026-06-29T17:44:01.307403Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, axes = plt.subplots(1, len(ra_values), figsize=(5 * len(ra_values), 5))\n",
    "if len(ra_values) == 1:\n",
    "    axes = [axes]\n",
    "\n",
    "for ax, ra in zip(axes, ra_values):\n",
    "    grid = sims[ra][\"grid\"]\n",
    "    xs, ys = grid[\"xs\"], grid[\"ys\"]\n",
    "    X, Y = np.meshgrid(xs / L, ys / L)\n",
    "    phi = grid[\"temperature_phi\"]\n",
    "    cf = ax.contourf(X, Y, phi, levels=21, cmap=\"coolwarm\")\n",
    "    ax.contour(X, Y, phi, levels=11, colors=\"k\", linewidths=0.4, alpha=0.5)\n",
    "    ax.streamplot(\n",
    "        xs / L,\n",
    "        ys / L,\n",
    "        grid[\"ux\"],\n",
    "        grid[\"uy\"],\n",
    "        color=common.colors.text,\n",
    "        density=1.1,\n",
    "        linewidth=0.7,\n",
    "        arrowsize=0.7,\n",
    "    )\n",
    "    ax.set_title(f\"Ra = {ra:.0e}\")\n",
    "    ax.set_xlabel(\"x / L\")\n",
    "    ax.set_ylabel(\"y / L\")\n",
    "    ax.set_aspect(\"equal\")\n",
    "\n",
    "fig.colorbar(cf, ax=axes, label=r\"$\\phi$\", fraction=0.025, pad=0.02)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "872b1cba",
   "metadata": {},
   "source": [
    "## Local hot-wall Nusselt profile\n",
    "\n",
    "$\\text{Nu}(y)$ along the hot (west) wall for each Ra. The peak near the bottom\n",
    "(where cold fluid impinges) sharpens with Ra; the height-averaged value is the\n",
    "$\\text{Nu}_\\text{avg}$ compared above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5bad8bef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:01.309873Z",
     "iopub.status.busy": "2026-06-29T17:44:01.309743Z",
     "iopub.status.idle": "2026-06-29T17:44:01.360656Z",
     "shell.execute_reply": "2026-06-29T17:44:01.360305Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Sra0tAAUFBeWOx8fHExUVBYBOp+PChQscOXKE6dOn89xzz920zNOnT3P48GGTrt+vXz9cXV2rHH9ZWq2WWbNmsXjxYoKCgnBzc2Pfvn0EBwfzySef4OLiUq3yd+7cSUhIiLHOSnXr1o1//vmHmJgYIiIijMezs7N5+eWXueOOO4iMjKzWtavKqhIYczhz5gwqlYqePXua/Jyvvvqq3P0OHTrw/vvvV2pAsLnorulC0hsgu1CLi52m1mMRQlg3g8Fw3Ye7pdna2qJQmOcfsm3btkFJS0dZw4YNY+zYseWus2HDBh555BG6d+9+08+HTZs28f7775t0/d9//91sCcyHH37IokWL+O677+jRowcASUlJ3H333fzf//0fn376KdwgwcrKyuLMmTOsXLmy3PHSBCsjI4P09HSaNm163XV9fHygZJxR2QTmnXfeobCwkJdfftksr68qGlQCc/DgQX766SemT59Oy5YtTX5eq1ataNeuHdnZ2Rw8eJBjx45x33338eeff+Lp6XnD52VlZZGRkWG8b2Njc10T3K3odLpyt0Xa4lu1UoFSoaBQp+dKdgGOGpkRb6pr61SYh9Sr+ZmzTnU6XclWJMVflMx+ueuuu6pdtjktXboUOzu7Sj2n9PUcOXKElStXotPpOHPmDAsXLqRTp07cf//9xnNKbwsLCzly5AhJSUnGFnk7Ozt27txpTBAq0qZNG0aNGmVSXC4uLsbrVea1XPuczMxMFixYYGztKH3c29ubadOm8c4775CcnEyjRo3YuHEjH3zwwXXlJiYmGhO6UitWrMDFxYWcnBwoSR6vvba9vT2UtLiUPrZ+/XqWL1/O7NmzcXZ2LvecW73e0ten0+lu+L429f3eYBKYAwcOMGPGDIYMGcLTTz9t0nPc3NxYtGhRuawzKyuLZ599li1btrB48eIbDmwCmDJlSrlfxLFjxzJ+/PgqxR8TEwNAYk7xD1aJASeNglQd7DpwmFR3aYGprNI6FeYl9Wp+5qpTtVpNXl6ecaxCfn6+Wco1p9zc3EqPpSh9HadPn0av11NUVMTRo0dRKpU88sgjaDQacnNzjedv376dN954A6VSSUBAAE5OTlDy4Xrp0qVy516rS5cudOnSpVKvxxSlSVRBQcF1z9m/fz9FRUVotVpWrFhRLhlLSEjAYDBw5MgRunTpQrNmzbjtttvKPX/r1q00atSIDh06lDtuY2NDbm6uMWHIz8+/7trZ2dkAKBQKcnNzSU1N5b///S8DBw6kV69e5c43GAy3fL0FBQUUFRVx/PjxG55z7ezhG2kQCcz69et57rnnGD58ODNnzkSpNK21wtvbG29v73LHnJ2dee211xg8eDAHDx686fN//vlnQkNDjfer2gITExNDcHAwKpWKuNRcWJmEWqWikZMdqfk5NG7RhtDWHpUqtyG7tk6FeUi9mp856zQ/P5/4+Hjs7e2N/1jZ29uzdOlSM0VrHlXpQip9PaNGjTJOuNBqtTz11FM8/fTTLF261DjYNTc3l1deeYWuXbsyZ84cY70aDAY6deqESqXCwcHhhtc6ffo0R44cMSmuvn37mtyFVPrZYGtre931S+vj/PnzaLXXzzwdNWoU3t7eODg4MGTIEIYMGXLd45GRkfznP/+p8Np2dnbY2tqSnp5+3bWzsrIAaN68OQ4ODvz++++kpaURHh5uXCfNYDCQnZ2NXq9n3bp1NG/evNxnX1lKpRKNRoO/v/8NW9pMTWDrfQKzaNEiZs6cyaRJk3j11VfN0rdamq1X9EYqy9nZ2Wz9nyqVCpVKhaIk+VIqwc2huNUlq0AnHxhVUFqnwrykXs3PHHWqUqlQKBTGL0o+GEu7CKxZ2ddT+r1Go+Htt99m6NChvPHGGyxZsgRKEpDs7GyGDx+OWn31I/DMmTMUFhaWK6MimzdvrtQYGDc3t0q/lmuvXzrkoW/fvsyYMaNS5V1bdkVUKhUhISEcOXLkunNiYmJQq9UEBwejUCho2bIlo0aN4vjx4+VaUUq7obZu3Uq3bt0ICwu76eu72Xva1Pd6vU1gDAYDn3zyCd988w0PPfQQzz77bKXLOHv2LK1atbru+Lx58wBo3bq1WWKtjNJp1CqFAreSgbuynYAQQlzP09OTadOmMXv2bNatW8egQYNo3LgxlLRmlDIYDHz77bdoNLfuivf39zd5DIy5/oFt0aIF3bt3Z+HChUyYMAF3d/dyj8fHx9OiRYtqXWP8+PG89NJLbNy40bhIa2ZmJn///TeDBw82XrNnz57XDXI2GAyMGDECvV7Phx9+WK04KsPqEphVq1YZ+9j0ej2pqaksX74cSkZLl07nevvtt1m4cCFBQUG0bNnSeE6ptm3bGteRSU9PZ8OGDfj6+tKtWzfjOTNnziQlJYUePXrg5+dHdnY227ZtIzo6GpVKZfI6MuZUOo1aqVDgZl+SwMhaMEIIUaGpU6cyf/58PvvsMwYMGIC3tzejRo3im2++IS8vjyZNmrBx40YiIiJMSjj69u1L3759zRJbTk6OsRvm0KFDAERFRZGcnAzAmDFjjOd++OGHzJgxgxEjRjB+/Hj8/PxITk7m4MGDpKSkXPcZV1ljxoxh69atPP/889x///24ubmxZMkSnJ2db9j1ZGlWl8C8//77xgWIKMmiS5f7HzhwoDGBOXDgAACHDx+ucDuA+++/35jAXLp0iVdeeYWhQ4eWS2DatGnD9u3brxtsZG9vz1tvvWWR9WCMLTBKBW72xT8+WY1XCNGQeXh4MGrUKPz9/a97zMnJif/+979s2rSJ06dP4+/vzxtvvEGfPn04cOAAZ8+eZdq0afTs2ZPk5GSzLQxniry8vHJ7OI0aNYpLly5x6dIluCaB8fLy4rfffmPjxo3s2bOHAwcO4OPjw5QpU265LEj//v0rrJuyFAoFH330ERs2bGD79u1cunSJiRMncvvtt+Po6HjL19KnTx+Tx5eai9UlMEOHDiUtLa3Cxzp27Gj8fsCAATddp6XsKr6urq7ccccd163s+5///Ie7776bzZs3Ex8fj1KpxN/fnyFDhtx0+nRNKt1KQKlAWmCEEKJkgOnNui5GjhzJyJEjoaS7Q6FQMGrUKEaPHl3uvP/7v/+r8VjLatSoUaW6XFQqFYMGDWLQoEGVus6tFucra8CAAQwYMKBS5QM88cQTNx38XBOsLoF56aWXTDrvZtObr9W0aVPee++9Ch9r1apVheNgLEVnTGCkC0kIIUTDJaufWZnS2WXFXUgyiFcIIUTDJAmMlSnXhWQnLTBCCCEaJklgrExpF1L5QbySwAghhGhYJIGxMhVPo5ZZSEIIIRoWSWCsTLmF7GQQrxBCiAbK6mYhNXQVTaPOyC9CrzegVFZ+m4SEjDy+3B7HtrOppOYWkZpbRE6hlqAmzvRs5UHPlh708/fExU42ixRCCFF3SAJjZcovZFecVOgNkF2orVSSsfd8Oh9tPsOvBy+i1V+//fn2uDS2x6UBp3G2VfNwZAue7tOapq6V2+ZeCCGEqAmSwFiZsmNg7NRKbFRKCnV60vOKTEpgDAYDn245w3N/HqWkMYe+bTyZ1qUZfq52eDjYoFEp2HM+g+1xqWw8lcLpK7l8sOk0n249w9TOzXh3eABeTrY1/EqFEEKIG5MExsroyyxkp1AUz0S6nF1IRv6tB/JqdXqeWHGYr6PiARgf4sMrA/0J97t+t9QgHxfu69oMvd7AP8cvM2vDKbadTeX7XedYEXOJT8YEMjnCzyy7ewshhBCVJYN4rczVLqTi+6YO5M3ML2LkD9F8HRWPQgEfjurIL1MiKkxeylIqFYzs2Jitj/dk62M9CPFx4UpuEVMWH2Dotzs5n5ZnrpcmhBBCmEwSGCtTtgUGExMYrU7PnT/vZfWJZBxsVCyf2pnn+rWpdOtJr9ae7HmmN+8OD8BWrWRtbAphH29m9fHL1XpNQghRXVqt1vilL12y3IoYDAa0Wi0Gw/VjEqtLp9OZtU5KY63oqzZJAmNldCXvbVXJjCNTVuN98a9jrD6RjL1GyYaHI7k92KfK19eolLwysC2Hnu9LuJ8rV3KLuO37Xbyx+oSxdUgIIWrTgQMHCAwMJDg4mJCQEAIDAwkPD2fKlCls377d0uHdUGFhIevWreO5554jIiKCwMBAoqKizH6dMWPG8L///e+W5124cIEnn3yS8PBwgoKCGD9+PFu2bLnuvIULFxIYGEhISAghISF06tSJyMhIOnXqxMmTJ80e/41IAmNl9PobtcBUnPnO3XWOT7acAWDe3WF0a+FuljjaeTmx/fGezOjeHIMB3lwTy6gfosmUfZmEEBby/PPPc/ToUY4cOcJvv/2GXq/nwQcfZPfu3ZYOrUJr165l2bJl9O3bl0cffdSisaSlpXHPPfeQlpbG33//ze7du+nduzcPP/ww27Ztq/A5a9asMdb37t27OXLkCG3btq21mCWBsTLGrQRKen+M2wlUkDhsO3OFh5cdAuD1Ie2Y0KmpWWOx06j4ZkIn5t0dir1Gyb/HL9P78x0yLkYIYVFKpZLWrVvz5ptvotPpWLJkSbnH9Xp9nehuGjFiBF999RWjR4/G0dHRYnEA/PDDDyQnJzNr1ix8fHywt7fnqaeeIjAw0KTWG0uQBMbKGMfAKMu3wJy9klvuvNjkbG7/cTdFOgPjQ3z4v8HtaiymKZ2bsfnRnjR2tuXQpUy6z97GvgvpNXY9IYQwRfPmzQFISkoqd3zOnDl06tTJ2N0UFhbGfffdx549e25Z5s3Gf9T0eJA9e/Ywffp0wsLCCAwMZMSIESxfvtwsZa9du5YOHTrQtGn5f3QHDRrEqVOnOH36tFmuY04yjdrK6Er+WSjtQurSrHgW0Y+7zxPs48wzfduQmJnPsG93cSW3iM7NXPlpYmiVVumtjC7N3dj1ZC9G/BDNkcQs+nyxg9+ndWFQO68ava4QouoMBgO5hTpLh1GOg43KbMsznDlT3H1+7YfyU089xSuvvIJCoUCv15OQkMDnn3/OjBkzWLlyJc2aNbthmXPnzuX999836fq///47HTp0qOarKLZ+/XqeeOIJxo0bx9tvv42bmxurVq3i9ddfJysri6lTp0LJz1Snu/5nWpp4laVWF6cA+fn5xMfHM2rUqOue17p1awBOnDhBmzZtyj02btw4MjIycHZ2JjQ0lCeeeIKQkBCzvF5TSAJjZfSGq3shAYwL8eE/A/15d/0pnv3jKNmFOn4/nMjZ1FzaeDrw9/RuONrWzo+5hYcD2x/vyfh5e1h3MoUR30fzy5QIxgQ1qZXrCyEqJ7dQh9N//rV0GOVkv3tblf9mlXYN6fV6Tp8+zeuvv46dnR1Tpky54XOUSiU+Pj689dZbrFq1in///ZcZM2bc9HyVSmVSPOZKxLRaLW+++SZhYWG8/fbbxuNjx44lNjaWOXPmMHHiRGxtbW+YYJ08eZL58+eXO1aaYGVkZGAwGHBxcbnueaXH0tPTyx175ZVXGDhwIN7e3hw7dox33nmHSZMm8f3339O9e3ezvO5bkQTGypTdC4mSX5CZtwWgVip5a20s/7fqBABeTjasmtEdb+faXTHX1V7DXw90ZdKCfSyPSWTcvD3MmxjKPRF+tRqHEKLh+fjjj/nkk0/Q6/UYDAacnJz48ccfCQoKKndeWloaH374IZs2bSIxMRFK/pbqdDrOnTt302tMmzaNadOm1ejruNaxY8dISkpi+vTpUNKaUnrbtWtXfvzxR44dO0ZoaGiFCZZOp0OhUKBUlh81cm2CVdEU7tJjZc8dPXp0uXM6derE7NmzGTt2LLNmzWLFihXVfs2mkATGypTdC6mUQqHgzWHtUSkVvL76BA42Kv6a3hX/RpYZFGarVrH03gim/3KQn/dc4N7F+8kq0PJwj5YWiUcIUTEHGxXZ795m6TDKcbAxrXWjIs8//zzTp09Hq9Vy8OBBnnvuOd544w0WL15sHCRrMBh47LHHyMzM5L333iM4OBgHBwcAOnfufMuxKzfqoqlIaRdNdV25cgWA9957j1mzZl33uEqlIiMjA26QYI0cOZLIyEheffXVCst3c3NDoVCQmZl53WNZWVnGc27GxcWFiIgI1q5dS35+PnZ2Nb9vniQwVqbsXkjX+r8h7ejd2oOmLna093aq/eDKUKuU/HhXKC62aj7fHscjy2LIyNfy0gB/i8YlhLhKoVDUWhdzbVKr1URERPDhhx8yefJkPv74Y1577TUATp06xfHjx3nzzTfp1q2b8TmZmZnGD+ubscQYGA8PDwDeeustJkyYUO3yrmVra0uLFi2MY4bKOnXqFADt27e/ZTkVtdbUJJmFZGUqaoEpq79/I4snL6WUSgWz7wji1UHF6wK8/PcxXv3nWI2sNCmEENfq3LkzQ4YMYcmSJcTFxUHJGBYAjab85remdnuUdtGY8mWuD/KOHTvSuHFj/vnnH7OUV5GhQ4dy7NgxLly4UO742rVradeunXEw742kp6ezZ88eAgMDsbWtnaELksBYmWvHwNR1pWN0Zo0o/i/k3fWneOr3I5LECCFqxVNPPYXBYGD27NkAtGzZklatWvH9999z/Phx0tLSWL58Odu3b8fT0/OW5U2bNo2jR4+a9BUQEHDL8q5dj6bsGjWl1Go1b7/9Nrt37+b555/n+PHjZGdnExcXx++//84999xTrToCuP/++2nSpAnPP/88cXFxpKen8/7773P8+HFeeeWVcufed999/PPPP5w/f56srCz27NnDk08+SW5u7nXn1qT613ZYz+mu2QvJWrw4wB8XOzWPLo9hzrazFOn0fDE2uMandwsh6j+FQoFKpbpukCpAmzZtGDNmDH/++SfHjx+nffv2fPrpp3z66adMnToVlUpFv379+OijjxgxYkSFZdSUc+fOMWzYMON9lUpVbgbU0aNHjd/37duXX3/9lW+//ZYHH3yQrKwsmjRpQlhYmLF77EZKW4Ruxs3NjUWLFvHhhx8yceJECgoK6NChA99//z09evQod+7LL7/MvHnz+PTTT0lKSsLNzY2wsDDeeecdk5I2c5EExsror9kLyZo83KMl9hoV05Ye4OuoeLR6A9+MD5EkRghRLZ06dSr3YX+t//3vf8bVZA0GA82aNeOrr766rounon1/alLz5s1vGve1OnTowCeffFLp66xcudKk83x8fPjoo49ueV5AQEC51XkNBgO5ubnGwdC1RbqQrMzVvZAsHUnVTO3SjJ/vDkOpgO93nWP6LwdlE0ghhBCVJgmMldFds5CdNZoc4cfCe8JRKRX8tPs89y3ZL0mMEEKISpEExsrcbBq1NZkY5suSyeGolQoW7E3g3kX70eost6maEEII6yIJjJW51TRqazK+U1N+mRKBWqlg8f4EJi3cR5EkMUIIIUwgCYyVsbZp1LdyR7APy6Z2RqNS8OvBS9w1fy+FWklihBBC3JwkMFamPrXAlBod1ITfp3XBVq1kRUwiE37eQ4G2bu2QK4QQom6RBMbK1JcxMNca3qExK0uSmD+OJDHupz3kF0kSI4QQomKSwFiZ+taFVNbQAG/+mt4Ve42Sv49d5o6fdpMnSYwQQogKSAJjZepjF1JZg9p58fcD3XCwUbHqeDJj5kaTW3jz3WGFEEI0PLISr5Wpr11IZfX3b8S/D3Rj+Pe7WBubwsgfovnz/q71ctdcIWpbQUGBpUOwKIPBQEFBAUqlstZ2Ta7vKlOn5nz/ySeClTEuZFdPW2BK9WnjyeoZ3Rn23U42nrrC8O938fcD3XCSJEaIKindHfnixYuWDsWiDAYDRUVFaDQaSWDMpLJ1Wrp3VXVZ3adBYWEh27dvZ+3atZw+fRp/f3/eeeedG56/Z88efvvtNxISEnB3d2fo0KGMGDGiUtc0RxnmUp/HwFyrZysP1j4UydBvd7LlTCrDvt3Jvw92x9nO6t62QlicRqOhTZs26HQNe1yZTqfj+PHj+Pv7m+VDVFS+TlUqFRqNptrXtapPgsuXLzN06FByc3ONxwyGGy9Bv3DhQt5+++1y56xevZrt27fz7rvvmnRNc5RhTsYxMA3kP4fuLdxZ91AkQ77dyfa4NIZ8u5NVD3bD1b76b34hGhqNRmOWDw5rVprA2dnZSQJjJpaqU6saxFtYWIhWq6Vfv37MnDnzpr+ICQkJvPfee6jVap544gnmz5/PzJkz8fDwYNmyZWzYsOGW1zNHGebWEMbAXKtLczfWPdQdd3sNO+PTGPzNTtLziiwdlhBCCAuyqgTG29ubnTt38s033zBhwoSb9rWtWLGCwsJCHnnkER5//HG6du3KhAkTjFuRL1269JbXM0cZ5qYz7kbdcBIYgIhmbmx4JBJPBw27z6cz6OsoUnMLLR2WEEIIC7GqBMbGxgZHR0eTzt27dy8A48ePL3e8e/fu+Pn5GR+v6TLMTW8cxFvrl7a4UF9XNj7aAy8nG/ZeyGDgV1GkZDfsGRVCCNFQWdUYmMq4cOECbm5uNG7c+LrH2rZty8aNG0lLS8Pd3b3GysjKyiIjI8N438bGBhsbm0q9jtK+ReOtXn/dYw1JR29H1s3oxuBvd3HgYiYDvopizYyueDnZmlzGtXUqzEPq1fykTs1P6tT8zF2nppZTbxOY3NxcnJycKnzM2dnZeM7NEpjqljFlyhTs7OyM98eOHXtda46pYmJiAEi6nA5AclIiBw7k3uJZ9dcXfV15eP0VYhKz6PnZZr4a4ImnfeUGj5XWqTAvqVfzkzo1P6lT8zNXncbGxpp0Xr1NYNRqNUVFFQ/01GqLV3a91Wj86pbx888/Exoaarxf1RaYmJgYgoODUalUeJw5DCfP0dTHh9DQtpUqqz4JBQI7ZjPom12cySjgqe3ZrJ3RDR8Xu1s+99o6FeYh9Wp+UqfmJ3VqfuauU32ZnoabqbcJjKenJ8ePH6ewsPC6pOHixYuoVCrc3NxqtAxnZ2dcXV2r+UqKqVQqVCoVpT9WjVrZ4H/5OjRxZfNjPen/5Q6OX85h4De72PBIJL6u9iY9v7ROhXlJvZqf1Kn5SZ2an7nq1NQy6u1Q0Pbt26PT6di5c2e542lpaRw5coTWrVvfsjXEHGWYW2li2tBmId2IfyNHNj/Wg+bu9sQm59D3ix3EpzbcrjUhhGgo6m0CM3jwYAA++OADUlJSoGQdmbfeeouioiLj4zVdhrnpDA1zGvXNtPZ0ZMujPWjl4cDpK7n0/Hw7RxOzLB2WEEKIGmR1XUiPPfYYycnJABQVFXHy5EnuvPNOALp06cILL7wAQP/+/YmIiGDv3r0MGDCA1q1bc+nSJdLT0/Hy8mLq1KnGMuPi4njxxRfp3r07zz77rPF4ZcqoLcZp1JLAlNPCw4Gtj/dgyDc7OZqUTZ8vtvPvg93p0vzm3YRCCCGsk9W1wBw7doyDBw9y8OBBDAYDubm5xvtnz541nqdQKPjiiy8YMmQIRUVFHDt2jPT0dIKDg/npp5/KjV3Jy8vj4MGDxMXFlbtWZcqoLca9kKzuJ1fzfF3t2fJYT7o0c+NKbhEDvt7BxlMplg5LCCFEDbC6FpjPP/+cwsKKV2C9dsCsu7s7c+bMITU1lcTERNzd3fHx8bnueS1btmTp0qUVJiSmllFbdCVjYKQFpmKejjasfziS23/czYZTKdz23S6W3hvBmKAmlg5NCCGEGVldAtOxY8dKP8fDwwMPD48bPm5vb19uunNVyqgtehkDc0vOdmr+fqArdy/Yx++HExk3bw9z7+rElM7NLB2aEEIIM5GOCCtj3I1aKQnMzdhpVPw6JYKpnf3Q6Q1MXXyAz7acsXRYQgghzEQSGCtztQXG0pHUfWqVkrl3hfJU71YAPL3yCC/9dRR96ZbeQgghrFa1u5C0Wi2nTp0iOTmZ1NRUNBoNHh4eNG3alObNm5snSmEkLTCVo1Qq+GRMIN5Otrz673He33iaC+l5PNFOkhghhLBmVUpgsrKy+OOPP1i/fj379+8nN7fihcO8vLzo3LkzI0eOpF+/fqjVVjfkps4pbTyQMTCmUygU/GdQW3xd7Zj+y0EW7b/IqUs2rAoswt1RVuIUQghrVKmM4tKlS3z55Zf8+eef5OXlQcmHg6+vL25ubri6uqLVaklPTyclJYXk5GT+/fdf/v33X7y8vLjnnnu47777sLc3bal3cT2ddCFV2dQuzWjsbMv4eXuITixkwNe7+PfBbjQxYf8kIYQQdYtJCUxhYSFz5sxh3rx5FBQU4OPjwz333ENkZCQhISG4uLhU+LyLFy9y6NAhNm7cyNq1a/n0009ZuHAhzz33HHfccYe5X0uDYFzITjKYKhkW4M36h7ox/LudHLiYSeScbax6sDvtvSvedVwIIUTdZNIg3suXL/Ptt9/SuXNn5s2bx8aNG3nhhRfo1avXDZMXgKZNmzJs2DBmzZrFjh07mDVrFs7OzsyZM8ecr6FBkb2Qqq9zMzfmDm6Ev6cDcal59JyzjZ3xaZYOSwghRCWY1ALj4uLCkiVLCAsLq/KF7OzsuP322xk9ejQ7duyocjkNnU62EjALP2c1Wx6LZMyPe9l9Pp0BX+1gyeQIRsuCd0IIYRVMaoFxcXGpVvJS7oJKJb169TJLWQ2RTKM2H28nWzY+EsnwDt7kFem546fdfBsVb+mwhBBCmEDWgbEyMo3avBxt1ayc1oX7uzZDb4CHfjvEa/8ex2CQadZCCFGXSQJjZWQatfmpVUq+v7MT/ze4HQAz153knoX7yS/SWTo0IYQQN2DSGJj09HRmz55drQu5ubnx5JNPVqsMcbUFRhpgzEuhUPDmsPa09LBnxq+HWLw/gbjUXH6f1gVvZ1tLhyeEEOIaJiUw2dnZLFy4sFoX8vX1lQTGDGQadc2a1rU5LT0cGPvTHqLi0+g2eyt/T+9GxybOlg5NCCFEGSYlMO7u7sycObNaF3J0dKzW80Ux6UKqef39G7HzyV6M+H4Xp6/kEjlnG79N6czg9l6WDk0IIUQJkxIYR0dHJkyYUPPRiFvSSQtMrWjv7cTOJ3sxdt4etp5J5bbvd/HF2CAeimxp6dCEEELIIF7ro5cxMLWmkZMtax/qzr0Rfuj0Bh7+LYbn/jhiHIckhBDCciSBsTKykF3tslWrmHd3KG8Paw/Ax5vPMPan3WQXaC0dmhBCNGgmD+L9888/q3UhR0dHRo8eXa0yRJkxMNIEU2sUCgX/HdyOto0cmbrkAH8cSaL359v5c3pX/NxkY1IhhLAEk6dRv/HGG9W6kK+vryQwZiDTqC3nrjBfmrvbM+bH3Ry4mEnXz7ay4r4udGvhbunQhBCiwTEpgXFycmLKlCnVupCrq2u1ni+K6aULyaIiW3qw68nejJobzZHELPp+uYNvJ4QwpXMzS4cmhBANikkJjJubG6+++mrNRyNuSaZRW14rTweinujFvYv2sfJIElMXH+DgxUxmjeiAWiXDyoQQojbIX1srI3sh1Q3OdmqW39eF1wa3hZLBvSO+jyYtt9DSoQkhRIMgCYyVubobtSQwlqZUKnhrWAC/TInAwUbFmthkun22jWNJWZYOTQgh6j2TupBMkZKSwuXLlyksrPg/UBsbGzp27GiuyzVYV1tgLB2JKDWhU1PaNnJkzI+7OZmSQ/fZ21g8OZzhHRpbOjQhhKi3qp3AREVFMWvWLI4dO3bT83x9fdmwYUN1L9fgyRiYuinU15XdT/Vm/M/FK/eO/CGa/w3vwIv926CQn5UQQphdtf6P379/Pw888ADHjh2jadOmUKalxc7ODkrW0AgLCyMoKMg8ETdwspVA3eXtbMu6hyJ5KLIFBgO8/PcxJi/cT16RztKhCSFEvVOtBGbOnDlotVruu+8+5s+fD4CXlxcrVqxg9+7dPPLIIxgMBry8vPjss8/MFXODJmNg6jYbtZKvx4fw5bhg1EoFi/Yn0Ovz7cSn5lo6NCGEqFeqnMAUFRWxe/duAB544IHrHrexseHpp59m9OjRrFmzhpUrV1YvUgGykJ3VeKRHS9Y+1J1Gjjbsu5BBxCdbWBebbOmwhBCi3qhyApOenk5hYSGurq54eXmhVBYXpdWW3yNmzJgxAPzzzz/VjVWUGQMjXUh1Xz//Rux9pjcRfq5cyS1i6Lc7eX/DKQwG2QxSCCGqq8oJTOkYl9LExd6+eE+Y9PT0cn+gfXx8AEhISKhurEK6kKxOc3cHtj3ek2ldmqE3wEt/H+POn/eSlS+bQQohRHVUOYFxdnbGxcWFtLQ08vLycHd3x9XVlYKCAs6cOWM8r/T70kRHVI9xGrUkMFbDTqPih7s68dW4YDQqBb8dukT32VuJTc62dGhCCGG1qpVVdOnSBYCDBw8C0Lt3bwBmzpzJ+fPniY2N5dNPPwUgJCSk+tGKMi0wlo5EVIZCoeDhHi3Z/GgPmrrYcTQpmy6fbuWPw4mWDk0IIaxStRKY0t2lf/31VwAef/xxnJyc2LFjB4MGDWLUqFGcOnUKJycnHnzwQfNE3MDp9MW3MgbGOkW29GDvM73p3dqDzHwtY37czeurTqDXy7gYIYSojGolMEOGDGH37t28+eabALRq1YrFixczZMgQGjdujLe3N0OGDGHJkiW0bNnSXDE3aDIGxvo1cbFj/cORPNGrFQBvrY1l1FzZR0kIISqjWivxKpVKXFxcyh1r164dc+bMqW5c1ZaUlERGRsYNH7ezs6N58+Y3LaOwsJC4uLgqP78m6KQLqV7QqJTMviOILs1cmfHrIf45dpmIT7by29QIwv3cLB2eEELUeWbbC6mu+eSTT1ixYsUNHw8LC2PJkiU3LSMuLo5Ro0ZV+FhgYCDLly+vdpyVYTAYMMg06nrl3s7NCGriwrh5ezibmkuPOduZfXsQD3ZvLlsQCCHETVQ5gUlLS2PZsmVERkbSoUOHOjfLqHHjxrRt2/a641lZWSQmJjJkyBCTy/Ly8sLNrfx/xS1atDBLnJVRdvkQ6UKqP8L8XNn7TG/uW3KAP44k8dBvh9h69gpfjwvB0bbe/o8hhBDVUuW/jjk5OXzwwQcAuLm50a1bN7p3705kZCStWrUyZ4xV8swzz/DMM89cd/y1115jxYoVxgX2TDFt2jSmT59u5ggrT1cmg5EWmPrF3cGG36d14YONp/nPv8dZsDeB/QmZ/DYlgoDGzpYOTwgh6pwqJzAeHh48+uijREVFERMTw+rVq1m9ejUATZo0ITIy0pjQNG7c2JwxV1l2djZ//fUXAwYMwNPTs1LPTUpKorCwkCZNmqDRaGosxpvRl0lgJH+pfxQKBS8O8Kd7C3fumr+XI4lZdPlsK99N6MTEMF9LhyeEEHVKlRMYBwcHnnrqKZ566imys7PZs2cPUVFRREVFERsby4oVK4xjUFq3bs2QIUMqbBGpTStXriQ3N5dx48ZV6nmff/4577//PpSsODxixAhefPFFXF1dayjSiunKTLWVhezqrz5tPNn/bB/uXrCPTaevcPeCfWw/m8qHoztiq1ZZOjwhhKgTzNLB7uTkRL9+/ejXrx8AV65cYefOnWzYsIF///2XM2fO8Oeff1o8gVmyZAlNmjQxLrhnqry8PHx9fcnOziYjI4PffvuNmJgYfvnlF+OWChXJysoqNxPKxsYGGxubSl1bp9MZb4u0VxMYg0FvfExUTtk6rau8HDWseqALb6w9yXsbTvP59jh2nUtjyeRwWrjbWzq8CllDvVobqVPzkzo1P3PXqanlmHWEoE6n48iRI+zYsYMdO3awf/9+YyAODg7mvFSl7dmzh9jYWB599FGTBxzb29vzn//8h3HjxuHk5ATAoUOHePnllzlx4gS//fYbkydPvuHzp0yZUi7BGTt2LOPHj69S/DExMWQX6q/eP3QIG5W0wlRHTEyMpUO4pfFNoElfD/4vKo3d5zMI/2gTb/Vwp2fTGyfOlmYN9WptpE7NT+rU/MxVp7GxsSadV+0E5uzZs+zYsYOoqCh27dpFZmYmALa2tkRERBAZGUlkZCRBQUHVvVS1LFmyBIVCUanuo2bNmjF16tRyx0JCQpg1axbjx48nKirqpgnMzz//TGhoqPF+VVtgYmJiCA4OJrNAD78VLz0fHtoJtapuzfyyFmXrVKWq+10yoaEwMjKXiQv2s+dCBk9tSuWVAW14Y0i7OjWY29rq1RpInZqf1Kn5mbtO9Xq9CWdVI4FJSUlh/PjxXLp0CUoWtevYsSM9evSgR48ehIeHY2trW9XizSo1NZXVq1fTo0cP/Pz8ql1e6arC2dk334zP2dnZbONkVCoVijL5ikatRlmHPryskUqlspo/YG28nNn2RE+eXXmUL3fE8b8Np9l1LoNFk8Np7Fw3fs9KWVO9WgupU/OTOjU/c9WpqWVUOYHJz883Ji+dO3fm6aefpnPnznVy8a3ly5dTWFhY6e6bgoKCCpOwNWvWANC0aVOzxWiKsoN4JXlpeGzVKr4YF0zPVu7M+PUQG06lEPrRZhZNDqe/fyNLhyeEELWqWrOQwsLCiImJYc+ePUyePJlGjRoZp05HRkbi62v5qZ8Gg4FffvkFNzc3Bg0aVOE5BQUFxMfH4+zsjI+Pj/H4M888g5ubG7169cLPz4+srCy2bdvGggULABg+fHitvQ5kJ2pRYlK4H2G+royft4ejSdkM/DqK1wa147XBbaVbUQjRYFRrHZglS5aQnZ3N7t27jVOo//77b/766y8oWa22e/fu9OjRg27duuHu7m7O2E2yfft24uPjmTJlyg3Hn5w5c4bbb7+doUOHMnv2bONxhULBsmXLWLZs2XXPuf/++ys9m6m6Sheyq0vjHoRldGjsTPRTvXny98PMjT7PW2tj2XQ6hUWTw/F1rZuzlIQQwpyqPYjXycmJ/v37079/fyiZQl2azERFRbF06VKWLl2Kr68vGzZsMEfMlbJz507atm3LnXfeecNzbG1tadu2bbnWF4BPP/2U1atXs3HjRs6dO4dSqcTf35/Ro0fTrVu3Woi+vNJxTbKNgABwtFXzw12hDPBvxMPLDrHlTCqdPtzMvLvDGNGxbiweKYQQNcXsG624ubnRrFkzLly4wPnz50lMTLTofPvnn3+e559//qbntG7d2thqVJZGo2HkyJGMHDmyBiM0nexELSpyT4QfXZu7cdf8vexPyGTkD9E817c17w7vgI1aupSEEPWTWRKY06dPExUVxY4dO4iOjiYrK8v4mL29PREREQwYMMAcl2rQ9NKFJG6grZcTUU/24oU/jzFn21k+2nyGrWdTWTI5glaell2DSQghakKVE5isrCxmzpxJVFQUSUlJVwtUqwkLCzOOfQkNDa302ieiYqWzkKQLSVTEVq1i9h1BDPD3ZNrSg0SfSyfs4818f2cnxneq3RlzQghR06qcwGRkZPD7778D0K5dO+Pso65duxpXrRXmVTqLWvZBEjdze7APYb6u3L1gH1HxaUz4eS8PR6bw8ZhA7DWy7oUQon6ocgLj4uLChx9+SGRkJI0ayRoUtUGmUQtTtfBwYPNjPfi/VSd4b8Mpvo6KZ0dcGkvvDSegsbOlwxNCiGqr8gg/FxcXRo0aJclLLSrtQpIxMMIUGpWS/43owOoZ3fB2suHQpUwiPt3KvN3nLR2aEEJUm0xRsCKlXUgyBkZUxpD23hx4ri8D/BuRW6jjviUHuGfBPjLyiiwdmhBCVJkkMFZEWmBEVfm42LHmoe68Paw9KqWCRfsTCP14MzvOplo6NCGEqBJJYKyIjIER1aFSKvjv4HZsfawHrTwciEvNo/cX23lj9Qm0OtN2fxVCiLpCEhgrcnUhO8lgRNVFtvTgwHN9mBzhi94Ab66Jpe+XO4hLzbV0aEIIYTJJYKyIcRq1NMGIanKx0zB/UjgL7wnDxU7Njrg0On20mUX7Llg6NCGEMIkkMFZELwvZCTObFO7HgWf70qOlO5n5Wu5ZuJ97F+0jM18G+Aoh6jZJYKyIcTdqyV+EGbXydGDzoz14Y0g7lApYsDeB0I+2EBUnA3yFEHVXlROYxMRE+vTpw1133WWW88StGQfxSheSMDO1SsnrQ9uz9bGetPSw52xqLr2/2MHba2ONs9+EEKIuqXICo9VqSUpKIjk52SzniVsrnSgiWwmImtKjlQcHnu3LpDBfdHoD/7fqBP2+3EG8DPAVQtQxNd6FVFBQAIBGo6npS9V7epmFJGqBq72GhZPDmT8pDGdbNdvOptLpo80s3pdg6dCEEMKoxhOYqKgoALy8vGr6UvXe1d2oLR2JaAgmR/hx4Lk+dG/hTka+lkkL9zFx/l5ScwstHZoQQlRuM8ekpCSmT58OQFFR8SyFy5cvM3LkyArPz8jI4PLlywD06dOn+tE2cKUtMDKNWtSW1p6ObH2sB++sO8nb606y9MBFtp5JZe5dnRga4G3p8IQQDVilEpiioiJOnjx5y2Nl2dnZMWrUKO67776qRykA0MleSMICSgf4Du/QmHsX7eNEcg7DvtvFoz1a8v7IDjjaVnlTeyGEqLJK/eVp3Lgx//zzD5S0vNx33314e3vz008/XXeuQqHA1taWxo0bo1bLHzhz0MteSMKCujR3Y9+zfXj57+PM2XaWL3fEsTY2mfmTwujWwt3S4QkhGphKZRYajYY2bdoA4OHhwfjx43F3dzceEzVL9kISluZgo2b2HUGM6tiYaUsPcDIlh56fb+c/A/35zwD5OyCEqD1Vbhpxd3fnnXfeMW804qZ0MgZG1BGD23sR83xfHlt+mMX7E3h77Un+OZrEy6G2hFo6OCFEg2C2vp2kpCT2799PSkoKKpWKpk2bEhERgZOTk7ku0eDpZQyMqEPcHWxYNDmcMYGNeWRZDHsTMpmcCO+p4niyd2tZcFEIUaOqncAkJyfz1ltvsXbtWgyG8it22tvbM3nyZJ588klsbGyqe6kGT6ZRi7rorjBferX2YNqSA6yNTeGZP47y17HL/HhXKM3c7S0dnhCinqrWOjCpqancfffdrFmzBoPBQKtWrejfvz89e/bE29ubvLw8vvvuO55++unrkhtRecZp1NICI+oYX1d7/pnehZc6u2KvUbL+ZArBH25i4d4L8rsvhKgR1Upg5syZw/nz52nSpAk//fQTq1at4uuvv2bu3Lls2rSJ119/HY1Gw/r161m9erX5om6gdLIbtajDFAoFE9o5suepXnRt7kZGvpbJi/Yzbt4ekrIKLB2eEKKeqXICYzAYjFOqP/jgAyIjI8s9rlKpmDRpEg899BCA8VxRdaVjYGQQr6jL2ns7sf3xnrw1rD0alYIVMYkEvr+RpfsTpDVGCGE2VU5g0tLSSE9Px9XVla5du97wvEGDBgFw9uzZql5KlJBp1MJaqFVKXhvcjt1P9ya0qQtXcouYuGAfE37ey2VpjRFCmEGVExi9vnhrZJVKddPzShex0+l0Vb2UKKGTheyElenU1JVdT/Xm9SHtUCsVLDt0icAPNvHbwYuWDk0IYeWqnMC4u7vj6OhIamoqJ06cuOF5pZs5+vn5VfVSooRMoxbWyEat5I2h7dn1VC+CfZxJySlkws97mTh/LynZ0hojhKiaKicwKpWK/v37A/Dyyy9z7ty5686Jiopizpw5AAwePLg6cQpZyE5YuXA/N/Y83Yf/DmqLSqlg6YGLBH6wiRUxlywdmhDCClVrHZinn36abdu2cfToUYYPH06vXr1o2bIlBQUFnDhxgr179wLQqVMnbr/9dnPF3GDpZR0YYeVs1Erevi2AMUFNmLp4P0eTshn70x7uDvNlzh1BeDrKelFCCNNUaxp1s2bN+PnnnwkICKCoqIiNGzfy448/smjRImPyMnToUL799ls0Go25Ym6wdAaZRi3qh87NijeGfGWgP0oFLN6fQOAHm/jjcKKlQxNCWIlqr8Tbvn17Vq5cyd69e9m3bx9XrlwxbiXQo0cPWrVqZZ5IxdVp1JLAiHrAVq3i3eEduD2oCVMXH+D45WzG/LibyRG+fHZ7EB4O0hojhLgxs+2FFBERQUREhLmKExUwTqOuVruZEHVL1+bu7H+2D6+vPsGHm06zYG8Ca2NT+GJsEONCmlo6PCFEHSUfhVbEOI1aWmBEPWOnUTFrZEe2Pd6TDo2dSMoqYPy8vYyft4fEzHxLhyeEqIPM1gJz5coVUlNT0Wq1FT6u0Wjw9/c31+Vu6fLly3z99dcVPta0aVMeeOABk8tKSUlh1apVJCQk4O7uzsCBA2nTpo0ZozWNTKMW9V1kSw/2PdOHmetO8t6GUyw7dIkNJ1P49PZA7o3wQyHvfSFEiWonMMuWLePbb78lLi7upuf5+vqyYcOG6l7OZOnp6SxcuLDCxwIDA01OYKKionjiiSfIysoyHvv000959dVXueeee8wWrylkITvRENhpVMy8LYDxIT7cv/QA+xMymbr4AIv3J/DN+BCauztYOkQhRB1QrQRm8eLFvPHGGwDY2tri5+eHnZ1dhed6e3tX51JVNmjQoOv2afLw8DDpuZmZmTz99NNkZWXRv39/unbtSlxcHMuWLWPmzJmEhoYSGBhYQ5FfT7YSEA1JqG/xKr4fbTrNG2tiWXU8mcAPNjFrREcejmyBUn4RhGjQqpXAfPXVVwCMHDmSN998EycnJ3PFZTbh4eFMnjy5Ss/9/fffSU9PZ9y4cbz77rvG4yEhIbz66qv89NNPfPDBB2aM9uZkN2rR0GhUSl4e2Jbbg5rwwC8H2R6XxmPLY1h6IIHv7+xEW6+69zdHCFE7qjyI98qVKyQlJaFUKuts8gJw6tQpPvvsM95//31+/fVX0tPTTX5u6TYI06dPL3d87NixeHh4sGPHDrPHezOyG7VoqAIaO7PlsZ7Mvj0IRxsVW86kEvLhZj7YeAqtTm/p8IQQFlDlFhhlyVxed3f3Opu8ACxfvrzc/f/973/MmjXLpK0Nzp49i4ODw3UDdpVKJR07dmTbtm1kZ2fX2uuXhexEQ6ZUKniidytGBTbmwV8Osu5kCi/+dYxfDl5k7l2hBPu4WDpEIUQtqnIC4+7ujo+PD4mJieTm5uLgUPcG1jk6OjJgwADatWtHdnY227Zt48iRIzzzzDOsXLnyljOJsrOzcXd3r/Cx0uOZmZk3TGCysrLIyMgw3rexscHGpnKLc5Xu4q3T6Yz/aSowyO7e1VC2ToX51Fa9NnO15d8HuvDTngs8/+cx9pzPIOKTLbzcvw2vDPDHRl1/VoeQ96r5SZ2an7nr1NRyqjUG5v777+edd95hwYIFzJgxozpFmV2TJk1Yt25duQG7zz77LP/73//46aefWLJkCa+++upNy1AoFBhKWj2uZTAuKnfjP5ZTpkwpN6h57NixjB8/vgqvBmJiYkhMygTgSkoyBw4cqFI54qqYmBhLh1Av1Va9hmlgyTBPZu3JYNOFfN5ed4pFu+P4v+5uBHrWr1V85b1qflKn5meuOo2NjTXpPJMSGJ1OR2pq6nXHhw0bxr59+/j0009JT09n2LBh+Pj4VFiGSqUyefaPObi4VNyc/OCDD/LTTz9x+vTpW5bh5uZGfHw8er3+ukQlOTn5ptcB+PnnnwkNDTXer2oLTExMDMHBwXheiAWyadK4MaGhAZUqR1xVtk5VKpWlw6k3LFWvgyIN/HYokSd/P8LpjEKmrUnhqd6teHNIOxxsrPvnK+9V85M6NT9z16leb9q4NpMSmEuXLjFw4MCbnvPDDz/www8/3PDx2l4H5kby84tX9bxZy0mpNm3aEBsby+HDhwkJCTEeLyws5PDhw/j6+t6068zZ2RlXV1ezxK1SqaBk7ItaqZRfPDNQqVRSjzXAEvU6MdyPQe28eOaPIyzYm8AnW87yx5EkvruzE/39G9VqLDVB3qvmJ3VqfuaqU1PLMKmzWK1W07hx42p9eXl5Vfc1VcqmTZvKjT8ByMvLY9asWVCymN2t9O7dG4A5c+aUW2H4m2++IScnhz59+pg97psxTqOuP138QphNIydb5k8K5+8HuuLnasfpK7kM+CqKB385SHpekaXDE0KYmUktME2aNGHLli01H40ZzZ8/n2eeeYagoCD8/PzIzs5mz549pKam4uLiwqRJk4znJiUl8c0339ChQwcmTJhgPD5y5Ei+/PJLtmzZwujRowkPDyc+Pp7o6GhsbW25//77a/U1yW7UQtza8A6NOfJiP175+zhf7ojj+13n+PtYEl+ODeb24Iq7uIUQ1qfe/i8/YMAA7O3tiY6OZvny5axZs4bU1FTatGnD3Llzady4sfHc1NRUFi5cyNatW8uVYWtry9dff03z5s05ffo0v/76K9HR0bi4uPDpp5/SvHnzWn1NspCdEKZxsdPwxbhgNj/ag3ZejlzKLOCOn/Zw5897SMoqsHR4QggzMNtmjnXNPffcw4QJEzh06BDx8fEolUr8/f0JCgq6bkO4xo0b89prr1WYkLRt25Z//vmHXbt2cfHiRdzd3YmMjLTI2jelWwloiwo5depUrW6OKYQ16tPGk4PP9eWttbG8v/E0vx68xLpY2RxSiPrApASmsLAQrVZrtrVeUlNTa2VGko2NDZ07d6Zz5843Pc/Dw+Om2w1oNBp69epVAxFWTmkCs2P7NmK++5cPP/yQdu3aWTosIeo0O42Kd4d3YEJIU6b/cnVzyIV7E/hmQggtPereGlZCiFszqQvp8uXLDBgwgG+//ZacnJwqX+zixYu8/vrr3H333VUuoyErXTE9L7f4Z3Btl1ddo9VqyczMJDExkYsXL5KQkMCFCxc4d+4ccXFxnD17lvj4eJKSksjMzKSwsPCG6+4IUV1hfsWbQ743ogO2aiVrYpMJ+mATs7eeMXbPCiGsh0ktMK6urrRo0YKPPvqIr7/+miFDhjB69Gg6d+58y3VNMjIy2LRpE3/++Sc7duxAr9dz5513miv+BqW0BUavL16lcNeuXdx///0WaQbX6/UkJSVx8eJFLl26xKVLl0hJSSEtLY3U1FQyMjIoKKj8WAOlUom9vT329vY4Ozvj5uaGu7v7dV+NGzfGw8NDpkGKStGolLw0wJ87gpvw4C8H2XImlad+P8Li/Rf54c5OdGzibOkQhRAmMimBcXZ2ZunSpfzzzz98+umnrFixghUrVqDRaAgICKB9+/a4u7vj6uqKVqslIyOD5ORkDh8+THx8vPG/6u7du/PCCy8QFBRU06+rXirdC8lQssxyYmIi58+fr5XBxCkpKRw+fJgTJ05w5swZ4uLiyMvLM+m5NjY2qNVqFAoFSqXSeKtUKtHpdOTn5xuTHb1eT05ODjk5OaSkpNy0XLVajbe3t3GqfpMmTfDx8aFZs2b4+PhIciNuqJ2XExsf6cG3O+N58a9j7IxPI+zjLfx3cFte6l+/tiMQor6q1CDe4cOHM2zYMLZt28bSpUvZunUrMTExN10+2M3NjREjRnDXXXfRvn17c8TcYJW2wFBmlcKdO3fWSAJTUFDAwYMHiY6O5tChQyQmJl53jo2NDT4+PsYvb29v3N3d8fDwwNXVFUdHRxwcHFCrb/020+l0FBQUkJeXZ/zKzMwkPT2dtLQ00tLSjN9fuXKF5ORktFotFy9e5OLFi9eVp1ar8fX1pXnz5jRr1oxmzZrRsmXLG64ULRoepVLBwz1aMqJDYx5Zdoi/j13m/1ad4NeDF/nhzlC6NHezdIhCiJuo9CwkpVJJnz596NOnD4WFhRw6dIhDhw6RnJxMWloaarUaDw8PfHx8CA8Pp127djLS30xKx8CUdiFR0o1kri65oqIioqOj2bx5M/v37y/XBaRUKmndujUdOnTA39+fNm3a4Ovra7ZWDpVKhYODg8kDxUu3t0hKSiIxMdH4dfHiRc6fP09BQQHx8fHEx8eXe569vT0tWrTA2dmZK1eu4O/vT7NmzdBoNGZ5HcL6NHO358/pXVmy/yJP/n6YmEtZdJ+9lWf6tOatYe1xsKm3kzWFsGrV+s00dZaPMA/9NV1IACdPnuTKlSt4enpWudyzZ8+yevVqtmzZQnZ2tvF4o0aN6NatG+Hh4XTs2BFHR8dqvgLzUalUeHl54eXldV2XpF6vJzk5mfPnz3P+/HnOnTvHuXPniI+PJy8vj+PHjwOwe/duKGmtadOmjbE7tH379rW+crSwLIVCwd3hvgxu14inVx5h4b4EPtp8hhWHE/luQicGtLX+7QiEqG/kXwsrUjpTorQFxtPTkytXrhAdHc1tt91WqbIMBgOHDx9m2bJl7Nu3z3i8UaNG9OvXj549e9K6dWurbD1TKpXGcTFlk2udTkdCQgInT55k165dZGdnc/bsWXJycjhx4gQnTpwwnuvp6Un79u0JCAggICCANm3aSCtNA9DIyZYF94Rzd5gvD/92iDNXchn4dRQPdGvOB6M64mYv7wEh6gpJYKyIsQWmJIHp0aMHf/75J7t27TI5gdHr9ezcuZPly5cbtyxXKpX06NGDwYMHExISUm8Hv6pUKpo3b46vry9ubm6EhoaiVCq5dOkSJ06c4Pjx45w4cYK4uDiuXLnCjh072LFjB5S00vj7+xMYGEhwcDAdOnTA3t7e0i9J1JARHWU7AiHqOklgrIhxqYqSQbw9e/bkzz//5NChQ+Tm5t50/EhRUREbN25kxYoVJCQkQEkX4KBBg7j99ttp0qRJrbyGukahUNC0aVOaNm1K//79oWTTz1OnThkTmuPHj5OZmcnx48c5fvw4y5YtQ6VS0bZtW4KDg40Jja2traVfjjCj0u0IJoY15YFfDhKbnMMdP+1hfIgPc+4IoomLnaVDFKJBkwTGipR2ISkovm3ZsiVNmzbl4sWL7Nixg0GDBl33nNzcXFatWsUff/xBamoqAI6OjowYMYKRI0fi5iYzLa5lb29vTEwo6W5LTEzk6NGjHD58mJiYGC5fvmxMaH799VfUajXt2rUjODiYoKAgOnbsKF1O9UTv1uW3I/jt0CXWn0zh49GBTO0i2xEIYSmSwFgR4zTqkgRGrVYTGRnJsmXLmD17Nnv27GHSpEl4enpy6NAh9u/fz9atW42rJ3t6ejJmzBiGDBlitm0hGgKFQmGcKj5w4EAoWYOnNJmJiYkhJSWFo0ePcvToUZYuXYqtrS3BwcGEhYURFhaGr6+vfNBZsYq2I5i29ACL9l/g2wmdZDsCISxAEhgrUrqQnaLkVqVSceedd5KSksKWLVvYsWMHUVFRKBQK9GXWivHz82PcuHH06dNHWgXMpEmTJjRp0oRBgwYZW2hKk5lDhw6RlpbGnj172LNnDwDe3t7GZKZTp051akaXMF2YnyvRT/Xmo81neH31CdbGphD4wSbevS2Ax3u1QqWUJFWI2iIJjBUpzUkUGFAoFKhUKuzt7XnuueeYMGECixYtYseOHRgMBnx9fQkLCyMiIoKwsDCUSllZtKaUbaEZMmQIBoOBuLg49u3bx/79+zl69CiXL19m9erVrF69GqVSSfv27QkPD6dz585WO9uroVJXsB3B0yuPsOSAbEcgRG2SBMaK6Mp0IV27um3z5s15+eWXuXz5MgqFQtYxsSCFQkGrVq1o1aoV48aNIz8/n5iYGPbv38/+/ftJSEjg2LFjHDt2jIULF+Lp6UmXLl3o0qULISEhMhjYSlS0HUHox5v576B2vDxAtiMQoqZJAmNF9GW6kG60PL+3t3ctRyVuxc7OzpigACQlJbF//3727NnDwYMHuXLlCqtWrWLVqlXY2NjQqVMn4/nVWaBQ1LzS7QhGdmzMw78Vb0fw+uqS7Qju6kTX5u6WDlGIeqvaCUxhYSGxsbGkpKSQmpqKRqMxbiXQunVr80QpoMw0akUFLTDCejRu3Jhhw4YxbNgwCgoKOHz4MLt37yY6OpqUlBR2795tXCW4devWdOnShe7du0tXUx3m51Z+O4LDiVlEzt7G8/3a8ObQ9thp6ufaSkJYUpU+BTMyMli5ciXr1q3j4MGD5OfnV3ieh4cHnTt3ZsSIEQwcOFAGkFaTcRq1wYBKLX8Q6wNbW1siIiKIiIjgoYceIi4uzpjAxMbGcubMGc6cOcPSpUvx9vYmMjKS7t27ExAQUG8XHLRWZbcjeOr3Iyzan8D7G0/z59Ek5k0Mk80hhTCzSiUwCQkJfP755/z999/Gjf6USiXNmzfHzc0NV1dXtFotGRkZJCcnk5yczJo1a1izZg2enp5MmjSJadOmyQyMKtLfZAyMsH5lx87ceeedpKens3fvXnbt2sW+ffu4fPkyK1euZOXKlbi6utKtWzciIyMJCQmRfw7qkEZOtiycHM6ETj489NshjiVlEzlnGy/1b8P/DWmHrfzzIYRZmPQpWFhYyCeffMKCBQsoLCzE19eXUaNG0b17d4KDg3FycqrweZcvX+bQoUNs2LCBNWvWMGfOHBYvXszTTz/NhAkTzP1a6r2yC9lJAlP/ubm5MXDgQAYOHEhBQQH79u1j586dREdHk5GRYfznwMHBgc6dOxMZGUl4eLhscVBH3B7sQ69WHjyx4jBLDlzk3fWn+ONIEvPuDiXcT1pjhKgukz4FL1++zNy5c+nTpw8PPfQQERERJvXFe3t7M2jQIAYNGsQbb7zBmjVr+Prrr/nqq68kgakC4xgYg0G6DxoYW1tbIiMjiYyMRKvVEhMTQ1RUFLt27SItLY0tW7awZcsWbGxsCA0NJTIykq5du+LsLFN6LamRky2L741gfCcfHlkWw+HELLp+to1XB7bl1UFtZaaSENVgUgLj6urKr7/+SkhISJUvZGNjw8iRIxkxYgQ7d+6scjkN2c2mUYuGQ61WGxfFe/jhh4mNjSUqKoqoqCgSExOJjo4mOjoalUpFaGgovXr1olu3bjdsKRU1b1xIU/q09uTRZTH8dugSb62NZeWRRObdHUqnpq6WDk8Iq2TSp6Czs3O1kpeyFAoFkZGRZimrodFLF5K4hlKpJCAggICAAO677z7i4uLYuXMnO3bsID4+nr1797J3717UarUxmenataskMxbg5WTLr1M788uBizy67BAHL2bS+ZOtvDa4Ha8M9EejktYYISqjyp+Cly9f5o8//mDq1KkygLCWSBeSuJmyg4DvvvtuLly4wLZt29i+fTvx8fHGrQ3UajXh4eH07NmTbt26yb5YtezO0Kb0bePJI8sOsSImkddXn+DvY0nMnxRGOy9JLIUwVZVT/sLCQj744ANGjx7N9u3bzRuVqJBxLyRpgREm8PPzY+LEicyZM4cvvviCSZMm0bx5c7RaLdHR0XzyySdMnjyZmTNnsmnTJnJzcy0dcoPR2NmWZVM7s2BSGG72GqLPpRP60Wa+3B6HwdhVLIS4mSp/CjZq1Ig77riD33//nfvvv5/Bgwfzyiuv4Ovra94IhZFMoxZV1axZMyZOnMjEiRM5d+4c27ZtY9u2bVy4cME4Zkaj0RAREUGfPn3o0qWLbGlQwxQKBfdE+NG3jSf3LTnA+pMpPLY8hj+OJDL3rlCautpZOkQh6rQqt8DY2dnx3nvvsXDhQgICAli7di3Dhw/n888/N64RI8zr6kJ2SAIjqqx58+ZMmjSJL774gjlz5nDXXXfh6+tLUVERO3fu5P3332fKlCl88skn7N27F61Wa+mQ6zU/N3vWzOjOZ7cHYqdWsvpEMsEfbuLXgxctHZoQdVq1PwUjIiJYvnw5ixYt4rPPPmPOnDmsWLGCV155hUGDBpknSgHlthLQSwIjqk2hUNCiRQtatGjBpEmTiIuLY+vWrWzZsoXLly+zceNGNm7ciIuLC7169aJPnz4EBATIzuY1QKlU8GTv1gxq68W9i/ez70IGd/68l3vCm/JAa72lwxOiTjLLXyKVSsW9997L6tWruf3220lISOCxxx7jgQce4OzZs+a4hCi3kJ20wAjzKh0APGXKFL777jtmzZrFiBEjcHV1JTMzk3/++YeXX36ZBx98kHnz5nH27FkZq1EDOjZxJuqJXrw6qC1KBSzcd5GJ/ySz8dQVS4cmRJ1j1n+lPD09mTVrlrFbaevWrYwaNYoPP/xQBgiawdXdqPUyC0nUGIVCQYcOHXjooYf46aefePPNNxkwYAD29vYkJyezbNkynnrqKR5//HF++eUXEhMTLR1yvWKjVjLztgC2Pd6TNp4OJOXqGPztLp774wgFWp2lwxOizqiRtuDSbqXp06dTVFTEd999x7Bhw/jrr79q4nINRmkLDNICI2qJSqUiLCyMp59+mp9//pmXX36ZyMhINBoN58+fZ8GCBcyYMYPnn3+eP//8k+zsbEuHXG9EtvRg79O9GOtfPM39481n6PbZNo4lZVk6NCHqBLN9Cubl5XHkyBEOHDjAwYMHOXjwIElJScbHk5KSeO6551i0aBGvvfYaHTp0MNelG4yr68DIGBhR+2xtbenRowc9evQgJyeHnTt3snnzZg4dOkRsbCyxsbEoFArWrVtHnz59iIyMlAXzqsnJVs1/uroxpVcHHvwthoMXM4n4ZAufjgniwe7NTdrSRYj6qsqfgoWFhfzzzz/GhCU2Nva62Qq+vr5EREQQHh5O06ZN+e6779i9ezfjx4/nqaeeYsaMGeZ4DQ2GsQup5D9jISzF0dHRuNFkWloa27dvZ9OmTcTGxhr/gfnqq6/o3Lkzffv2pUuXLtjY2Fg6bKs1smNjDj7nwdTF+1kbm8JDvx1i9YnLfHdnJzwcpF5Fw1StlXhfeumlqwWp1QQFBREeHm78aty4cbnn9O3bl99//53XX3+djz76iMaNGzNmzJjqvYIGpOxCdrL6sagr3N3dGTlyJLfddhsbN27kypUrbN26lXPnzrFz50527tyJg4MDkZGR9O3bl+DgYEnAq8DHxY5VD3bn481n+M+/x1gek0j0uXQW3BNG3zaNLB2eELWuygmMRqOhd+/exmSlU6dO2Nvb3/J5t99+O4WFhbz22mssW7ZMEphKKN0LCdlKQNRR7u7u9O/fn7vuuouzZ8+yZcsWNm/eTEpKCuvXr2f9+vV4eHjQu3dv+vbtS5s2baQbpBKUSgXP929Df39P7l6wj5MpOfT/KopXB7bl/4a0k/2URINS5QSmcePGfP/991V6bteuXQG4dOlSVS/fIOmM68BIAiPqvtJ9me69916OHj3K5s2b2b59O6mpqaxcuZKVK1fi6+tL37596du3Lz4+PpYO2WpENHNj37N9eHLFYX7cfZ6Z606y7mQKi+4Jp5Wn7G0lGgaLjAR1cXEhIiKC/Pz8GrtGamoqf/75J+vWrePMmTPodDqaN2/OHXfcwbhx40zqjz958uQNW4iCgoL45ZdfaiDyG9NLF5KwQkqlkqCgIIKCgpgxYwb79u1j8+bNREdHk5CQwKJFi1i0aBHt2rWjX79+9OrVCzc3N0uHXec52aqZOzGUoe29eOi3Q+yMTyP04818NS6YSeF+lg5PiBpnkQTGw8ODRYsW1eg1/vOf/7Bx48Zyx9LS0jh48CCrV69m7ty5t1xR1GAwoNNVvO6CJZZX10kXkrByGo2Gbt260a1bN3Jzc4mKimLLli3GiQCxsbF8//33hIaG0rdvX9kt2wR3hfnSrYU79yzcx464NO5ZuJ8NJ68w+45AHGxktqKov0x6d6emprJmzRrGjh1b7ZkEpS0jU6dOrVY5t+Lu7s6UKVMYMmQILVu2RKVSsWXLFt566y2ioqLYtGkTAwYMMKms559/nmnTppU7Zol+e73sRi3qEQcHh3IzmbZu3crmzZs5efIk+/btY9++fdjY2NCtWzf69etHaGiotDzeQEsPBzY/2oO3157k7XWx/BB9jl3n0vh1SgQBjZ0tHZ4QNcKkT8Hc3Fxef/11vvnmG6ZNm8bIkSPx8PCo1IVOnz7NsmXLWLx4Me7u7jWewPzvf/+77tjtt99OSkoKH3zwAefOnTO5LKVSWScSBn2ZMTB1IR4hzMXd3Z3Ro0czevRoLl68yObNm9m8eTMXL15k69atbN26FWdnZ3r27Em/fv1kT6YKqFVK3hzWnj6tPbhn0X4OJ2bR+dOtfDUumHs7N7N0eEKYnUmfgr6+vnz00Ud8/PHHvPPOO8yaNYtevXoRGRlJSEgI7du3x9HR0Xi+wWAgLS2NmJgYYmJi2LBhA0eOHAGgS5cuvPjiizX3im7B2bn4v5FWrVqZ/Jxff/2V77//noKCAlq1asUdd9zBpEmTav0P6NXdqKULSdRfTZs25e6772bixImcOnWKzZs3s3XrVtLS0li1ahWrVq3C29ub3r17069fP1q0aGHpkOuUge28OPBsn+KupFMpTFl8gE2nrzDnjiDpUhL1iknvZoVCwciRIxkyZAhLly5l0aJFbNq0iU2bNhnPsbGxwdXVFa1WS2ZmZrmxIwqFgu7duzN16lSTu21qQl5eHvPmzSM4OJjevXub/LyyG1IePnyYw4cPExUVxZw5c26axGRlZZGRkWG8b2NjU+kuuNJ61Ol0xi4kSmYh3Wh8jri5snUqzKcm6rV169a0bt2aKVOmEBMTw5YtW9i5cyeXL19m2bJlLFu2jJYtW9KnTx969+5No0b1az2Uqtapl6OGfx/owrvrT/HWupPMjT7Prvg0Fk8Oo2MD71KS33/zM3edmlqOwlDFLWWjo6NZt24de/bs4fjx49dd0N7enk6dOtG1a1dGjBhBy5Ytq3IZsykoKOCxxx7j+PHjLF68mGbNbt2keurUKX744QfGjRtHu3btyM7OZtu2bXz00Uekp6fz8ccfM2LEiOuet2/fPiIiImjevDl2dnbG42PHjmX8+PFVit9gMNBlcfG08yFn5jNhxBDCwsKqVJYQ1qyoqIjY2FhiYmI4efIker3e+FiLFi0IDg6mY8eOJq1L1RDsSSrg1e1pXMnXY6dS8HIXV0a2loHRou46fvw4kydPZu/evYSHh9/wvConMGUVFhaSmppKWloaarUaDw8P3N3d60wfdWZmJo8++igXLlzgp59+qnYytXnzZmbMmMGIESP4+OOPr3u8NIHZtGkToaGhxuNVbYGJiYkhMDAI+1fXADD09M+8+OQj9O3bt1qvo6EqrVNZEda8LFGvWVlZREVFsXnzZo4ePWo8rlarCQ8Pp0+fPnTu3BlbW9taicfczFWnSVkFTFlygPUnrwBwX2c/Zt8eiINNw3v/y++/+Zm7Tvft20fXrl1vmcCYpUPUxsaGJk2a0KRJE3MUZ1YJCQnMmDGDwsJCFi5ciK+vb7XLjIiIACAlJeWm5zk7O+Pq6lrt6wFQLhk0YGNjI7981aRSqaQOa0Bt1qubmxu33XYbt912G8nJycaVf+Pi4oiOjiY6Ohp7e3vjNgYhISFW+TOvbp02dXNg9YxI3l1/kjdWn+CnPRfYfSGD3xrwLCX5/Tc/c9WpqWXU6xFdx44d48EHH8TV1ZUFCxZctzdTVR04cAAAT09Ps5RnCn2ZhjJZiVeI63l5eTFu3DjGjRtHfHw8mzZtYsuWLSQnJ7NhwwY2bNiAu7u7cRsDf3//BrWNgUqp4LXB7ejdyoO7F+zjSGIWXT7byo93hTK+U1NLhydEpdXbBGb79u088cQTtGjRgh9++KHS074B3njjDdq0aUPPnj3x8/MjOzubrVu38v7770PJ5pS1RV+mo09hkGnUQtxMixYtmDp1Kvfeey/Hjx9n06ZNbN++nbS0NP744w/++OMPfH196dOnD3379qVp04bzAd7PvxEHnuvLxPl72XT6ChN+3suzfdN4b0QH2UtJWJUqfwomJyfz5JNPmny+l5cXs2fPrurlKu3jjz8mJyeH48eP06tXr+senzZtGi+88AKUDBgaO3YsQ4YM4dNPPzWec/78eRYvXlxh+b1792bUqFE1+ArK0+nLt8BIAiPErSmVSjp27EjHjh158MEHOXDgAJs2bWLXrl0kJCSwePFiFi9eTLt27ejbty+9evXC3d3d0mHXuMbOtqx9qDuv/nuc9zee5uPNZ4g+l84vUyLwcbEzoQQhLK/Kn4IFBQXs27fP5PPNMfakMkrHJpedoVBW2eOlWwZce+5bb71lnDJ+7tw5FAoF/v7+jB49msmTJ9dqN46+3FhrSWCEqCyNRkOXLl3o0qULubm57Nq1i02bNpXbxuCHH36gU6dO9O3bl+7du9frbQzUKiWzRnakewt37ltygG1nUwn7eAu/3BtBnza11z0uRFVV+VPQ29ubpUuXVviYVqvl3Llz/Pzzzxw/fpxnnnmmUuuumMOvv/7KzSZYlZ0h1aFDB44cOXLdrClfX19eeOEFY0uNJenK5FaykJ0Q1ePg4ED//v3p378/aWlpbN++nU2bNhEbG8v+/fvZv38/NjY2dO3alb59+xIeHl5vtzG4I9iHoCbOjP1pD4cTsxjwdRTvDe/Ac/1aN6gxQsL6VDmBsbGxKTdF+FqdO3dm1KhRTJw4ka+++oqhQ4dW9VJVUtkP+LreonHtIN76+sdUiNrm7u7OyJEjGTlyJBcvXjTOZEpISGDbtm1s27bNuI1Bnz596NixY51ZIsJc2no5sfPJXjy87BAL9ibwwl9HiYpP5ceJobjYyd8aUTfV6G+hRqPhoYceIi8vj7lz59bkpeo93TWtSdICI4T5NW3alIkTJ/Lll1/y8ccfM2bMGDw8PMjKymLVqlX85z//4cEHH2TevHnExcVZOlyzcrRV8/PdYXw5LhiNSsHymEQ6f7KVw5cyLR2aEBWq8WaH0j2HDh06VNOXqteMGzka9CisoMVICGtWOt7N39+f++67j5iYGDZv3kxUVBTJycnGbQxatGhB79696dWrV72YyaRQKHikR0si/FwZP28PJ1Ny6DZ7G9+OD+GeCD9LhydEOTX+KVi62FtBQUFNX6peKzsLCUlghKg1KpWK0NBQQkNDefjhh9mzZw+bN29mz549xMfHEx8fz4IFC2jdujU9e/akZ8+eVp/MdG3uzr5n+jBp4T7WxqYwedF+ouLT+Hh0IDbq+tV9JqxXjX4KZmdn89VXXwHg7+9fk5eq90rHwCgovpUuJCFqn62trTFJyc7OZseOHWzfvp2DBw9y5swZzpw5w/z582nTpg29evWiZ8+edXKFclM0crLl3we788bqE8xcd5Ivtsex53w6v07pTDN32WdKWF6VE5jU1FTefvvtGz6emZnJ4cOHSU9PR6lUcu+991b1UqJcF1LxN9ICI4RlOTk5MWTIEIYMGUJmZiY7d+5k27ZtHDp0iNOnT3P69GnmzZuHv7+/MemxtmRGpVTw9m0BdG/hzuRF+9l1Lp2IT7ew9N4I+vvXr52/hfWp8qdgbm4u//zzzy3Pa9q0KS+//DJdu3at6qVEuS6k4vnUSoN0yQlRV7i4uBiTmYyMDKKioti+fTsxMTGcOnWKU6dOMW/ePNq2bWtsmfH29rZ02CYb0bExe5/pzbif9nDgYiaDvo7ivREdeL5fG5lqLSymygmMp6cnX3zxxQ0f12g0+Pj44O/vX++mHFqCsQupJI9J/b0dNr0/wrH9Q5YNTAhRjqurK8OGDWPYsGGkp6cbW2YOHz7MyZMnOXnyJD/++CPt2rWjZ8+e9OrVCy8vL0uHfUutPR3Z/kRPHlkWw897LvDiX8eIPpfO3LtCcbaTFmFR+6r8rrO3t2fQoEHmjUbcUGkLTOkYGDX5ZEY9jPbKPly6zUGhsrFwhEKIa7m5uRmTmbS0NGPLzOHDh42r//7444/4+/sTGRlJZGQkfn51d7aPg42anyaG0r2FO0/9fpjfDl3iSFIWy6d2brC7WgvLkbTZSlydhFQyiFdZ3JWUG/stRemHce06G7VneK005xoMBtDloS/MxKDLxaAt86XLK7m9egxdHgZdIQZ9IeiLMOiLQF9YcluEwVAEukIMBi0YDMbXePWWkuNU/BhKUGpQKNWgUKNQakCpRqFQg1Jz3TGDQoXT5RRyj7VGqXZAobJDobYvvlXZgerq96XHUdmhUNmjUDugUEiLoqg8d3d3hg8fzvDhw43JzLZt2zhy5Iixm2n+/Pk0a9bMmMy0aNHC0mFfp3SqdWhTF8bP28uxpGy6fraNnyaGMjbEx9LhiQZEEhgroTN2IRXfKhUGXHvOJTP6GYou7yDlr86onFpi12IcNo17o3TwReXgi9LWExQqKElsDNocDEXZGIqyMGiz0Zd+X5SFvigDQ2FGyW0mhqIM9IVljhVlGu9j0Fq0PqrLBchOqtpzFWpHFGonFBpnFBonFGonlCW3tz7mjMLGDaWNGwob1+LHZQxBg3NtMhMdHU1UVBSHDh3i/PnznD9/nl9++QUvLy9at26NjY0NHTt2rFOzDyNberDv2T7cNX8vm09fYdy8PbzU35+Zt7VHLbtai1pgcgKTlZXF/Pnzq3whFxcXJk+eXOXnN3Rlp1GrFHoUCrBvdTc2jXuRte9VCi78jS47jpwjH5Fz5KNaikpR3CKhdkChcrj6vdqhuBXD+Jg9CqUNKG1KWkI0Jfc1KMp8X9xCoixXfvlbjIlYueMGHQa9Fgza4lYdgxb02uIWHX2R8bHS7w36Iq4kX8Td1RH0BaDLL2450uUXf2nzSo5dPY6+0HhVgzYHgzYH8quYAZWrQiUKjWtJQuOG0sa1+FbjWi7RKXurtPFAaeuBwtazpEVIEiBr5u7uztChQxk6dCg5OTns2bOHqKgo9u7dS3JyMsnJyezatQtXV1e6detGZGQkISEhdWI7kdJdrV/++xgfbz7DrI2n2HMhncWTw/FysrV0eKKeMzmBycjI4LPPPqvyhXx9fSWBqQbjNGoMxd1HKjsUajvULm1x7/cLBm0u+QmrKDj3O9qM4+hyE9DnJYKhgt24FcqSlgEnFGrn4pYCjXPJB6lLya1r8QemxhWFxqXkw9O13GMKtaNVdqfodDpOHzhAy9BQk/+jNRj0GLR5JclLaatVdvlWLG12+WPaq+cYirLRa7MxlLZoFaYXJ1UGPYbCNHSFaVV7MUoblLaeKG09UNp6oii5VZa5Vdh6Fic9diW3tp4o1HZVu56oUY6OjvTt25e+fftSUFDA3r17+ffffzl16hQZGRmsWbOGNWvW4ODgQEREBF27diUiIgInJyeLxaxRKflodCBdm7kx/ZeDrD+ZQsQnW1g2tQtdmrtZLC5R/5mcwDg4OHDHHXdUqvCcnBw2bNiAVmvd3Q11gXEatcGAWqlHaeNe7nGF2gH7FmOxbzHWeMyg12IoyjSOKzFgQKl2LG4dkf/aK0WhUKLQOILGEaj+9Ner44jSS7rlyt6ml3TfpRuTnav309EXpKIvuAIlY4n0eZfQ512qXAAq+6uJjp1X+S/b8vdVdl4obD2sMlm1Zra2tnTr1g1bW1uCgoI4duwYUVFR7Ny5k7S0NLZu3crWrVtRKpUEBgbSpUsXunbtarFVgO8K8yXIx4U7ftzNyZQcen2+nc/HBvFg97o3jkfUDyYnMB4eHrz33nsmnVtYWMjixYv5+uuv0Wq1KJVK+vTpU504G7xyXUhKA0pb91s+R6FUo7D1qIXoRGUpFApQO6BSO6ByqPwHjsFgKG4NKklm9Mbb4u8NZY8VpqLPv4KhMBV9QSoYdMXJU+4F9LkXTAxYWZzwVJDglH6h8UCdn4ourwlKh8bFg6qFWajVauN2Bg899BCxsbFER0eze/du4uPjiYmJISYmhrlz5+Ln50fXrl3p2rUr7du3r9VxM4FNnNn9dG+mLt7PyiNJzPj1ELvi0/l8bBB2mrozfkfUD2b9C6PX6/n999/5/PPPSUhIAKB///4888wztG/f3pyXanDKTqNWKfQobG6dwIj6S6FQoNA4gcYJlVNzk59nMOiLB2yXJjj5KegLUtDnJ5f/Krj6vaEwHQx64/2b8QaunCyJ0cb9mpYc75LvvYu/7Mvct/WUhMdESqWSgIAAAgICmDJlComJiezevZvo6GgOHz7MhQsXuHDhAsuXL8fFxYWIiAi6detGaGgoDg4ONR6fq72G5fd14b0Np/jvquP8EH2Og5cyWDa1M83da/76ouEw21+MdevW8cknn3Dq1CkAOnfuzLPPPktERIS5LtGgld1KQKU0XNeFJIQpFAqlcTwTzq1Neo5BX1Sc6FSU4ORdNn6vy0umMOcSKl1mcZdlydgeXWasKZFdbeG5NrkxfpUkQfbeKGzcpEurRJMmTRg1ahSjRo0iJyeHffv2ER0dzd69e8nMzGTjxo1s3LgRtVpNYGAgERERhIeH06xZsxrrSlYqFfxnUFs6N3Pl7gX72HM+g/CPt7Dk3ggGtav7i/YJ61DtBGbXrl18/PHHHDhwAICAgACeeeYZ+vXrZ474RAldmXVQVEo9ShsZHCdqh0KpQeXgg8rh5mt86HQ6Dhw4QKeQYBTa9Apbc4q/LhcnPvmXSx6/AhiKW4IKUiDjmAlBqVHaNSqX3CjtvFHZl79f+r1C49wgxn05OjrSu3dvevfujU6n49ixY+zatYvo6GguXbrEwYMHOXjwIHPnzsXLy4vw8HAiIiIICQmpkdaZIe292ftMH8bN28O+CxkM/XYn79wWwEsD/BvEz0PUrConMEePHuWjjz5i27ZtADRr1ownn3ySUaNGyRuzBuj1V9eBUSv1KEwYAyOEJSiUKlT2xcmEKQx6bXGXVmlCUza5yb+MLv9yuccMRcXrEOnzEotn2plCaYvS3vv6bqxyLT5XW3kUauvfbVmlUhEUFERQUBD3338/CQkJ7N27l3379nH48GGSk5NZvXo1q1evRqVS0bFjR8LDwwkPD6dly5Zm+zve0sOBbY/35LFlMfy4+zyv/HOc6PPp/DQxFBc7y08FF5Wze/duduzYwUMPPYSdnWVnM1Y6gYmLi+Ozzz7j33//xWAw4OXlxSOPPMKdd95ZJ9YlqK905daBkS4kUX8olGpU9o1R2Tc26XyDrqCkS+tymQTn+sSn9MugzQV9Afqc8+hzzpsWk9qpwuRGaedt7MZS2nqV3Daq81t5KBQK/Pz88PPzY8yYMeTn53P48GFjQnPp0iXjQOB58+bh4eFhTGZCQ0OrPU3bXqPih7s60b2FO0+sOMyKmESOJm5l+X1d6NhEtiCwFpcuXeK9WbPIL9IRFhZm8ck5Jicw+fn5vPvuuyxbtgytVouzszPTp0/nvvvuw97e+v9bqQlarbbaU8h1Oh06nQ6tVosaPWr0qFSgV7nJ9PQqKlunBoPBhGcIU9RevarAtjEK28aoXOFWc1v0RTllEp6Uki6t0kQnpSQJuvo9hiIoyoei85BlYsKjcS3TjeWF0qZRmXE8jVDalnxv74XSxgOF0rQZOTVVp2VnNU2fPp2LFy9y4MAB9u/fz+HDh0lLS2P9+vWsX78epVJJ69atCQoKIiQkhICAAGxtq7ZI3f1dfAlu7MDd8/dxOjmLyM828+2EEMaF1N7Ub/n9rxq9Xs/szz7moGs451zaM/T0aXr06AE1UKemfrYpDCZe7cKFCwwcOBBKNiibOHEiLi4uJgfk7OzMnXfeafL51mzfvn1ERETwzjvv0KpVq2qVZTAYyMjIoFBlx65z6aj1hTTXnSegbXNUjs3MFnNDUlqnrq6u0t1pRvWhXg0GQ/GKzrqC4v26dIWgL8CgK8CgL9nPq+R74y2V/YOtKF6RWmWLQmlbvEK1yrZ4RWqVDQqlLQpV8XGUNmRm5dZqner1erKyssjIyCAjI4O8vLxyjyuVSpycnHBxccHFxQVHR8dKx1ag1bHvQgYpOcUrXLfxdCSgsRPKWtrLzdrfp5aQmHCGcwkpJDv4oVcoaW6TTae2/lADdXr27FleffVV9u7dS3h4+A3Pq9IYmPT0dL7++utKPcfX17fBJDA1ofRPpAJQKAzFS+8LIcxKoVCAoniLC1MYDIaSLSoKriY7pcmNrhCDvjQRKjlekvCUfm8g65bXsENBYY5tcXJTktgUJznFt1x7q1BV60NEqVTi6uqKq6srlKzrlZGRQVZWFpmZmRQWFpKZmUlmZiaUjLVxdnY2JjT29rdeKNNWraJbC3dOXM7mVEoOp6/kkJ5fRISfK7ZqWS+mLjHo8slNPc2Fi9lolbboS2b/Feos33pVqZV4hw8fXuULeXg0vAXVBg0adNPs0RQ6nY6DBw9y0daHF07swzU/mQcKVnLH4+OxbdLbbLE2JKV12qlTpzq1OZ61k3q9teIp6Veum6Glu3YdnpLuLoP21glOccFAaau70rZ4hWUbt+KtJGzcUdq4l2wv4V5839a9eFsJG/eS7Sfci7cMuUXiYTAYSEhIICYmhkOHDnHkyBFycnLKnePm5kZQUBCBgYEEBATccrr2ipiLPPjrIXJSdPgU2jHv7lB6t/Y07XVXgbxPb82gzacwaSu5p+aSGfc3Xx8M51SKJ1ktQthK8fILvTnE+xMmQA3U6b59+3j11VdveV6lVuL95JNPqhtXg6JWq1GrqzdTXaFQFL8hFCq0KNEZQKXUYePYqNplN1SldapWq+UPmBlJvZpCDTZ+4OJn0tnawhxi9m6iQxsvKEwtMzi5zEDlvMslSVAS6PKL99jKz4H885TuhKYz5WIKZUly41Fmw1CPqxuJaor3QGuscaVJmCtDu/VHrxpNfEImMcfjOXT4OEePHi23zQElG/l27NiRwMBAOnbsSOvWrcu9PyaENSeoqTvj5u3hWFI2g76N5u1hAbw8wB+l0vxdPPI+Lc+gK0SbeRJtxnG0qfspTNpCYXI06Au4kmvP1zs7cy7dDY1Giar9ILRnilve0oo0xs8gc9epqZ9t8gloJcpvJXD9XkhCiPpHobJDb9MEjeetNx4t3V6iePXkNPQFacXbSBSklmw5kVr+fmFayXYTqaDLK95YtOAKuoIrpiU8JVyAnkDPNkq0bV05m+7DiRRPTiY5cjpJTWZmJjt37mTnzp0A2NmoaNeqER3aNqVju5b4t26Fv5M7O+735cl/U5h/4Aqv/nuczaevsOCeMNnVugqMW40Uphf/nPOvoM+7WLzJb27xrS73IvrcBHQ554u3F7nG8fS2fBfVkew8PS4uLjzz3PMM+O3qnmvZOssPY5AExkpcnUaNbCUghLhO6fYSSo0TULnJAwZtXrmExnDt94UZJRuKluymXlT+FoMODHrUujTaOqfR1rk4BK1eQXyaG6eueHAyxZPTV9zJLbTh0IkkDp1IAvajVOjxc82ktUcad3ik4d8ohP9duZ81scmEzFzK1+3m08MzCYXaCYXaEYXGCYXKHoXKzvhFme9vdKz0vkGhQVUQhy7LBdS2oFSDQl28lUWZW5Rqs6/2bDDoS8ZMFV29NWjL39cXFQ8Y1+YWf+mKbylzX6/NAW1u8a73RRnoC9KMG8HqC9NKtv8wPQ1VaFxQuwagdgsk0yacFVvT2bh1D3q9Hn9/f1555RXi8jRk5l+dlZdjsHxiKQmMlbi6lYAetap492khhDAHhdoeldq+yhuLFu+sXnFy416YQaeS5EdXkM75xCxOnMvnRIKOk5dUpOeqOZfuxrl0NzadKU68BjguY1fjwSTixdgjj/NMo8U80+QXlArzDBxtDFwxZYcLFOUTHKqQ0Bh0JYlKERj0JjzBjBTqknFPHqgcmqJy8EXp0BSVQ1OUDr7Fx5xaorT3IT09nWXLl/PPP/9QVFQEwODBg3nooYewsbFh7obibYIcNApyiwzkKezRFWajsqneGkHVIQmMlShdiRdArdbI9D8hRJ1Qdmd1brHdBIAH0Knke4PBQEpKCidOnODEiRMcP36c06dPQ04OXc/+RYx3Ty64tOOjlHtYemkg97kdJchXQ+um9rRorMFeo8Wgy8egy4eS2xvdNx7TF6AtyEGlNGAwaEGvLR43VKHiWWZQVJkGjcpRqEBZMvNNqUGhKLlVO6JQO1z9UjmUv1/yuNLGHYWNW/Gg7bLf27qD6uYzwgwGA0ePHuXffxexY8cO4/orgYGBTJ06lYCAAOO5G0+lADAswJvlMUkUKW3JSD6Jh29YDVXMrUkCYyWudiHpUanr9qqfQghhCoVCgZeXF15eXvTq1QuAoqIizpw5Y0xq/jyzj+12IVzQNOHDDGfCj2/AM/84AD4+PrRp08b41bp161uuT1a6Z1do6NVxRcXr/+hAry2X1BiMt8VdPVRlkTaFsuIERampkW4qUyQkJBgHWp8/f7VbqH379kycOJHw8PByiU+hVs+2s6kAjA/xZXlMEoUqW9Ivn5EERtza1S4k0GgkgRFC1E8ajYb27dvTvn17AF4AdsReYPLiGM5mOhLVbCRh+cdpen47ly5d4tKlS8Y9+SiZMdusWTNatGhB8+bNjV8326yyeP2fknEvtfIqa5der+fUqVPs2bOH6Ohozpw5Y3zM1taWvn37ctttt9GmTZsKn7/7fDo5hToaOdrQp03xkihFShuuXD6DaXva1wxJYKyETn91N2q1xvKDp4QQorb0aOdHzMtNeGx5DPP2XGCfXQdsB3bjvxGO5CXFc/r0aU6fPs2lS5dITU0lNTWVgwcPliujUaNGtGjRAj+/4instra2+Pn51csVeQ0GAxcuXODw4cMcPnyYQ4cOkZGRYXxcqVQSGhpK79696d69O46Ojjctr7T7qF8bTzwdSv6BVii5dDmpZl/ILUgCYyXKTqNWayy7A6gQQtQ2R1s1P90dxqB2Xjy6LIaoc5lMupzL1+O78+K4cQDk5uZy/vx5zp07Z/yKj48nNTWVlJQUUlJS2Lt3LwArV66EkkVamzZtio+Pj/GrtFurUaNGdX6TYp1Ox+XLl4mPj+fUqVOcOnWKkydPkpVVfhFEBwcHQkNDiYiIoFu3bpXaCmjjqSsA9PdvhJ1GhRotWtRcTMs0++upDElgrISuZPC6wiAJjBCi4Zoc4UePlu5MXrifqPg07l6wj3+OXebzsUG4ODiU634qlZ2dbUxo4uLiOHbsGNnZ2aSkpJCbm2v84L+WQqHA3d3dmNB4eHjg5uZ23Zerq2uNJTparda4L1VGRgbJyckkJiaSlJREQkICFy5coLCw8Lrn2djY0L59e4KCgggODiYgIKBKi5/mFGjZEVc8/qW/f/EKyQ4KLZkGNYkZ+WZ4hVUnCYyVKNcCYyO7fwshGq7Wno5seawH76w7yVtrY5m/9wLbzqayYFIYPVpdv22Nk5MTHTt2pGPHjuUG8Wq1WpKSkrh48SKXLl3i4sWLJCUlkZycTHJyMoWFhcYuqRMnTtw0JhsbGxwcHK77srW1RalUGlepVSqVqFQqVCoVOp2OwsJCioqKKCoqorCwkMLCQgoKCowJS3Z29i3rQ6PR4OfnR+vWrWnbti1t27alZcuWZkmqFuy7QL5WTxtPBwK8i6dMO6v1ZBZBck4tTwu/Rr1PYPR6Pfv27SMhIQF3d3e6du2KnV3lWjDMUUZ16Q1Xx8BobGUNGCFEw6ZWKXl9aHsGt/PinkX7OJuaS+8vtvPyAH/+b0g7kzaFtLW1NQ7yvZbBYCAzM5PLly8bE5r09HTS0tJIT083fmVkZBgTkcLCQtLT083+WstusOnh4UGTJk2MX82bN6dx48Y1si2CwWBg9tazADzeq5VxrJCrrZKEIkjNq/0ZVGXV6wQmLi6Oxx57rFzToLu7Ox999BE9e/astTLMwTiN2mBArbn5gCshhGgoerTy4MCzfXl8RQwL9ibw7vpT/Hk0iXkTwwjzc61yuQqFwpg0tG3b9obn6fV6cnNzyc3NJScnh7y8PHJycozHCgsL0el0FX6p1Wo0Gg02NjZoNBrj97a2tsZru7q64uTkhFJZ+8nChpMpHE3KxslWxbQuzYzHXe1tIBvSimyLp5hXZYE/M6i3CUxRUREPPfQQcXFxNG/enNDQUOLj4zl48CCPP/44f//9N02b3nzVSXOUYS7GadQYUNtKAiOEEKVc7TXMnxTO7UFNePi3GGIuZdH1s638d1Bb/jOoLRpVzX3AKpVKnJyccHKy3Iq0NeWzktaX+zo3w9X+andUIycHSM4nXeeEPvcS2PtaJD7Ltv/UoL///pu4uDh69OjB33//zQcffMAvv/zCQw89RG5uLnPnzq2VMsyldBq1AgMa2/r3iyKEENU1LqQpR17ox7gQH7R6A2+siaXbZ1uJuWTZ2TLW6HRKDn8dK54m/Xiv8ntrNXIuHoeZbXBEl5tgkfiozwnM5s2bAXjqqaewsbm68Nujjz6Kg4MDGzdurJUyzMU4BsZgQC0JjBBCVMjb2ZZfp0SweHI4Hg4a9idkEvHJFt5ZF0uRzrKDTq3JF9vjMBhgWIAX7b3Lf+Z4uxSPw8w2OKDNOX+DEmpevU1gTp06hY2NDSEhIeWO29nZERQUREJCAnl5eTVehrkYp1FjQGNr+vx9IYRoaBQKBRPDfDnyQj9GBzamSGfgv/+eIPzjLUTFp1k6vDovK1/LD9HnAHiq9/Vr7fq4OwNQoLQjNy2+1uMrVW/HwKSnp+Pp6VnhwCdvb2/jCHN7+xtPSa5uGVlZWeVWP7SxsSnXkmMKna54BzGttgBKBvGqbJyMx0Xlldad1KF5Sb2an9Rp9Xg5alg2JZxF+y/y3J/HOJyYRZ8voxjn78CXbfPxcJQ1tSry5fazZOZradfIkYFtPK57/zVyKl4NvkhpS1rKSVzM/D41tZx6m8AYDIYbjtounQp2q0qqbhlTpkwpN9167NixjB8/3qT4r3XpYnE2rMBAwqUUDhw4UKVyxFUxMTGWDqFekno1P6nT6glUwpKh7nx2IJM/z+Tx28lcNr2/iecjXBnYzK7ebSVQHWn5Ot5eexmAu/01HDp08Lpz0hOLF7ArUtmSEBdLZsn701zv09jYWJPOq7cJjKOjI5cvX67wsdJ5+s7OzjVaxs8//0xoaKjxflVbYGJiYvB0dwIyAAP+bduVK1dUTmmdBgcH18jaCQ2V1Kv5SZ2aV7/usD72Mg8u3c+5LB0vb0tjRAdvZt8eSAt3WSAU4PEVh8kpMhDu68Krt0eiVF6f3BV5psPGHRQqbdHrCgkODjbr+1SvN22sUr1NYFq1akVcXBxnz56lVaurI6gNBgPHjh3D09PzlglMdctwdnbG1bXq6xCUZdBd7ULSaDTyx8wMSlfDFOYl9Wp+UqfmM7CdN4uHe/NPiiPvbzrN38cus/5kCi/29+elAW1wsKm3H4u3dCQxi293Frf2fzwmEI2m4rrwciruWShS2ZKZmW58b5rrfWpqGfV2EG/37t0B+PHHH8sdX7lyJSkpKURGRtZKGeai1RYPFlZgqNJ+FkIIIYrZqhS8ObQdB57tS982nuRr9by1NpaAWRtZuj8Bg3Hl84bluT+OoDfAHcFN6Num0Q3P83AoXhNGp9SQmpmPwWCZ2V319pNwzJgxfP755yxdupSMjAy6du1KXFwcixcvBuDee+81npuens7atWvx8/Mrl5RUpoyaptPmA/aSwAghhJl0bOLMxkci+e3QJZ7/8yjn0vKYuGAfX+yI47MxQdVaydfa/HssidUnktGoFLw/suNNz3W106DAgAEFSflOGPJTai3OsuptC0zpcv8ODg6sWrWKt956i59//hmdTscLL7xQbgzJpUuX+O9//2tMTKpSRk3TlcxCwiAJjBBCmItCoWBCp6Ycf6k/bw1rj71GydYzqUR8uoUZvx7kUqZld1yuDRl5RTy2/DAAT/ZqhX+jm6/2rlQqcCjp5UkpdEWXe6E2wrxOvf4k7Nu3L//88w9//fUXFy9exN3dncGDB9OhQ4dy57m5uTF+/HiCgoKqXEZN0+mKf4mkBUYIIczPXqPitcHtuK9zM176+xiL9yfw3c5zLNh7gad6t+bF/m1wd6jcJAxrYDAYePi3Q5xNzaWlhz2vDW5n0vOcbRTk5MEVrQv63ASgmQnPMq96/0no4+PDgw8+eMtz3nnnnWqVUdOM68BIAiOEEDWmmbs9iyaH82iPFrzw1zF2xqfx3oZTfLUjjhf7+/NU71Y42tafv8Hzdl9gyYGLqJQKFk+OKLfn0c242alIzNORqnUu2U6g9hOYetuFVN/oyy5kJ7MRhBCiRvVq7cmOJ3qycloXgpo4k5Gv5dV/j9Pmfxv4fNtZCrXWvy1BbHI2j68oXrvlraHt6d7C3eTnetgXt0Zl6J3QW6gLSRIYK6ErmUaNtMAIIUStUCgUjA5qwoHn+jJ/UhitPBxIyirgiRWHafveBuZsPUtuodbSYVZJVr6WifP3klOoo7+/Jy8N8K/U8z1LVuPN0jmiz71YQ1HenCQwVkKnKwJAAZLACCFELVIpFUyO8OP4S/35clwwTZxtOZeWx5O/H6bFzPXMXBtLWm6hpcM0WV6RjtFzo9mfkImng4b5k8JQVbBg3c2UbuiYgwNabGso0puTBMZK6LXFvxwKg166kIQQwgJs1Eoe6dGSM68O5MtxwbTycCAlp5DXVp2g+cx1PP/HERIyameD36oq1OoZ99MeNp2+grOtmn8f7I6va+VXIfZyKX5OkcoWRcd3ayDSW5MExkoUaYuM32s0pg2yEkIIYX72GhWP9GhJ7Mv9WXRPOCE+LmQX6Pho8xlavbOeexftY/vZ1Dq3IJ5Wp2fSwn38e/wy/9/evcdFVSb+A//MhUEU5CKKoBikHe8gXlDygpdcL2tWuKKlqWvmrvkrkywvr9V9pa6bVts396XWtmWGmRfUdREzKc1LuUZ5N9AE74EKCMwwwDAzz+8PmdGJ2wAzMAc+79eL1wvOOfPMc54ZznzmOc95joebEkmzItGvg0+tyvJvcb/XxaB0R0FBgYNrah+ei5AJo+UUEgfxEhG5BLVKiWd7t8PkiCDsT7uDtw5expGMXGz+6RY2/3QLPdp64U9Rj2Bqn/bwsfPqHmfJLCjGpPifcDQjFxqVEv/5Yz8MfrRVrcuzzMZbqnJHfn6+A2tqP/bAyIEwwmS6P+Kdl1ETEbkWhUKBMV0DcHjuQJyYNwgzI4Ph4abE+SwtXt59HkFvHsDMradx4tq9BumVOXQ5GxH/OIKjGbnwcldj14y++F3nNnUq07cskJUq3aHVah1U05rhJ6EMKE06GMX9rKkAe2CIiFxVZAdfRHbwxbvju2PzTzfxwfFruJClxcaUG9iYcgOP+bfAsxH3e226BlR9Q+G6ytUb8NY3l/Hu4XSYBdAz0AsJ0/tCau1Z57L9yib1M5T1wLRoUfXsvc7AACMDClMBTJYAowCUSnacERG5Mh8PN/y/QaGYOzAE31+9hw+OX0XCmUz8kl2I5cmXsDz5EroGeGJc1wCM6xaAx0N8oVY55tiuKzHi/45k4O1v01FQfP8y7+l922P9hJ4Ou9u2b/MHPTAFBQUICgpySLk1wQAjBwo1hEcwoAVUippd6kZERA1HoVBgYKgfBob6YX2MEf+9kIUvTt3CVxfvIvW2Dqm3dXj723R4uasxMNQXQx5thUGhfggLbGn3rLgAoDcYsT/tLhLOZmLvz7ehLbkfXHoGeuFvY7pgXLcAKBz4+WE7BibHYeXWBAOMDJg0QVD6+gJ37tX4Wn0iInINXs3UmNKnPab0aY+8olJ8lXYHe1NvY1/qHeTqS7E/7S72p921bh/s0wzd23oh2McDbTzd0cZTg2ZqFQwmMwwmM/KKSpF2534IunS3EAbTg9mBO7ZqjuWjO2Nyr3ZQOuFzw3IKSSiUyM7XObx8ezDAyITRfP+NyQBDRCR/Ph5umBTRDpMi2sFkFjiXWYAjGTk4kpGL/127h1v5xbiRd//HXiF+HpjQMxATwgLRv4OvU4KLhYebChqVAgaTwCNdyt8IuT4wwMiEqSzAqDn+hYioUVEpFejVzhu92nnjlcGPAgDu6Q24kKXFz7d1yNKW4I7u/k+J0Qx3tRIalRItNCpIrT3RNcATXdt4IcTPw6GniarTqoUGmQUl6N6nP3D3Sr09rwUDjEwYy7oGnZmoiYjINfg212DQo60wqA5ztTibr4cbMgtKcK+oFH4N8Pz8Oi8TJvP9uQPYA0NERK7AMg7mnr602m2dgZ+GMmEJMCoHXWZHRERUF5Yrke4VMcBQFSxjYHgZNRERuQLLbLy57IGhqrAHhoiIXInlFFIue2CoKhwDQ0RErsQyG28ee2CoKqayG4A5aqppIiKiuvCznEJqoB4YXkYtEyZOZEdERC5kSMdWeP/p7pD8mwP6W/X+/AwwMmEuO4XkpuadqImIqOH1DGyJnoEtYTKZcPp0/QcYno+QCcspJPbAEBERMcDIhuUeXSoO4iUiImKAkQuz4CkkIiIiCwYYmbDOA8MeGCIiIgYYuTDzMmoiIiIrfhrKRFkHDNxUPIVERETEACMTlh4Y3kqAiIiIAUY2TOyBISIismKAkYkHVyHxJSMiIuKnoUxYxsCo2QNDRETEACMXDDBEREQPMMDIhOBEdkRERFYMMDLBHhgiIqIHGu3dqIUQSElJQXJyMjIyMmA2mxEcHIyYmBj06tXLrjKuX7+OV199tcJ1nTp1wpo1axxc68qV3QqJPTBERESNOcAsWLAAe/fuLbd827ZtmDp1KpYuXVptGcXFxbhw4YKTalgz1onsGGCIiIgab4ApLCxEZGQkRo4ciZCQEKjVahw5cgSbNm3C5s2bMWbMGPTt29eusqZNm4bx48fbLGvevLmTal6xsvzCeWCIiIgac4B555134OnpabPs8ccfh1KpxMcff4zz58/bHWDatm2Lnj17Oqmm9jELBQBAzR4YIiKixhtgfhteLCRJAgC0adPG7rIOHz6M7777DiUlJQgNDcXTTz9td/hxFEsPjEbdaF8yIiIiuzWpT0MhBHbu3ImgoCAMHz7c7sedOHHC+vuPP/6IHTt24KWXXsK8efOqfJxWq0V+fr71b41GA41GU6M6m0ym+3Uv+1upVFiXUe1Y2o/t6FhsV8djmzoe29TxHN2m9pbj0gEmPT0dr7/+ut3bx8fHo0WLFpWuX7VqFc6cOYNPP/0UzZo1s6vM7t27IyYmBo899hh0Oh2OHTuGHTt2YP369YiMjERUVFSlj502bZrN88TExOAPf/iD3fvzMJMAoACyMn/F6dOna1UG2Tp37lxDV6FRYrs6HtvU8dimjueoNr106ZJd27l0gNHr9TW6Cqiy1GYymfDmm2/iv//9LzZs2IDevXvbVV5ISAgSEhKgVD6YLmfEiBHo0qULli1bhsTExCoDzGeffWZzyXZte2Duvynuj4HpGBpq92XgVDFLm/bs2RMqDop2GLar47FNHY9t6niOblOz2WzHVi4eYDp16oSEhAS7t6+o90Wv1yMuLg4pKSn497//XaOxK5WFjTFjxmDZsmW4detWlY/38vKCt7e33c9XFVEWYNw1bvyncxCVSsW2dAK2q+OxTR2Pbep4jmpTe8tw6QDj4eFRp6t/cnJy8Kc//Qk3btzAp59+6rAriW7evAlUEpicxTqI182lXzIiIqJ60WhvJXDt2jVMnjwZmZmZ+Oyzz2oVXj7++GP8+OOP1vsQAcDFixexcOFCAEBkZKRD61wVc1kPDG8lQERE5OI9MHWxcOFCXL9+HW3btsXixYvLrX/qqacwffp0AMCVK1fw2muvISoqymbQ8Pfff481a9bAw8MDQUFB0Gq1uHPnDgCgY8eOiI2Nrcc9KjuFxB4YIiKixhtgDAYDACArKwtZWVnl1vfv39/6u+WWAe3bt7fZ5sUXXwTKgkx6ejoAoFmzZhgzZgzeeOONep2NVyjuBxg3BhgiIqLGG2Defvtt6PX6Ste3bt3a+ntoaCgSEhLg4+Njs82AAQMwYMAAlJSU4ObNm1AoFAgODoabm5tT6/5b5odOYblxIjsiIqLGG2A6duxo97bNmjWrcoyMu7t7jcpzNPOD/AJ3Tf2GJyIiIlfUaAfxNiYPBxjezJGIiIgBRhaMpgeT+mjYA0NERMQAIwfGh2YY5s0ciYiIGGBk4eEAwzEwREREDDCyUGp8EGDc1BwDQ0RExAAjA8aHbmzFU0hEREQMMLJgND4IMGXz2RERETVpDDAyUGoZAyMEFEwwREREDDByYCq7jFoBUe22RERETQEDjAx4tGgBAFCr+HIRERGBAUYe3DQagAGGiIjIip+IMmAqO3Ok5PgXIiIigAFGHiw3o1YpGWCIiIjAACMPZvbAEBER2eCsaDKgUgJd2rSAlztvI0BERAQGGHlo76nG+QXRUKl4GwEiIiLwFBIRERHJEQMMERERyQ4DDBEREckOAwwRERHJDgMMERERyQ4DDBEREckOAwwRERHJDgMMERERyQ4DDBEREckOAwwRERHJDgOMizMYDEhISIDBYGjoqjQabFPnYLs6HtvU8dimjtdQbcoA4+IMBgN27drFfzYHYps6B9vV8dimjsc2dbyGalMGGCIiIpIdBhgiIiKSHXVDV6AxKioqAgCkpqbWuSytVovi4mKcPn0aXl5eDqgdsU2dg+3qeGxTx2ObOp6j29Ty2Wn5LK2MQggh6vxsZOPzzz/H1KlTG7oaREREsrV582ZMmTKl0vUMME6QnZ2Nr776CiEhIfDw8Gjo6hAREclGUVERrl69ilGjRsHf37/S7RhgiIiISHY4iJeIiIhkhwGGiIiIZIcBpoEVFBRAp9M1eBmNSVFREfLz8+tURl5eHsxms8PqJHcGgwG5ubl1bhMhBLKyspCVldXkJxIzmUzIzc1FaWlpncoxGo24d++ew+old/fu3UNxcXGdyigoKGjy78+H5ebmIisrC0ajsdZl6HQ6h39OMcA0kH379mHkyJHo168f+vTpgyeffBLHjh2r9zIakzNnziA2Nha9evVCZGQkoqOjsWXLFrseW1paisTERLzwwguIiIhA//79ERYWhtjYWBw6dMjpdXdVWVlZmDt3LiIiIhAVFYXIyEisXr261gf3LVu2IDo6GtHR0fj5558dXl850Ov1WL58Ofr27YuoqChERERg/vz5yM7OrlE5qampmD17Nnr16oUBAwZYX5uCggKn1d2VffLJJxg0aBAGDBiAXr16YcqUKUhLS7P78ZmZmVi8eDF69+6Nfv36ISwsDE888QTi4+Ob5JeZy5cv45///CfGjx+PqKgoREdHIyMjo8blfP311xg9ejT69OmDPn36YMyYMTh48KBD6shBvA1g3759mD9/PgDA09MTZrMZer0ebm5u2LhxI/r161cvZTQmly5dwqRJk6DX6+Hu7g53d3frgfwvf/kLnn/++Sofn56ejrFjx1r/9vHxQUFBgfXAtWLFCsTGxjp5L1yLTqfDM888g+vXr0OtVsPLy8v6TX/cuHF49913a1TerVu3MG7cOLRp0wZXr17Ftm3b0KtXLyfV3nXNnj0bhw8fhkKhsL7PTCYTJEnCzp07odFoqi3ju+++w5w5c1BSUgKlUgkfHx9otVqUlpbi/fffx+jRo+tlX1zFunXrsHbtWgCAt7c3ioqKYDAY4O3tjZ07dyI4OLjKxxcWFmLcuHH49ddfoVAo4O3tjeLiYmtPzqxZs/D666/Xy764ihkzZuD48eMAALVaDaPRiMTEREiSZHcZ3377LebMmQOz2YzmzZsDZQFeqVTiww8/xJAhQ+pWSUH1ymg0isGDB4vOnTuL7du3C5PJJEpLS8VHH30kJEkSzzzzTL2U0djMnj1bSJIkVq5cKYqLi4UQQhw8eFD06NFDRERECK1WW+Xjr1+/LuLi4sSxY8eETqcTQgih0+nE3//+dyFJkhg6dGi97IcrWbdunZAkScyYMUPk5OQIIYS4ePGiGDp0qJAkSZw8ebJG5f3xj38U8+bNE2+99ZaQJEmcOnXKSTV3XYcPHxaSJIknnnhCpKenCyGEuHv3rnjuueeEJEkiPj6+2jIKCgpEVFSUkCRJLFq0yPraFBYWik8++UR8//33Tt8PV3L37l3Ro0cPER4eLo4ePSqEEKKoqEgsW7ZMSJIkXnvttWrLOHDggJAkScTGxopff/1VCCGE2WwWycnJonv37iIyMtLp++FqVqxYIdauXStSU1PFm2++KSRJEhcvXqxRGSNHjhSSJInPPvtMGI1GYTQaxebNm4UkSWLUqFF1riMDTD374YcfhCRJ4uWXXy63burUqUKSJHHlyhWnl9GYFBQUiG7duokRI0YIk8lks87yYZmYmFjr8ocPHy66devmgJrKy7hx40TXrl1FVlaWzfIvv/xSSJIkVqxYYXdZ27dvFwMHDhS5ublNOsAsWrRISJIkDh48aLP8+vXronPnzmLSpEnVlhEfHy8kSRJTp04VZrPZibWVh61btwpJksQ//vEPm+WlpaViyJAhIjw8XJSUlFRZRnJyspAkSWzcuLHcurFjxzbJAPOw2gSY8+fPC0mSxMyZM8uts3zhvHDhQp3qxTEw9ezChQsAgKFDh5ZbZ1lW3dgAR5TRmFy8eBFGoxFDhgyBUmn7lra0h6XNakoIAbPZjK5duzqkrnJhMBiQnp6OLl26ICAgwGZddHQ0lEql3e+x27dvY/Xq1VixYgV8fX2dVGN5+Pnnn+Hm5oaBAwfaLA8ODkanTp2QlpaG6s7qf/fddwCA6dOnQ6FQoLCwEFqt1qn1dmWW/+1hw4bZLFer1Rg0aBCKioqqHbsRFRWFwMBAbNq0CQcOHMD169eRlpaG9957D5cvX0ZMTIxT96Exshwffvu6wAHHZQveC6me3blzByg7YP1W+/btbbZxZhmNiT3tcffu3VqV/fnnnyMzMxMrV66sYy3lJTs7GyaTqcI29fDwQKtWrexu07/+9a/43e9+V+GBrKm5c+cOAgICKhzn0r59e/zyyy/QarVo2bJlpWVcu3YNANCpUyfreBqUvf9nz57d5MZq2Xs87NKlS6VltGjRAlu3bsWaNWvw8ssvW5d7e3tjyZIl1Y6ho/Ju374NOOm4bMEemHpmuXrD3d293DrLsuqu8HBEGY2JZV8r+lCoS3vs27cPq1atQlxcXLlvzI1dVe8xlLV1SUlJteXs2bMHly5dwpIlSxxeRzkyGAxVtimAatu1uLgYnp6eWLRoEQ4fPoyWLVtCo9Hgxo0bWLp0KTZt2uSUursqy2XodT0eJicnW8Ogt7c3NBoN8vPzsWvXLly5csXh9W7sLK9LVcdle44hVWGAqWeWkdiFhYXl1un1eqDsG66zy2hMnNEe8fHxWLBgARYsWIDZs2c7qKbyYWmvitoUZe1aXZtmZ2dj1apVeOWVV6DT6azzv1jKtMwt0ZQuUfXw8KiyTWHHe7VZs2bQ6XQwGAw4cOAAUlJScObMGaxevRpqtRrr1q2DyWRySv1dUVXvVXvb9PDhw1i5ciXCw8Nx6NAh/PDDDzh79iw++OAD3LhxA3PmzGlSXwodwZ7XxXLsri0GmHoWGBgIlF22+1uWZUFBQU4vozGxtEdF57lr2h5CCKxevRp/+9vfsHTpUsycOdPBtZUHf39/aDSaCt9jubm5uHfvHtq1a1dlGf/5z3+Ql5eHhQsXWud+iY6OxrZt2wAAc+bMQXR0NHJycpy2H64mKCgId+7cqXBCr4yMDHh7e8PT07PKMiztPm/ePDzyyCMAAKVSiaeffhpDhgxBfn4+bt265aQ9cD2OOB7u378fALBkyRLrtgqFAsOGDcPEiRNx7dq1Gs0pQ449LleGAaaeWea92Lt3r81yk8mEL7/8EkqlEmFhYU4vozHp3LkzmjdvjkOHDpX7YLC0kT3zjRgMBsTFxWHTpk1466238Oyzzzqtzq5OpVKhR48euHLlSrmBdva2qYeHBwICAsr9WL51+fn5ISAgACqVyol74lrCw8NhNpuRlJRks/zkyZO4deuWXe/T3r17A2Wzxf6WZQZqe+aSaSwsbZaYmGizPD8/H0eOHIGfn5816FXG0iNQ0QzeeXl5NtuQfSIiIoCyU/EP97IKIazv/7rOA8VBvPWsa9eu6Nq1K06dOoWlS5di2rRpMBqN+PDDD5Geno6hQ4eidevW1u2zs7NhNBrRtm3bWpfR2Gk0GowdOxYJCQmYO3cu4uLi4OXlhT179mDv3r0IDAxEVFSUdfv8/HwUFRXBz8/PeqDX6XSYM2cOUlJSsHjxYgwYMABZWVk2z9OmTZtyVzk1ZjExMTh58iReffVVLF26FCEhIThx4gTee+89qNVqjB8/3rqtXq9HQUEBvLy80KJFCwDAlClTMGXKlHLlrl69Gp988gk2bNjQ5Caye+aZZxAfH481a9bA3d0dffr0QXp6OpYvXw6UtbmF5fYNHh4e8Pb2ti4fP3481q9fj9WrV8NsNiMsLAx6vR4JCQn46aefEBoaanO8aOyGDh0KX19f7N69G+3atcPvf/975OXl4Z133oFOp8PMmTNt/m+zsrKgUqlsjpHh4eHYv38/Fi1ahPnz56Nbt27Q6/X46quvsGfPHmg0miZ3JeLDU/8XFRUBAHJycqzHxYePhzk5OSgtLUVAQAAUCgUAoEOHDujduzdOnjyJhQsXYtasWUDZjMkXLlxAZGRktRMMVocz8TaAs2fP4vnnny93vw4fHx9s377d5tvC6NGjrd+C1Wp1rcpoCrKzsxEbG1uu61ylUmHDhg2Ijo62LluwYAESExNtZoI9ceIEpk2bVuVzHDt2rEkFQ5PJhBdeeME6G+fDXnnlFcydO9f69+bNm7FixQosXrwYM2bMqLJcS4BpqjPxWvb/t0aMGIF169ZZPwBOnz6NSZMm4cknn8Q777xjs+2mTZuwatWqcmW4u7vjo48+Qv/+/Z24B65n3759iIuLK3cJemhoKLZv325zVVfnzp3RoUMHJCcnW5fpdDpMnjwZv/zyS4XlL1iwAC+++KIT98D1rF+/Hu+//36l648fPw4/Pz+gLHhfuHABKSkpNm2dlpaG5557rtw4GE9PT3zxxRc1mtW3IuyBaQBhYWFISEjABx98gPPnz0OlUiEiIgIvvfRSuXEFrVu3hl6vtx7UalNGU+Dv748dO3Zgw4YNOHHiBAwGAyRJwqxZsxAeHm6zrY+PT7lLWTUaTbn5Tn6rKZ3qQNn+/utf/8LGjRuRnJyMvLw8tG/fHrGxsTa3XUDZYLyAgABr70tVvLy8Kr2UuClYuHAhOnfujJ07dyIzMxN+fn4YM2YMnn/+eZv/c8t70sfHp1wZ06dPR0hICLZs2YKMjAy4ubkhPDwcL7zwAjp16lTPe9Twxo4dC39/f2zcuBHp6elo1qwZBg4ciD//+c/lLkkPCAgo90XE09MTu3btwpYtW3D06FHcvHkTCoUCjz32GCZOnFj3Ke9lyNPTs8pj4sPHQ39/fwQEBJTroe7SpQt27dqFDRs24MyZM1AoFAgPD8ecOXMc8iWbPTBEREQkO03nhD4RERE1GgwwREREJDsMMERERCQ7DDBEREQkOwwwREREJDsMMERERCQ7DDBEREQkOwwwREREJDsMMERERCQ7DDBE1GTl5eUhKSkJ586dq3bbc+fOISkpqdzduYmoYTDAEFGTlZSUhLi4OKSlpVW77Y4dOxAXF4edO3fWS92IqGoMMETUZH399ddQKpUYNmxYQ1eFiGqIAYaImiStVouUlBSEh4fD39+/oatDRDWkbugKEBFVxGw2Y//+/RBCYOTIkdBoNBVul5qaioyMDHTs2BFdunSxu/xvv/0WpaWlGDFihANrTUT1hT0wROSSlEolvvjiC8TFxeHrr7+udLs33ngDcXFxyMnJqVH5ljIZYIjkiQGGiFzWs88+CwDYvn17hetPnTqFS5cuITg4GI8//rjd5RoMBhw9ehShoaF49NFHHVZfIqo/DDBE5LJGjhyJ1q1b43//+x+uXbtWbr0l2MTGxkKhUNhd7vHjx1FYWIgnnnjCofUlovrDAENELsvNzQ0TJkyAEALbtm2zWafVavHll1/Czc0NMTExNSr3m2++AXj6iEjWGGCIyKVNmjQJKpUKu3fvhsFgsC7fs2cPioqKMHz48BpdRSSEwMGDB+Hv74/w8HAn1ZqInI0BhohcWlBQEKKjo5Gbm2szmNdy+mjy5Mk1Ku/s2bO4e/cuhg8fDqWSh0AiueJ/LxG5PMtg3q1btwIATp8+jYsXL6JDhw6IioqqUVm8+oiocWCAISKXN3jwYAQHB+OHH37A1atXreNhJk6cWKPBuygLMM2bN69x8CEi18IAQ0QuT6FQYNKkSRBC4OOPP7YO3p0wYUKNyrl69SoyMjIwePBguLu7O62+ROR8nImXiGRhwoQJWLt2rXXsy+jRo9GqVasalZGcnAwAGD58eK3rce3aNSQlJVW6PiwsDMHBwbUun4jswwBDRLLg5+eHUaNGITExESi7OqmmvvnmG6jVagwdOrTW9Th27BiOHTtW6fqVK1cywBDVAwYYIpKNESNGIDExsVaDd3NycnDmzBn069cPPj4+NX7unj17QqvVVrsdwwtR/WCAISLZOHLkCFDLwbsHDx6E2Wyu9dVHEydOxMSJE2v1WCJyPA7iJSJZuH37NpKSkqBWq2s88y4AlJSUYOzYsRg5cqRT6kdE9UshhBANXQkioooIIbBv3z4UFhZiy5YtSE1NxVNPPYU1a9Y0dNWIqIExwBCRyzIajejevbv1b19fX+zevRuBgYENWi8iangcA0NELkupVGLs2LFQqVTo0KEDJk+ejDZt2jR0tYjIBbAHhoiIiGSHg3iJiIhIdhhgiIiISHYYYIiIiEh2GGCIiIhIdhhgiIiISHYYYIiIiEh2GGCIiIhIdhhgiIiISHYYYIiIiEh2/j/TbG6ke0bOfAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = common.fig_single()\n",
    "shapes = common.markers.shapes()\n",
    "for i, ra in enumerate(ra_values):\n",
    "    y_norm, nu_local = sims[ra][\"nu_y\"]\n",
    "    ax.plot(y_norm, nu_local, label=f\"Ra = {ra:.0e}\", linewidth=1.5)\n",
    "common.refline(ax, 1.0)\n",
    "ax.set_xlabel(\"y / L\")\n",
    "ax.set_ylabel(r\"$\\mathrm{Nu}(y)$ (hot wall)\")\n",
    "ax.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "becc169c",
   "metadata": {},
   "source": [
    "## Version"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "01ba729d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:01.361721Z",
     "iopub.status.busy": "2026-06-29T17:44:01.361609Z",
     "iopub.status.idle": "2026-06-29T17:44:01.408257Z",
     "shell.execute_reply": "2026-06-29T17:44:01.408068Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Version:"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0.1a0"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Commit hash:"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "80a1135356dcbcdac92068bde45adb0fae958657"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "sim_cfg = next(iter(ConfigScheme.sim_cfgs_from_file_dct(str(case_path)).values()))\n",
    "sim_info = sim_cfg.output.read_info()\n",
    "\n",
    "nassu_commit = sim_info[\"commit\"]\n",
    "nassu_version = sim_info[\"version\"]\n",
    "print(\"Version:\", nassu_version)\n",
    "print(\"Commit hash:\", nassu_commit)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa5c23ae",
   "metadata": {},
   "source": [
    "## Configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1b6f4eb8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-06-29T17:44:01.409156Z",
     "iopub.status.busy": "2026-06-29T17:44:01.409086Z",
     "iopub.status.idle": "2026-06-29T17:44:01.444600Z",
     "shell.execute_reply": "2026-06-29T17:44:01.444309Z"
    }
   },
   "outputs": [
    {
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       ".output_html .il { color: #666 } /* Literal.Number.Integer.Long */</style><div class=\"highlight\"><pre><span></span><span class=\"c1\"># Differentially heated square cavity - de Vahl Davis (1983) benchmark</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># Natural-convection benchmark for the scalar-transport Boussinesq</span>\n",
       "<span class=\"c1\"># buoyancy path. A square cavity with two opposing vertical walls held</span>\n",
       "<span class=\"c1\"># at fixed scalar values (hot W = 1, cold E = 0) and two adiabatic</span>\n",
       "<span class=\"c1\"># horizontal walls (N, S) develops a buoyancy-driven recirculation. The</span>\n",
       "<span class=\"c1\"># scalar `temperature` couples back onto the fluid through the Boussinesq</span>\n",
       "<span class=\"c1\"># body force F = -rho0 * beta * (phi - phi_ref) * gravity.</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># This case validates the buoyancy coupling using only domain-face BCs</span>\n",
       "<span class=\"c1\"># (no voxelization / IBM needed).</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># Quasi-2D: a thin slab in z (8 cells, periodic) reproduces the 2-D</span>\n",
       "<span class=\"c1\"># benchmark while staying on the 3-D D3Q27 fluid / D3Q7 scalar kernels</span>\n",
       "<span class=\"c1\"># (same pattern as case 12.2).</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># ---------------------------------------------------------------------</span>\n",
       "<span class=\"c1\"># Non-dimensional mapping (Pr = 0.71, dT = 1, L = 128, U = 0.1)</span>\n",
       "<span class=\"c1\"># ---------------------------------------------------------------------</span>\n",
       "<span class=\"c1\"># The governing dimensionless groups are</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\">#     Ra = g * beta * dT * L^3 / (nu * D)        (Rayleigh number)</span>\n",
       "<span class=\"c1\">#     Pr = nu / D                                (Prandtl number)</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># We fix the buoyant velocity scale U = sqrt(g * beta * dT * L) and the</span>\n",
       "<span class=\"c1\"># cavity side L; then</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\">#     nu   = U * L * sqrt(Pr / Ra)</span>\n",
       "<span class=\"c1\">#     D    = nu / Pr</span>\n",
       "<span class=\"c1\">#     beta = U^2 / (dT * L)            (with dT = 1)</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># So fixing U and L fixes beta and the buoyancy force for ALL Ra; only</span>\n",
       "<span class=\"c1\"># nu (fluid tau) and D (scalar diffusivity) change with Ra. The implied</span>\n",
       "<span class=\"c1\"># gravity magnitude is g = U^2 / (beta * dT * L) = 1 (lattice), and the</span>\n",
       "<span class=\"c1\"># alpha used to nondimensionalise the benchmark velocities is alpha = D</span>\n",
       "<span class=\"c1\"># (Pr = nu/alpha = nu/D = 0.71 by construction).</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># Fluid relaxation (cs^2 = 1/3): tau = nu / cs^2 + 1/2 = 3*nu + 1/2.</span>\n",
       "<span class=\"c1\"># Scalar relaxation (D3Q7, cs_phi^2 = 1/4): tau_phi = D / 0.25 + 1/2.</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\">#   | Ra   | nu        | tau (fluid) | D         | tau_phi (D/0.25+0.5) |</span>\n",
       "<span class=\"c1\">#   | 1e3  | 0.341066  | 1.5232      | 0.480384  | 2.4215               |</span>\n",
       "<span class=\"c1\">#   | 1e4  | 0.107855  | 0.8236      | 0.151909  | 1.1076               |</span>\n",
       "<span class=\"c1\">#   | 1e5  | 0.034107  | 0.6023      | 0.048038  | 0.6922               |</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># The tabulated fluid `tau` and scalar `D` below use the rounded values</span>\n",
       "<span class=\"c1\"># (tau = 1.5232 / 0.8236 / 0.6023; D = 0.48038 / 0.15191 / 0.04804).</span>\n",
       "<span class=\"c1\"># beta = U^2 / L = 0.1^2 / 128 = 7.8125e-5, identical for all three runs.</span>\n",
       "<span class=\"c1\"># Raising U from 0.04 to 0.1 scales nu and D up by 2.5x, cutting the</span>\n",
       "<span class=\"c1\"># step count to steady state by 2.5x while keeping Ra, Pr fixed; the peak</span>\n",
       "<span class=\"c1\"># Mach number stays &lt;= 0.045 (well within the Ma &lt; 0.1 limit).</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># ---------------------------------------------------------------------</span>\n",
       "<span class=\"c1\"># Steady state and timing</span>\n",
       "<span class=\"c1\"># ---------------------------------------------------------------------</span>\n",
       "<span class=\"c1\"># Convective time scale L/U = 1280 steps; diffusive time scale L^2/D</span>\n",
       "<span class=\"c1\"># ranges from ~34k (Ra=1e3) to ~340k (Ra=1e5). The runs are seeded with</span>\n",
       "<span class=\"c1\"># a linear hot-&gt;cold horizontal ramp for the scalar to cut the transient.</span>\n",
       "<span class=\"c1\"># n_steps below is a generous fixed budget per Ra; it may be shortened</span>\n",
       "<span class=\"c1\"># using the `data.divergence` and `report` output once the wall Nusselt</span>\n",
       "<span class=\"c1\"># number and velocity extrema stop drifting.</span>\n",
       "<span class=\"c1\">#</span>\n",
       "<span class=\"c1\"># Reference: de Vahl Davis, G. (1983). &quot;Natural convection of air in a</span>\n",
       "<span class=\"c1\"># square cavity: a bench-mark numerical solution.&quot; Int. J. Numer.</span>\n",
       "<span class=\"c1\"># Methods Fluids 3(3):249-264. Comparison data in</span>\n",
       "<span class=\"c1\"># validation/thermal/01_differentially_heated_cavity/reference/.</span>\n",
       "\n",
       "<span class=\"nt\">simulations</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">  </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">name</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">differentiallyHeatedCavity</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">save_path</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!unroll</span>\n",
       "<span class=\"w\">      </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">./validation/thermal/01_differentially_heated_cavity/results/dvd_ra1e3</span>\n",
       "<span class=\"w\">      </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">./validation/thermal/01_differentially_heated_cavity/results/dvd_ra1e4</span>\n",
       "<span class=\"w\">      </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">./validation/thermal/01_differentially_heated_cavity/results/dvd_ra1e5</span>\n",
       "<span class=\"w\">    </span><span class=\"nt\">n_steps</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!unroll</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">240000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">200000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">200000</span><span class=\"p p-Indicator\">]</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">report</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">2000</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">domain</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"c1\"># Square cavity 128 x 128 in the x-y plane; thin periodic slab in z.</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">domain_size</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">x</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">128</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">y</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">128</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">z</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">8</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">block_size</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">8</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">data</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"c1\"># Steady-state monitor: watch this flatten to size n_steps.</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">exports</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">rho</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">u</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">temperature_phi</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">start_step</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!unroll</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">216000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">180000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">180000</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!unroll</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">8000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">10000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">10000</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">volume</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">plane_series</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">macrs</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">u</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">temperature_phi</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">interval</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">{</span><span class=\"nt\">frequency</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!unroll</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">8000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">10000</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">10000</span><span class=\"p p-Indicator\">],</span><span class=\"nt\"> lvl</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"nv\">0</span><span class=\"p p-Indicator\">}</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">target</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">planes</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Vertical mid-plane (x = L/2): u_y profile -&gt; v_max location.</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">vertical_mid</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">x</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis_pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">64</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">dist</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Horizontal mid-plane (y = L/2): u_x profile -&gt; u_max location.</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">horizontal_mid</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">y</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis_pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">64</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">dist</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># slice full (z = L/2)</span>\n",
       "<span class=\"w\">              </span><span class=\"nt\">slice_mid</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">z</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">axis_pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">4</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">dist</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">outputs</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">instantaneous</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">true</span>\n",
       "\n",
       "<span class=\"w\">    </span><span class=\"nt\">models</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">precision</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">default</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">single</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">LBM</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"c1\"># Fluid kinematic viscosity per Ra (Pr = 0.71, U = 0.1, L = 128).</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">tau</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!unroll</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">1.5232</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0.8236</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0.6023</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">vel_set</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">D3Q27</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">coll_oper</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">HRRBGK</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">LES</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">model</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">Smagorinsky</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">sgs_cte</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.1</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">engine</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">name</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">CUDA</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"c1\"># All four in-plane walls are no-slip (HWBB). z is periodic.</span>\n",
       "<span class=\"w\">      </span><span class=\"c1\"># x walls (W, E) carry the hot / cold scalar Dirichlet; y walls</span>\n",
       "<span class=\"w\">      </span><span class=\"c1\"># (N, S) are adiabatic for the scalar (zero-flux bounce-back).</span>\n",
       "<span class=\"w\">      </span><span class=\"nt\">BC</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">periodic_dims</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">false</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">false</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">true</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">BC_map</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">W</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">W</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">E</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">E</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0</span>\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "<span class=\"w\">          </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RegularizedHWBB</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">order</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1</span>\n",
       "\n",
       "<span class=\"w\">      </span><span class=\"nt\">scalar_transports</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">        </span><span class=\"nt\">temperature</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">velocity_set</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">D3Q7</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">collision_operator</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">RRBGK</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">adv_diff_equation</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"c1\"># Scalar diffusivity per Ra (D = nu / Pr).</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">D</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"kt\">!unroll</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">0.48038</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0.15191</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0.04804</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">S</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s\">&quot;0&quot;</span>\n",
       "<span class=\"w\">          </span><span class=\"c1\"># Boussinesq coupling onto the fluid. beta = U^2 / L = 7.8125e-5,</span>\n",
       "<span class=\"w\">          </span><span class=\"c1\"># gravity along -y (y is vertical); a hot parcel (phi &gt; phi_ref)</span>\n",
       "<span class=\"w\">          </span><span class=\"c1\"># then feels +y upward force via F = -rho0*beta*(phi-phi_ref)*g.</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">buoyancy</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">beta</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">7.8125e-5</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">phi_ref</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.5</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">gravity</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"p p-Indicator\">[</span><span class=\"nv\">0.0</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">-1.0</span><span class=\"p p-Indicator\">,</span><span class=\"w\"> </span><span class=\"nv\">0.0</span><span class=\"p p-Indicator\">]</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">rho0</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1.0</span>\n",
       "<span class=\"w\">          </span><span class=\"c1\"># Linear hot-&gt;cold horizontal ramp (x is the lattice index,</span>\n",
       "<span class=\"w\">          </span><span class=\"c1\"># 0..127). Seeds the scalar near its eventual conduction profile</span>\n",
       "<span class=\"w\">          </span><span class=\"c1\"># to shorten the transient.</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">initial_field</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"s\">&quot;1.0</span><span class=\"nv\"> </span><span class=\"s\">-</span><span class=\"nv\"> </span><span class=\"s\">x</span><span class=\"nv\"> </span><span class=\"s\">/</span><span class=\"nv\"> </span><span class=\"s\">127.0&quot;</span>\n",
       "<span class=\"w\">          </span><span class=\"nt\">BC</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">            </span><span class=\"nt\">BC_map</span><span class=\"p\">:</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Hot vertical wall (west), phi = 1, no-slip.</span>\n",
       "<span class=\"w\">              </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">W</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">ScalarRegularizedDirichlet</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">W</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">phi_w</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">1.0</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">ux</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">uy</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">uz</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Cold vertical wall (east), phi = 0, no-slip.</span>\n",
       "<span class=\"w\">              </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">E</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">ScalarRegularizedDirichlet</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">E</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">phi_w</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">ux</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">uy</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">uz</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">0.0</span>\n",
       "<span class=\"w\">              </span><span class=\"c1\"># Adiabatic horizontal walls (zero scalar flux).</span>\n",
       "<span class=\"w\">              </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">ScalarHWBB</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">N</span>\n",
       "<span class=\"w\">              </span><span class=\"p p-Indicator\">-</span><span class=\"w\"> </span><span class=\"nt\">pos</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">BC</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">ScalarHWBB</span>\n",
       "<span class=\"w\">                </span><span class=\"nt\">wall_normal</span><span class=\"p\">:</span><span class=\"w\"> </span><span class=\"l l-Scalar l-Scalar-Plain\">S</span>\n",
       "</pre></div>\n"
      ],
      "text/latex": [
       "\\begin{Verbatim}[commandchars=\\\\\\{\\}]\n",
       "\\PY{c+c1}{\\PYZsh{} Differentially heated square cavity \\PYZhy{} de Vahl Davis (1983) benchmark}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} Natural\\PYZhy{}convection benchmark for the scalar\\PYZhy{}transport Boussinesq}\n",
       "\\PY{c+c1}{\\PYZsh{} buoyancy path. A square cavity with two opposing vertical walls held}\n",
       "\\PY{c+c1}{\\PYZsh{} at fixed scalar values (hot W = 1, cold E = 0) and two adiabatic}\n",
       "\\PY{c+c1}{\\PYZsh{} horizontal walls (N, S) develops a buoyancy\\PYZhy{}driven recirculation. The}\n",
       "\\PY{c+c1}{\\PYZsh{} scalar `temperature` couples back onto the fluid through the Boussinesq}\n",
       "\\PY{c+c1}{\\PYZsh{} body force F = \\PYZhy{}rho0 * beta * (phi \\PYZhy{} phi\\PYZus{}ref) * gravity.}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} This case validates the buoyancy coupling using only domain\\PYZhy{}face BCs}\n",
       "\\PY{c+c1}{\\PYZsh{} (no voxelization / IBM needed).}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} Quasi\\PYZhy{}2D: a thin slab in z (8 cells, periodic) reproduces the 2\\PYZhy{}D}\n",
       "\\PY{c+c1}{\\PYZsh{} benchmark while staying on the 3\\PYZhy{}D D3Q27 fluid / D3Q7 scalar kernels}\n",
       "\\PY{c+c1}{\\PYZsh{} (same pattern as case 12.2).}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} \\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}}\n",
       "\\PY{c+c1}{\\PYZsh{} Non\\PYZhy{}dimensional mapping (Pr = 0.71, dT = 1, L = 128, U = 0.1)}\n",
       "\\PY{c+c1}{\\PYZsh{} \\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}}\n",
       "\\PY{c+c1}{\\PYZsh{} The governing dimensionless groups are}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{}     Ra = g * beta * dT * L\\PYZca{}3 / (nu * D)        (Rayleigh number)}\n",
       "\\PY{c+c1}{\\PYZsh{}     Pr = nu / D                                (Prandtl number)}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} We fix the buoyant velocity scale U = sqrt(g * beta * dT * L) and the}\n",
       "\\PY{c+c1}{\\PYZsh{} cavity side L; then}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{}     nu   = U * L * sqrt(Pr / Ra)}\n",
       "\\PY{c+c1}{\\PYZsh{}     D    = nu / Pr}\n",
       "\\PY{c+c1}{\\PYZsh{}     beta = U\\PYZca{}2 / (dT * L)            (with dT = 1)}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} So fixing U and L fixes beta and the buoyancy force for ALL Ra; only}\n",
       "\\PY{c+c1}{\\PYZsh{} nu (fluid tau) and D (scalar diffusivity) change with Ra. The implied}\n",
       "\\PY{c+c1}{\\PYZsh{} gravity magnitude is g = U\\PYZca{}2 / (beta * dT * L) = 1 (lattice), and the}\n",
       "\\PY{c+c1}{\\PYZsh{} alpha used to nondimensionalise the benchmark velocities is alpha = D}\n",
       "\\PY{c+c1}{\\PYZsh{} (Pr = nu/alpha = nu/D = 0.71 by construction).}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} Fluid relaxation (cs\\PYZca{}2 = 1/3): tau = nu / cs\\PYZca{}2 + 1/2 = 3*nu + 1/2.}\n",
       "\\PY{c+c1}{\\PYZsh{} Scalar relaxation (D3Q7, cs\\PYZus{}phi\\PYZca{}2 = 1/4): tau\\PYZus{}phi = D / 0.25 + 1/2.}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{}   | Ra   | nu        | tau (fluid) | D         | tau\\PYZus{}phi (D/0.25+0.5) |}\n",
       "\\PY{c+c1}{\\PYZsh{}   | 1e3  | 0.341066  | 1.5232      | 0.480384  | 2.4215               |}\n",
       "\\PY{c+c1}{\\PYZsh{}   | 1e4  | 0.107855  | 0.8236      | 0.151909  | 1.1076               |}\n",
       "\\PY{c+c1}{\\PYZsh{}   | 1e5  | 0.034107  | 0.6023      | 0.048038  | 0.6922               |}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} The tabulated fluid `tau` and scalar `D` below use the rounded values}\n",
       "\\PY{c+c1}{\\PYZsh{} (tau = 1.5232 / 0.8236 / 0.6023; D = 0.48038 / 0.15191 / 0.04804).}\n",
       "\\PY{c+c1}{\\PYZsh{} beta = U\\PYZca{}2 / L = 0.1\\PYZca{}2 / 128 = 7.8125e\\PYZhy{}5, identical for all three runs.}\n",
       "\\PY{c+c1}{\\PYZsh{} Raising U from 0.04 to 0.1 scales nu and D up by 2.5x, cutting the}\n",
       "\\PY{c+c1}{\\PYZsh{} step count to steady state by 2.5x while keeping Ra, Pr fixed; the peak}\n",
       "\\PY{c+c1}{\\PYZsh{} Mach number stays \\PYZlt{}= 0.045 (well within the Ma \\PYZlt{} 0.1 limit).}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} \\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}}\n",
       "\\PY{c+c1}{\\PYZsh{} Steady state and timing}\n",
       "\\PY{c+c1}{\\PYZsh{} \\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}\\PYZhy{}}\n",
       "\\PY{c+c1}{\\PYZsh{} Convective time scale L/U = 1280 steps; diffusive time scale L\\PYZca{}2/D}\n",
       "\\PY{c+c1}{\\PYZsh{} ranges from \\PYZti{}34k (Ra=1e3) to \\PYZti{}340k (Ra=1e5). The runs are seeded with}\n",
       "\\PY{c+c1}{\\PYZsh{} a linear hot\\PYZhy{}\\PYZgt{}cold horizontal ramp for the scalar to cut the transient.}\n",
       "\\PY{c+c1}{\\PYZsh{} n\\PYZus{}steps below is a generous fixed budget per Ra; it may be shortened}\n",
       "\\PY{c+c1}{\\PYZsh{} using the `data.divergence` and `report` output once the wall Nusselt}\n",
       "\\PY{c+c1}{\\PYZsh{} number and velocity extrema stop drifting.}\n",
       "\\PY{c+c1}{\\PYZsh{}}\n",
       "\\PY{c+c1}{\\PYZsh{} Reference: de Vahl Davis, G. (1983). \\PYZdq{}Natural convection of air in a}\n",
       "\\PY{c+c1}{\\PYZsh{} square cavity: a bench\\PYZhy{}mark numerical solution.\\PYZdq{} Int. J. Numer.}\n",
       "\\PY{c+c1}{\\PYZsh{} Methods Fluids 3(3):249\\PYZhy{}264. Comparison data in}\n",
       "\\PY{c+c1}{\\PYZsh{} validation/thermal/01\\PYZus{}differentially\\PYZus{}heated\\PYZus{}cavity/reference/.}\n",
       "\n",
       "\\PY{n+nt}{simulations}\\PY{p}{:}\n",
       "\\PY{+w}{  }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{name}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{differentiallyHeatedCavity}\n",
       "\\PY{+w}{    }\\PY{n+nt}{save\\PYZus{}path}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!unroll}\n",
       "\\PY{+w}{      }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{./validation/thermal/01\\PYZus{}differentially\\PYZus{}heated\\PYZus{}cavity/results/dvd\\PYZus{}ra1e3}\n",
       "\\PY{+w}{      }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{./validation/thermal/01\\PYZus{}differentially\\PYZus{}heated\\PYZus{}cavity/results/dvd\\PYZus{}ra1e4}\n",
       "\\PY{+w}{      }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{./validation/thermal/01\\PYZus{}differentially\\PYZus{}heated\\PYZus{}cavity/results/dvd\\PYZus{}ra1e5}\n",
       "\\PY{+w}{    }\\PY{n+nt}{n\\PYZus{}steps}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!unroll}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{240000}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{200000}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{200000}\\PY{p+pIndicator}{]}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{report}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{2000}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{domain}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} Square cavity 128 x 128 in the x\\PYZhy{}y plane; thin periodic slab in z.}\n",
       "\\PY{+w}{      }\\PY{n+nt}{domain\\PYZus{}size}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{x}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{128}\n",
       "\\PY{+w}{        }\\PY{n+nt}{y}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{128}\n",
       "\\PY{+w}{        }\\PY{n+nt}{z}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{8}\n",
       "\\PY{+w}{      }\\PY{n+nt}{block\\PYZus{}size}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{8}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{data}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} Steady\\PYZhy{}state monitor: watch this flatten to size n\\PYZus{}steps.}\n",
       "\\PY{+w}{      }\\PY{n+nt}{exports}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{macrs}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{rho}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{u}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{temperature\\PYZus{}phi}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{          }\\PY{n+nt}{interval}\\PY{p}{:}\n",
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       "\\PY{+w}{            }\\PY{n+nt}{frequency}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!unroll}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{8000}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{10000}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{10000}\\PY{p+pIndicator}{]}\n",
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       "\\PY{+w}{          }\\PY{n+nt}{target}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{planes}\\PY{p}{:}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Vertical mid\\PYZhy{}plane (x = L/2): u\\PYZus{}y profile \\PYZhy{}\\PYZgt{} v\\PYZus{}max location.}\n",
       "\\PY{+w}{              }\\PY{n+nt}{vertical\\PYZus{}mid}\\PY{p}{:}\n",
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       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Horizontal mid\\PYZhy{}plane (y = L/2): u\\PYZus{}x profile \\PYZhy{}\\PYZgt{} u\\PYZus{}max location.}\n",
       "\\PY{+w}{              }\\PY{n+nt}{horizontal\\PYZus{}mid}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{y}\n",
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       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} slice full (z = L/2)}\n",
       "\\PY{+w}{              }\\PY{n+nt}{slice\\PYZus{}mid}\\PY{p}{:}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{z}\n",
       "\\PY{+w}{                }\\PY{n+nt}{axis\\PYZus{}pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{4}\n",
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       "\\PY{+w}{          }\\PY{n+nt}{outputs}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{instantaneous}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{true}\n",
       "\n",
       "\\PY{+w}{    }\\PY{n+nt}{models}\\PY{p}{:}\n",
       "\\PY{+w}{      }\\PY{n+nt}{precision}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{default}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{single}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{LBM}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{c+c1}{\\PYZsh{} Fluid kinematic viscosity per Ra (Pr = 0.71, U = 0.1, L = 128).}\n",
       "\\PY{+w}{        }\\PY{n+nt}{tau}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!unroll}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{1.5232}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0.8236}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0.6023}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{        }\\PY{n+nt}{vel\\PYZus{}set}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{D3Q27}\n",
       "\\PY{+w}{        }\\PY{n+nt}{coll\\PYZus{}oper}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{HRRBGK}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{LES}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{model}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{Smagorinsky}\n",
       "\\PY{+w}{        }\\PY{n+nt}{sgs\\PYZus{}cte}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.1}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{engine}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{name}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{CUDA}\n",
       "\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} All four in\\PYZhy{}plane walls are no\\PYZhy{}slip (HWBB). z is periodic.}\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} x walls (W, E) carry the hot / cold scalar Dirichlet; y walls}\n",
       "\\PY{+w}{      }\\PY{c+c1}{\\PYZsh{} (N, S) are adiabatic for the scalar (zero\\PYZhy{}flux bounce\\PYZhy{}back).}\n",
       "\\PY{+w}{      }\\PY{n+nt}{BC}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{periodic\\PYZus{}dims}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{false}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{false}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{true}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{        }\\PY{n+nt}{BC\\PYZus{}map}\\PY{p}{:}\n",
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       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{W}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
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       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{E}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0}\n",
       "\\PY{+w}{          }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\\PY{+w}{          }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\PY{+w}{            }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RegularizedHWBB}\n",
       "\\PY{+w}{            }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\PY{+w}{            }\\PY{n+nt}{order}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1}\n",
       "\n",
       "\\PY{+w}{      }\\PY{n+nt}{scalar\\PYZus{}transports}\\PY{p}{:}\n",
       "\\PY{+w}{        }\\PY{n+nt}{temperature}\\PY{p}{:}\n",
       "\\PY{+w}{          }\\PY{n+nt}{velocity\\PYZus{}set}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{D3Q7}\n",
       "\\PY{+w}{          }\\PY{n+nt}{collision\\PYZus{}operator}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{RRBGK}\n",
       "\\PY{+w}{          }\\PY{n+nt}{adv\\PYZus{}diff\\PYZus{}equation}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{c+c1}{\\PYZsh{} Scalar diffusivity per Ra (D = nu / Pr).}\n",
       "\\PY{+w}{            }\\PY{n+nt}{D}\\PY{p}{:}\\PY{+w}{ }\\PY{k+kt}{!unroll}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{0.48038}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0.15191}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0.04804}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{            }\\PY{n+nt}{S}\\PY{p}{:}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{0}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{          }\\PY{c+c1}{\\PYZsh{} Boussinesq coupling onto the fluid. beta = U\\PYZca{}2 / L = 7.8125e\\PYZhy{}5,}\n",
       "\\PY{+w}{          }\\PY{c+c1}{\\PYZsh{} gravity along \\PYZhy{}y (y is vertical); a hot parcel (phi \\PYZgt{} phi\\PYZus{}ref)}\n",
       "\\PY{+w}{          }\\PY{c+c1}{\\PYZsh{} then feels +y upward force via F = \\PYZhy{}rho0*beta*(phi\\PYZhy{}phi\\PYZus{}ref)*g.}\n",
       "\\PY{+w}{          }\\PY{n+nt}{buoyancy}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{beta}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{7.8125e\\PYZhy{}5}\n",
       "\\PY{+w}{            }\\PY{n+nt}{phi\\PYZus{}ref}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.5}\n",
       "\\PY{+w}{            }\\PY{n+nt}{gravity}\\PY{p}{:}\\PY{+w}{ }\\PY{p+pIndicator}{[}\\PY{n+nv}{0.0}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{\\PYZhy{}1.0}\\PY{p+pIndicator}{,}\\PY{+w}{ }\\PY{n+nv}{0.0}\\PY{p+pIndicator}{]}\n",
       "\\PY{+w}{            }\\PY{n+nt}{rho0}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1.0}\n",
       "\\PY{+w}{          }\\PY{c+c1}{\\PYZsh{} Linear hot\\PYZhy{}\\PYZgt{}cold horizontal ramp (x is the lattice index,}\n",
       "\\PY{+w}{          }\\PY{c+c1}{\\PYZsh{} 0..127). Seeds the scalar near its eventual conduction profile}\n",
       "\\PY{+w}{          }\\PY{c+c1}{\\PYZsh{} to shorten the transient.}\n",
       "\\PY{+w}{          }\\PY{n+nt}{initial\\PYZus{}field}\\PY{p}{:}\\PY{+w}{ }\\PY{l+s}{\\PYZdq{}}\\PY{l+s}{1.0}\\PY{n+nv}{ }\\PY{l+s}{\\PYZhy{}}\\PY{n+nv}{ }\\PY{l+s}{x}\\PY{n+nv}{ }\\PY{l+s}{/}\\PY{n+nv}{ }\\PY{l+s}{127.0}\\PY{l+s}{\\PYZdq{}}\n",
       "\\PY{+w}{          }\\PY{n+nt}{BC}\\PY{p}{:}\n",
       "\\PY{+w}{            }\\PY{n+nt}{BC\\PYZus{}map}\\PY{p}{:}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Hot vertical wall (west), phi = 1, no\\PYZhy{}slip.}\n",
       "\\PY{+w}{              }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{W}\n",
       "\\PY{+w}{                }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{ScalarRegularizedDirichlet}\n",
       "\\PY{+w}{                }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{W}\n",
       "\\PY{+w}{                }\\PY{n+nt}{phi\\PYZus{}w}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{1.0}\n",
       "\\PY{+w}{                }\\PY{n+nt}{ux}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.0}\n",
       "\\PY{+w}{                }\\PY{n+nt}{uy}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.0}\n",
       "\\PY{+w}{                }\\PY{n+nt}{uz}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.0}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Cold vertical wall (east), phi = 0, no\\PYZhy{}slip.}\n",
       "\\PY{+w}{              }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{E}\n",
       "\\PY{+w}{                }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{ScalarRegularizedDirichlet}\n",
       "\\PY{+w}{                }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{E}\n",
       "\\PY{+w}{                }\\PY{n+nt}{phi\\PYZus{}w}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.0}\n",
       "\\PY{+w}{                }\\PY{n+nt}{ux}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.0}\n",
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       "\\PY{+w}{                }\\PY{n+nt}{uz}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{0.0}\n",
       "\\PY{+w}{              }\\PY{c+c1}{\\PYZsh{} Adiabatic horizontal walls (zero scalar flux).}\n",
       "\\PY{+w}{              }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{                }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{ScalarHWBB}\n",
       "\\PY{+w}{                }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{N}\n",
       "\\PY{+w}{              }\\PY{p+pIndicator}{\\PYZhy{}}\\PY{+w}{ }\\PY{n+nt}{pos}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\PY{+w}{                }\\PY{n+nt}{BC}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{ScalarHWBB}\n",
       "\\PY{+w}{                }\\PY{n+nt}{wall\\PYZus{}normal}\\PY{p}{:}\\PY{+w}{ }\\PY{l+lScalar+lScalarPlain}{S}\n",
       "\\end{Verbatim}\n"
      ],
      "text/plain": [
       "# Differentially heated square cavity - de Vahl Davis (1983) benchmark\n",
       "#\n",
       "# Natural-convection benchmark for the scalar-transport Boussinesq\n",
       "# buoyancy path. A square cavity with two opposing vertical walls held\n",
       "# at fixed scalar values (hot W = 1, cold E = 0) and two adiabatic\n",
       "# horizontal walls (N, S) develops a buoyancy-driven recirculation. The\n",
       "# scalar `temperature` couples back onto the fluid through the Boussinesq\n",
       "# body force F = -rho0 * beta * (phi - phi_ref) * gravity.\n",
       "#\n",
       "# This case validates the buoyancy coupling using only domain-face BCs\n",
       "# (no voxelization / IBM needed).\n",
       "#\n",
       "# Quasi-2D: a thin slab in z (8 cells, periodic) reproduces the 2-D\n",
       "# benchmark while staying on the 3-D D3Q27 fluid / D3Q7 scalar kernels\n",
       "# (same pattern as case 12.2).\n",
       "#\n",
       "# ---------------------------------------------------------------------\n",
       "# Non-dimensional mapping (Pr = 0.71, dT = 1, L = 128, U = 0.1)\n",
       "# ---------------------------------------------------------------------\n",
       "# The governing dimensionless groups are\n",
       "#\n",
       "#     Ra = g * beta * dT * L^3 / (nu * D)        (Rayleigh number)\n",
       "#     Pr = nu / D                                (Prandtl number)\n",
       "#\n",
       "# We fix the buoyant velocity scale U = sqrt(g * beta * dT * L) and the\n",
       "# cavity side L; then\n",
       "#\n",
       "#     nu   = U * L * sqrt(Pr / Ra)\n",
       "#     D    = nu / Pr\n",
       "#     beta = U^2 / (dT * L)            (with dT = 1)\n",
       "#\n",
       "# So fixing U and L fixes beta and the buoyancy force for ALL Ra; only\n",
       "# nu (fluid tau) and D (scalar diffusivity) change with Ra. The implied\n",
       "# gravity magnitude is g = U^2 / (beta * dT * L) = 1 (lattice), and the\n",
       "# alpha used to nondimensionalise the benchmark velocities is alpha = D\n",
       "# (Pr = nu/alpha = nu/D = 0.71 by construction).\n",
       "#\n",
       "# Fluid relaxation (cs^2 = 1/3): tau = nu / cs^2 + 1/2 = 3*nu + 1/2.\n",
       "# Scalar relaxation (D3Q7, cs_phi^2 = 1/4): tau_phi = D / 0.25 + 1/2.\n",
       "#\n",
       "#   | Ra   | nu        | tau (fluid) | D         | tau_phi (D/0.25+0.5) |\n",
       "#   | 1e3  | 0.341066  | 1.5232      | 0.480384  | 2.4215               |\n",
       "#   | 1e4  | 0.107855  | 0.8236      | 0.151909  | 1.1076               |\n",
       "#   | 1e5  | 0.034107  | 0.6023      | 0.048038  | 0.6922               |\n",
       "#\n",
       "# The tabulated fluid `tau` and scalar `D` below use the rounded values\n",
       "# (tau = 1.5232 / 0.8236 / 0.6023; D = 0.48038 / 0.15191 / 0.04804).\n",
       "# beta = U^2 / L = 0.1^2 / 128 = 7.8125e-5, identical for all three runs.\n",
       "# Raising U from 0.04 to 0.1 scales nu and D up by 2.5x, cutting the\n",
       "# step count to steady state by 2.5x while keeping Ra, Pr fixed; the peak\n",
       "# Mach number stays <= 0.045 (well within the Ma < 0.1 limit).\n",
       "#\n",
       "# ---------------------------------------------------------------------\n",
       "# Steady state and timing\n",
       "# ---------------------------------------------------------------------\n",
       "# Convective time scale L/U = 1280 steps; diffusive time scale L^2/D\n",
       "# ranges from ~34k (Ra=1e3) to ~340k (Ra=1e5). The runs are seeded with\n",
       "# a linear hot->cold horizontal ramp for the scalar to cut the transient.\n",
       "# n_steps below is a generous fixed budget per Ra; it may be shortened\n",
       "# using the `data.divergence` and `report` output once the wall Nusselt\n",
       "# number and velocity extrema stop drifting.\n",
       "#\n",
       "# Reference: de Vahl Davis, G. (1983). \"Natural convection of air in a\n",
       "# square cavity: a bench-mark numerical solution.\" Int. J. Numer.\n",
       "# Methods Fluids 3(3):249-264. Comparison data in\n",
       "# validation/thermal/01_differentially_heated_cavity/reference/.\n",
       "\n",
       "simulations:\n",
       "  - name: differentiallyHeatedCavity\n",
       "    save_path: !unroll\n",
       "      - ./validation/thermal/01_differentially_heated_cavity/results/dvd_ra1e3\n",
       "      - ./validation/thermal/01_differentially_heated_cavity/results/dvd_ra1e4\n",
       "      - ./validation/thermal/01_differentially_heated_cavity/results/dvd_ra1e5\n",
       "    n_steps: !unroll [240000, 200000, 200000]\n",
       "\n",
       "    report:\n",
       "      frequency: 2000\n",
       "\n",
       "    domain:\n",
       "      # Square cavity 128 x 128 in the x-y plane; thin periodic slab in z.\n",
       "      domain_size:\n",
       "        x: 128\n",
       "        y: 128\n",
       "        z: 8\n",
       "      block_size: 8\n",
       "\n",
       "    data:\n",
       "      # Steady-state monitor: watch this flatten to size n_steps.\n",
       "      exports:\n",
       "        default:\n",
       "          macrs: [rho, u, temperature_phi]\n",
       "          interval:\n",
       "            start_step: !unroll [216000, 180000, 180000]\n",
       "            frequency: !unroll [8000, 10000, 10000]\n",
       "            lvl: 0\n",
       "          target:\n",
       "            volume: {}\n",
       "          outputs:\n",
       "            instantaneous: true\n",
       "        plane_series:\n",
       "          macrs: [u, temperature_phi]\n",
       "          interval: {frequency: !unroll [8000, 10000, 10000], lvl: 0}\n",
       "          target:\n",
       "            planes:\n",
       "              # Vertical mid-plane (x = L/2): u_y profile -> v_max location.\n",
       "              vertical_mid:\n",
       "                axis: x\n",
       "                axis_pos: 64\n",
       "                dist: 1\n",
       "              # Horizontal mid-plane (y = L/2): u_x profile -> u_max location.\n",
       "              horizontal_mid:\n",
       "                axis: y\n",
       "                axis_pos: 64\n",
       "                dist: 1\n",
       "              # slice full (z = L/2)\n",
       "              slice_mid:\n",
       "                axis: z\n",
       "                axis_pos: 4\n",
       "                dist: 1\n",
       "          outputs:\n",
       "            instantaneous: true\n",
       "\n",
       "    models:\n",
       "      precision:\n",
       "        default: single\n",
       "\n",
       "      LBM:\n",
       "        # Fluid kinematic viscosity per Ra (Pr = 0.71, U = 0.1, L = 128).\n",
       "        tau: !unroll [1.5232, 0.8236, 0.6023]\n",
       "        vel_set: D3Q27\n",
       "        coll_oper: HRRBGK\n",
       "\n",
       "      LES:\n",
       "        model: Smagorinsky\n",
       "        sgs_cte: 0.1\n",
       "\n",
       "      engine:\n",
       "        name: CUDA\n",
       "\n",
       "      # All four in-plane walls are no-slip (HWBB). z is periodic.\n",
       "      # x walls (W, E) carry the hot / cold scalar Dirichlet; y walls\n",
       "      # (N, S) are adiabatic for the scalar (zero-flux bounce-back).\n",
       "      BC:\n",
       "        periodic_dims: [false, false, true]\n",
       "        BC_map:\n",
       "          - pos: W\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: W\n",
       "            order: 0\n",
       "          - pos: E\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: E\n",
       "            order: 0\n",
       "          - pos: N\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: N\n",
       "            order: 1\n",
       "          - pos: S\n",
       "            BC: RegularizedHWBB\n",
       "            wall_normal: S\n",
       "            order: 1\n",
       "\n",
       "      scalar_transports:\n",
       "        temperature:\n",
       "          velocity_set: D3Q7\n",
       "          collision_operator: RRBGK\n",
       "          adv_diff_equation:\n",
       "            # Scalar diffusivity per Ra (D = nu / Pr).\n",
       "            D: !unroll [0.48038, 0.15191, 0.04804]\n",
       "            S: \"0\"\n",
       "          # Boussinesq coupling onto the fluid. beta = U^2 / L = 7.8125e-5,\n",
       "          # gravity along -y (y is vertical); a hot parcel (phi > phi_ref)\n",
       "          # then feels +y upward force via F = -rho0*beta*(phi-phi_ref)*g.\n",
       "          buoyancy:\n",
       "            beta: 7.8125e-5\n",
       "            phi_ref: 0.5\n",
       "            gravity: [0.0, -1.0, 0.0]\n",
       "            rho0: 1.0\n",
       "          # Linear hot->cold horizontal ramp (x is the lattice index,\n",
       "          # 0..127). Seeds the scalar near its eventual conduction profile\n",
       "          # to shorten the transient.\n",
       "          initial_field: \"1.0 - x / 127.0\"\n",
       "          BC:\n",
       "            BC_map:\n",
       "              # Hot vertical wall (west), phi = 1, no-slip.\n",
       "              - pos: W\n",
       "                BC: ScalarRegularizedDirichlet\n",
       "                wall_normal: W\n",
       "                phi_w: 1.0\n",
       "                ux: 0.0\n",
       "                uy: 0.0\n",
       "                uz: 0.0\n",
       "              # Cold vertical wall (east), phi = 0, no-slip.\n",
       "              - pos: E\n",
       "                BC: ScalarRegularizedDirichlet\n",
       "                wall_normal: E\n",
       "                phi_w: 0.0\n",
       "                ux: 0.0\n",
       "                uy: 0.0\n",
       "                uz: 0.0\n",
       "              # Adiabatic horizontal walls (zero scalar flux).\n",
       "              - pos: N\n",
       "                BC: ScalarHWBB\n",
       "                wall_normal: N\n",
       "              - pos: S\n",
       "                BC: ScalarHWBB\n",
       "                wall_normal: S"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Code\n",
    "\n",
    "Code(filename=str(case_path))"
   ]
  }
 ],
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