Oh wow it worked lol

Author: danshapero

notebooks/frontal-ablation.ipynb

@@ -80,7 +80,24 @@
     "a = Constant(0.0)\n",
     "m_0 = Constant(-1.0)\n",
     "δm_δx = Constant(4.0)\n",
-    "m = max_value(0, δm_δx * x[0] + m_0)"
+    "#m = max_value(0, δm_δx * x[0] + m_0)\n",
+    "m = Constant(0.0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "05984ccc-9cf0-487c-aad4-e94a29b58b60",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "u_γ = Constant(-1.0)\n",
+    "x_γ = Constant(0.5)\n",
+    "h_γ = Constant(0.5)\n",
+    "\n",
+    "f_γ = h_γ * firedrake.as_vector(\n",
+    "    (firedrake.conditional(x[0] >= x_γ, u_γ, 0), 0)\n",
+    ")"
    ]
   },
   {
@@ -91,14 +108,14 @@
    "outputs": [],
    "source": [
     "ϕ = firedrake.TestFunction(Q)\n",
-    "F_cells = (Dt(h) * ϕ - inner(h * u, grad(ϕ)) - (a - m) * ϕ) * dx\n",
+    "F_cells = (Dt(h) * ϕ - inner(h * u - f_γ, grad(ϕ)) - (a - m) * ϕ) * dx\n",
     "\n",
     "ν = firedrake.FacetNormal(mesh)\n",
-    "f = max_value(0, h * inner(u, ν))\n",
+    "f = max_value(0, inner(h * u - f_γ, ν))\n",
     "F_facets = jump(f) * jump(ϕ) * dS\n",
     "\n",
-    "F_inflow = h_in * ϕ * min_value(0, inner(u, ν)) * ds\n",
-    "F_outflow = h * ϕ * max_value(0, inner(u, ν)) * ds\n",
+    "F_inflow = h_in * min_value(0, inner(u, ν)) * ϕ * ds\n",
+    "F_outflow = max_value(0, inner(h * u - f_γ, ν)) * ϕ * ds\n",
     "\n",
     "F = F_cells + F_facets + F_inflow + F_outflow"
    ]