From 0937dae5a4c77de531225c1e29ed1c32ca37c9da Mon Sep 17 00:00:00 2001
From: RemDelaporteMathurin <rdelaportemathurin@gmail.com>
Date: Wed, 2 Oct 2024 09:43:20 -0400
Subject: [PATCH] initial task

---
 tasks/task_permeation_regimes.ipynb | 40879 ++++++++++++++++++++++++++
 1 file changed, 40879 insertions(+)
 create mode 100644 tasks/task_permeation_regimes.ipynb

diff --git a/tasks/task_permeation_regimes.ipynb b/tasks/task_permeation_regimes.ipynb
new file mode 100644
index 0000000..c4cd1d7
--- /dev/null
+++ b/tasks/task_permeation_regimes.ipynb
@@ -0,0 +1,40879 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Different permeation regimes\n",
+    "\n",
+    "Let's start by making a parametric FESTIM model taking as parameters the size of the domain, the upstream pressure, the surface rate coefficients, and the diffusivity."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import festim as F\n",
+    "import numpy as np\n",
+    "\n",
+    "\n",
+    "def compute_permeation_flux(L, P_up, K_r_, K_d, D):\n",
+    "    my_model = F.Simulation(log_level=40)\n",
+    "\n",
+    "    my_model.mesh = F.MeshFromVertices(vertices=np.linspace(0, L, num=10))\n",
+    "\n",
+    "    my_model.materials = F.Material(id=1, D_0=D, E_D=0)\n",
+    "\n",
+    "    my_model.boundary_conditions = [\n",
+    "        F.DissociationFlux(Kd_0=K_d, E_Kd=0, P=P_up, surfaces=1),\n",
+    "        F.RecombinationFlux(Kr_0=K_r_, E_Kr=0, order=2, surfaces=[1, 2]),\n",
+    "    ]\n",
+    "\n",
+    "    my_model.T = 300  # ignored here\n",
+    "\n",
+    "    my_model.settings = F.Settings(\n",
+    "        absolute_tolerance=1e-7,\n",
+    "        relative_tolerance=1e-10,\n",
+    "        transient=True,\n",
+    "        final_time=100,\n",
+    "    )\n",
+    "\n",
+    "    my_model.dt = F.Stepsize(0.01, stepsize_change_ratio=1.1)\n",
+    "\n",
+    "    permeation_flux = F.HydrogenFlux(surface=2)\n",
+    "    surface_concentration = F.TotalSurface(field=\"solute\", surface=1)\n",
+    "    surface_concentration_L = F.TotalSurface(field=\"solute\", surface=2)\n",
+    "    my_model.exports = [\n",
+    "        F.DerivedQuantities(\n",
+    "            [permeation_flux, surface_concentration, surface_concentration_L],\n",
+    "            show_units=True,\n",
+    "        ),\n",
+    "        F.TXTExport(field=0, filename=f\"./pressure_{P_up:.2e}.txt\"),\n",
+    "    ]\n",
+    "\n",
+    "    my_model.initialise()\n",
+    "    my_model.run()\n",
+    "\n",
+    "    return permeation_flux, surface_concentration, surface_concentration_L"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can run this model for a range of upstream pressures. We choose arbitrary values for rate coefficients, diffusivities, and length."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " ---- P = 1.00e-06 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 1.1 s\n",
+      " ---- P = 1.78e-05 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 0.9 s\n",
+      " ---- P = 3.16e-04 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 1.0 s\n",
+      " ---- P = 5.62e-03 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 0.9 s\n",
+      " ---- P = 1.00e-01 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 0.9 s\n",
+      " ---- P = 1.78e+00 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 0.9 s\n",
+      " ---- P = 3.16e+01 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 0.8 s\n",
+      " ---- P = 5.62e+02 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 0.7 s\n",
+      " ---- P = 1.00e+04 ----\n",
+      "Defining initial values\n",
+      "Defining variational problem\n",
+      "Defining source terms\n",
+      "Defining boundary conditions\n",
+      "Time stepping...\n",
+      "100.0 %        1.0e+02 s    Elapsed time so far: 1.0 s\n"
+     ]
+    }
+   ],
+   "source": [
+    "K_r = 10\n",
+    "K_d = 100\n",
+    "L = 1\n",
+    "D = 2\n",
+    "fluxes = []\n",
+    "concentrations_0 = []\n",
+    "concentrations_L = []\n",
+    "pressures = np.logspace(-6, 4, num=9)\n",
+    "for P_up in pressures:\n",
+    "    print(f\" ---- P = {P_up:.2e} ----\")\n",
+    "    flux, c_surf_0, c_surf_L = compute_permeation_flux(L, P_up, K_r, K_d, D)\n",
+    "    fluxes.append(flux)\n",
+    "    concentrations_0.append(c_surf_0)\n",
+    "    concentrations_L.append(c_surf_L)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.colors as mcolors\n",
+    "\n",
+    "norm = mcolors.LogNorm(vmin=pressures[0], vmax=pressures[-1])\n",
+    "\n",
+    "for i, P in enumerate(pressures):\n",
+    "    plt.loglog(\n",
+    "        fluxes[i].t,\n",
+    "        np.abs(fluxes[i].data),\n",
+    "        label=f\"P={P}\",\n",
+    "        color=plt.cm.viridis(norm(P)),\n",
+    "    )\n",
+    "\n",
+    "plt.colorbar(\n",
+    "    plt.cm.ScalarMappable(norm=norm, cmap=\"viridis\"), label=\"Pressure\", ax=plt.gca()\n",
+    ")\n",
+    "plt.xlabel(\"Time\")\n",
+    "plt.ylabel(\"Permeation flux\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<link rel=\"stylesheet\"\n",
+       "href=\"https://maxcdn.bootstrapcdn.com/font-awesome/4.4.0/css/font-awesome.min.css\">\n",
+       "<script language=\"javascript\">\n",
+       "  function isInternetExplorer() {\n",
+       "    ua = navigator.userAgent;\n",
+       "    /* MSIE used to detect old browsers and Trident used to newer ones*/\n",
+       "    return ua.indexOf(\"MSIE \") > -1 || ua.indexOf(\"Trident/\") > -1;\n",
+       "  }\n",
+       "\n",
+       "  /* Define the Animation class */\n",
+       "  function Animation(frames, img_id, slider_id, interval, loop_select_id){\n",
+       "    this.img_id = img_id;\n",
+       "    this.slider_id = slider_id;\n",
+       "    this.loop_select_id = loop_select_id;\n",
+       "    this.interval = interval;\n",
+       "    this.current_frame = 0;\n",
+       "    this.direction = 0;\n",
+       "    this.timer = null;\n",
+       "    this.frames = new Array(frames.length);\n",
+       "\n",
+       "    for (var i=0; i<frames.length; i++)\n",
+       "    {\n",
+       "     this.frames[i] = new Image();\n",
+       "     this.frames[i].src = frames[i];\n",
+       "    }\n",
+       "    var slider = document.getElementById(this.slider_id);\n",
+       "    slider.max = this.frames.length - 1;\n",
+       "    if (isInternetExplorer()) {\n",
+       "        // switch from oninput to onchange because IE <= 11 does not conform\n",
+       "        // with W3C specification. It ignores oninput and onchange behaves\n",
+       "        // like oninput. In contrast, Microsoft Edge behaves correctly.\n",
+       "        slider.setAttribute('onchange', slider.getAttribute('oninput'));\n",
+       "        slider.setAttribute('oninput', null);\n",
+       "    }\n",
+       "    this.set_frame(this.current_frame);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.get_loop_state = function(){\n",
+       "    var button_group = document[this.loop_select_id].state;\n",
+       "    for (var i = 0; i < button_group.length; i++) {\n",
+       "        var button = button_group[i];\n",
+       "        if (button.checked) {\n",
+       "            return button.value;\n",
+       "        }\n",
+       "    }\n",
+       "    return undefined;\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.set_frame = function(frame){\n",
+       "    this.current_frame = frame;\n",
+       "    document.getElementById(this.img_id).src =\n",
+       "            this.frames[this.current_frame].src;\n",
+       "    document.getElementById(this.slider_id).value = this.current_frame;\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.next_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(Math.min(this.frames.length - 1, this.current_frame + 1));\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.previous_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(Math.max(0, this.current_frame - 1));\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.first_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(0);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.last_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(this.frames.length - 1);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.slower = function()\n",
+       "  {\n",
+       "    this.interval /= 0.7;\n",
+       "    if(this.direction > 0){this.play_animation();}\n",
+       "    else if(this.direction < 0){this.reverse_animation();}\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.faster = function()\n",
+       "  {\n",
+       "    this.interval *= 0.7;\n",
+       "    if(this.direction > 0){this.play_animation();}\n",
+       "    else if(this.direction < 0){this.reverse_animation();}\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.anim_step_forward = function()\n",
+       "  {\n",
+       "    this.current_frame += 1;\n",
+       "    if(this.current_frame < this.frames.length){\n",
+       "      this.set_frame(this.current_frame);\n",
+       "    }else{\n",
+       "      var loop_state = this.get_loop_state();\n",
+       "      if(loop_state == \"loop\"){\n",
+       "        this.first_frame();\n",
+       "      }else if(loop_state == \"reflect\"){\n",
+       "        this.last_frame();\n",
+       "        this.reverse_animation();\n",
+       "      }else{\n",
+       "        this.pause_animation();\n",
+       "        this.last_frame();\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.anim_step_reverse = function()\n",
+       "  {\n",
+       "    this.current_frame -= 1;\n",
+       "    if(this.current_frame >= 0){\n",
+       "      this.set_frame(this.current_frame);\n",
+       "    }else{\n",
+       "      var loop_state = this.get_loop_state();\n",
+       "      if(loop_state == \"loop\"){\n",
+       "        this.last_frame();\n",
+       "      }else if(loop_state == \"reflect\"){\n",
+       "        this.first_frame();\n",
+       "        this.play_animation();\n",
+       "      }else{\n",
+       "        this.pause_animation();\n",
+       "        this.first_frame();\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.pause_animation = function()\n",
+       "  {\n",
+       "    this.direction = 0;\n",
+       "    if (this.timer){\n",
+       "      clearInterval(this.timer);\n",
+       "      this.timer = null;\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.play_animation = function()\n",
+       "  {\n",
+       "    this.pause_animation();\n",
+       "    this.direction = 1;\n",
+       "    var t = this;\n",
+       "    if (!this.timer) this.timer = setInterval(function() {\n",
+       "        t.anim_step_forward();\n",
+       "    }, this.interval);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.reverse_animation = function()\n",
+       "  {\n",
+       "    this.pause_animation();\n",
+       "    this.direction = -1;\n",
+       "    var t = this;\n",
+       "    if (!this.timer) this.timer = setInterval(function() {\n",
+       "        t.anim_step_reverse();\n",
+       "    }, this.interval);\n",
+       "  }\n",
+       "</script>\n",
+       "\n",
+       "<style>\n",
+       ".animation {\n",
+       "    display: inline-block;\n",
+       "    text-align: center;\n",
+       "}\n",
+       "input[type=range].anim-slider {\n",
+       "    width: 374px;\n",
+       "    margin-left: auto;\n",
+       "    margin-right: auto;\n",
+       "}\n",
+       ".anim-buttons {\n",
+       "    margin: 8px 0px;\n",
+       "}\n",
+       ".anim-buttons button {\n",
+       "    padding: 0;\n",
+       "    width: 36px;\n",
+       "}\n",
+       ".anim-state label {\n",
+       "    margin-right: 8px;\n",
+       "}\n",
+       ".anim-state input {\n",
+       "    margin: 0;\n",
+       "    vertical-align: middle;\n",
+       "}\n",
+       "</style>\n",
+       "\n",
+       "<div class=\"animation\">\n",
+       "  <img id=\"_anim_img12a8f89698a9499183863d171254910a\">\n",
+       "  <div class=\"anim-controls\">\n",
+       "    <input id=\"_anim_slider12a8f89698a9499183863d171254910a\" type=\"range\" class=\"anim-slider\"\n",
+       "           name=\"points\" min=\"0\" max=\"1\" step=\"1\" value=\"0\"\n",
+       "           oninput=\"anim12a8f89698a9499183863d171254910a.set_frame(parseInt(this.value));\">\n",
+       "    <div class=\"anim-buttons\">\n",
+       "      <button title=\"Decrease speed\" aria-label=\"Decrease speed\" onclick=\"anim12a8f89698a9499183863d171254910a.slower()\">\n",
+       "          <i class=\"fa fa-minus\"></i></button>\n",
+       "      <button title=\"First frame\" aria-label=\"First frame\" onclick=\"anim12a8f89698a9499183863d171254910a.first_frame()\">\n",
+       "        <i class=\"fa fa-fast-backward\"></i></button>\n",
+       "      <button title=\"Previous frame\" aria-label=\"Previous frame\" onclick=\"anim12a8f89698a9499183863d171254910a.previous_frame()\">\n",
+       "          <i class=\"fa fa-step-backward\"></i></button>\n",
+       "      <button title=\"Play backwards\" aria-label=\"Play backwards\" onclick=\"anim12a8f89698a9499183863d171254910a.reverse_animation()\">\n",
+       "          <i class=\"fa fa-play fa-flip-horizontal\"></i></button>\n",
+       "      <button title=\"Pause\" aria-label=\"Pause\" onclick=\"anim12a8f89698a9499183863d171254910a.pause_animation()\">\n",
+       "          <i class=\"fa fa-pause\"></i></button>\n",
+       "      <button title=\"Play\" aria-label=\"Play\" onclick=\"anim12a8f89698a9499183863d171254910a.play_animation()\">\n",
+       "          <i class=\"fa fa-play\"></i></button>\n",
+       "      <button title=\"Next frame\" aria-label=\"Next frame\" onclick=\"anim12a8f89698a9499183863d171254910a.next_frame()\">\n",
+       "          <i class=\"fa fa-step-forward\"></i></button>\n",
+       "      <button title=\"Last frame\" aria-label=\"Last frame\" onclick=\"anim12a8f89698a9499183863d171254910a.last_frame()\">\n",
+       "          <i class=\"fa fa-fast-forward\"></i></button>\n",
+       "      <button title=\"Increase speed\" aria-label=\"Increase speed\" onclick=\"anim12a8f89698a9499183863d171254910a.faster()\">\n",
+       "          <i class=\"fa fa-plus\"></i></button>\n",
+       "    </div>\n",
+       "    <form title=\"Repetition mode\" aria-label=\"Repetition mode\" action=\"#n\" name=\"_anim_loop_select12a8f89698a9499183863d171254910a\"\n",
+       "          class=\"anim-state\">\n",
+       "      <input type=\"radio\" name=\"state\" value=\"once\" id=\"_anim_radio1_12a8f89698a9499183863d171254910a\"\n",
+       "             >\n",
+       "      <label for=\"_anim_radio1_12a8f89698a9499183863d171254910a\">Once</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"loop\" id=\"_anim_radio2_12a8f89698a9499183863d171254910a\"\n",
+       "             checked>\n",
+       "      <label for=\"_anim_radio2_12a8f89698a9499183863d171254910a\">Loop</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"reflect\" id=\"_anim_radio3_12a8f89698a9499183863d171254910a\"\n",
+       "             >\n",
+       "      <label for=\"_anim_radio3_12a8f89698a9499183863d171254910a\">Reflect</label>\n",
+       "    </form>\n",
+       "  </div>\n",
+       "</div>\n",
+       "\n",
+       "\n",
+       "<script language=\"javascript\">\n",
+       "  /* Instantiate the Animation class. */\n",
+       "  /* The IDs given should match those used in the template above. */\n",
+       "  (function() {\n",
+       "    var img_id = \"_anim_img12a8f89698a9499183863d171254910a\";\n",
+       "    var slider_id = \"_anim_slider12a8f89698a9499183863d171254910a\";\n",
+       "    var loop_select_id = \"_anim_loop_select12a8f89698a9499183863d171254910a\";\n",
+       "    var frames = new Array(73);\n",
+       "    \n",
+       "  frames[0] = \"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90\\\n",
+       "bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9h\\\n",
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+       "SzjttDHlKNq03nZSqxVtH7ltq+JWVGs55hjR2KSbtCl5IfOCrAVdpTCTISzBtFDhu380nu34A+IY\\\n",
+       "53D5vp6Px++hfM/n9/19fvwi3v7O7/c7LmOMEQAAAKzRpa0bAAAAQHARAAEAACxDAAQAALAMARAA\\\n",
+       "AMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAA\\\n",
+       "AMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAA\\\n",
+       "LEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACw\\\n",
+       "DAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAy\\\n",
+       "BEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQ\\\n",
+       "AAEAACxDAAQAALAMARAAAMAyBEAAAADLEAABAAAsQwAEAACwDAEQAADAMgTAH8AYo9raWhlj2roV\\\n",
+       "AACAFiMA/gDHjh1TRESEjh071tatAAAAtBgBEAAAwDIEQAAAAMsQAAEAACxDAAQAALAMARAAAMAy\\\n",
+       "BEAAAADLEAABAAAsQwAEAACwDAEQAADAMgRAAAAAyxAAAQAALEMABAAAsAwBEAAAwDIEQAAAAMsQ\\\n",
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+       "AABJRU5ErkJggg==\\\n",
+       "\"\n",
+       "\n",
+       "\n",
+       "    /* set a timeout to make sure all the above elements are created before\n",
+       "       the object is initialized. */\n",
+       "    setTimeout(function() {\n",
+       "        anim12a8f89698a9499183863d171254910a = new Animation(frames, img_id, slider_id, 50.0,\n",
+       "                                 loop_select_id);\n",
+       "    }, 0);\n",
+       "  })()\n",
+       "</script>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.animation as animation\n",
+    "from IPython.display import HTML\n",
+    "\n",
+    "def make_animation(P):\n",
+    "    data = np.genfromtxt(\n",
+    "        f\"pressure_{P:.2e}.txt\", delimiter=\",\", skip_header=1\n",
+    "    )\n",
+    "\n",
+    "\n",
+    "    x = data[:, 0]\n",
+    "    # order x\n",
+    "    order = np.argsort(x)\n",
+    "    x = x[order]\n",
+    "\n",
+    "    fig, ax = plt.subplots()\n",
+    "    (line1,) = ax.plot([], [], lw=2, color=\"black\")\n",
+    "\n",
+    "    def init():\n",
+    "        line1.set_data([], [])\n",
+    "        ax.set_xlim(0, L)\n",
+    "        ax.set_ylim(bottom=0, top=np.max(data[:, 1:])*1.1)\n",
+    "        ax.set_xlabel(r\"x\")\n",
+    "        ax.set_ylabel(r\"H concentration\")\n",
+    "        ax.spines[\"top\"].set_visible(False)\n",
+    "        ax.spines[\"right\"].set_visible(False)\n",
+    "\n",
+    "        return [line1]\n",
+    "\n",
+    "\n",
+    "    def animate(i):\n",
+    "        c = data[:, i+1][order]\n",
+    "        line1.set_data(x, c)\n",
+    "        return [line1]\n",
+    "\n",
+    "\n",
+    "    # Call the animator\n",
+    "    ani = animation.FuncAnimation(\n",
+    "        fig, animate, init_func=init, frames=data.shape[1]-1, interval=50, blit=True\n",
+    "    )\n",
+    "\n",
+    "    plt.close(fig)\n",
+    "\n",
+    "    return HTML(ani.to_jshtml())\n",
+    "\n",
+    "make_animation(pressures[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<link rel=\"stylesheet\"\n",
+       "href=\"https://maxcdn.bootstrapcdn.com/font-awesome/4.4.0/css/font-awesome.min.css\">\n",
+       "<script language=\"javascript\">\n",
+       "  function isInternetExplorer() {\n",
+       "    ua = navigator.userAgent;\n",
+       "    /* MSIE used to detect old browsers and Trident used to newer ones*/\n",
+       "    return ua.indexOf(\"MSIE \") > -1 || ua.indexOf(\"Trident/\") > -1;\n",
+       "  }\n",
+       "\n",
+       "  /* Define the Animation class */\n",
+       "  function Animation(frames, img_id, slider_id, interval, loop_select_id){\n",
+       "    this.img_id = img_id;\n",
+       "    this.slider_id = slider_id;\n",
+       "    this.loop_select_id = loop_select_id;\n",
+       "    this.interval = interval;\n",
+       "    this.current_frame = 0;\n",
+       "    this.direction = 0;\n",
+       "    this.timer = null;\n",
+       "    this.frames = new Array(frames.length);\n",
+       "\n",
+       "    for (var i=0; i<frames.length; i++)\n",
+       "    {\n",
+       "     this.frames[i] = new Image();\n",
+       "     this.frames[i].src = frames[i];\n",
+       "    }\n",
+       "    var slider = document.getElementById(this.slider_id);\n",
+       "    slider.max = this.frames.length - 1;\n",
+       "    if (isInternetExplorer()) {\n",
+       "        // switch from oninput to onchange because IE <= 11 does not conform\n",
+       "        // with W3C specification. It ignores oninput and onchange behaves\n",
+       "        // like oninput. In contrast, Microsoft Edge behaves correctly.\n",
+       "        slider.setAttribute('onchange', slider.getAttribute('oninput'));\n",
+       "        slider.setAttribute('oninput', null);\n",
+       "    }\n",
+       "    this.set_frame(this.current_frame);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.get_loop_state = function(){\n",
+       "    var button_group = document[this.loop_select_id].state;\n",
+       "    for (var i = 0; i < button_group.length; i++) {\n",
+       "        var button = button_group[i];\n",
+       "        if (button.checked) {\n",
+       "            return button.value;\n",
+       "        }\n",
+       "    }\n",
+       "    return undefined;\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.set_frame = function(frame){\n",
+       "    this.current_frame = frame;\n",
+       "    document.getElementById(this.img_id).src =\n",
+       "            this.frames[this.current_frame].src;\n",
+       "    document.getElementById(this.slider_id).value = this.current_frame;\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.next_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(Math.min(this.frames.length - 1, this.current_frame + 1));\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.previous_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(Math.max(0, this.current_frame - 1));\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.first_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(0);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.last_frame = function()\n",
+       "  {\n",
+       "    this.set_frame(this.frames.length - 1);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.slower = function()\n",
+       "  {\n",
+       "    this.interval /= 0.7;\n",
+       "    if(this.direction > 0){this.play_animation();}\n",
+       "    else if(this.direction < 0){this.reverse_animation();}\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.faster = function()\n",
+       "  {\n",
+       "    this.interval *= 0.7;\n",
+       "    if(this.direction > 0){this.play_animation();}\n",
+       "    else if(this.direction < 0){this.reverse_animation();}\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.anim_step_forward = function()\n",
+       "  {\n",
+       "    this.current_frame += 1;\n",
+       "    if(this.current_frame < this.frames.length){\n",
+       "      this.set_frame(this.current_frame);\n",
+       "    }else{\n",
+       "      var loop_state = this.get_loop_state();\n",
+       "      if(loop_state == \"loop\"){\n",
+       "        this.first_frame();\n",
+       "      }else if(loop_state == \"reflect\"){\n",
+       "        this.last_frame();\n",
+       "        this.reverse_animation();\n",
+       "      }else{\n",
+       "        this.pause_animation();\n",
+       "        this.last_frame();\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.anim_step_reverse = function()\n",
+       "  {\n",
+       "    this.current_frame -= 1;\n",
+       "    if(this.current_frame >= 0){\n",
+       "      this.set_frame(this.current_frame);\n",
+       "    }else{\n",
+       "      var loop_state = this.get_loop_state();\n",
+       "      if(loop_state == \"loop\"){\n",
+       "        this.last_frame();\n",
+       "      }else if(loop_state == \"reflect\"){\n",
+       "        this.first_frame();\n",
+       "        this.play_animation();\n",
+       "      }else{\n",
+       "        this.pause_animation();\n",
+       "        this.first_frame();\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.pause_animation = function()\n",
+       "  {\n",
+       "    this.direction = 0;\n",
+       "    if (this.timer){\n",
+       "      clearInterval(this.timer);\n",
+       "      this.timer = null;\n",
+       "    }\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.play_animation = function()\n",
+       "  {\n",
+       "    this.pause_animation();\n",
+       "    this.direction = 1;\n",
+       "    var t = this;\n",
+       "    if (!this.timer) this.timer = setInterval(function() {\n",
+       "        t.anim_step_forward();\n",
+       "    }, this.interval);\n",
+       "  }\n",
+       "\n",
+       "  Animation.prototype.reverse_animation = function()\n",
+       "  {\n",
+       "    this.pause_animation();\n",
+       "    this.direction = -1;\n",
+       "    var t = this;\n",
+       "    if (!this.timer) this.timer = setInterval(function() {\n",
+       "        t.anim_step_reverse();\n",
+       "    }, this.interval);\n",
+       "  }\n",
+       "</script>\n",
+       "\n",
+       "<style>\n",
+       ".animation {\n",
+       "    display: inline-block;\n",
+       "    text-align: center;\n",
+       "}\n",
+       "input[type=range].anim-slider {\n",
+       "    width: 374px;\n",
+       "    margin-left: auto;\n",
+       "    margin-right: auto;\n",
+       "}\n",
+       ".anim-buttons {\n",
+       "    margin: 8px 0px;\n",
+       "}\n",
+       ".anim-buttons button {\n",
+       "    padding: 0;\n",
+       "    width: 36px;\n",
+       "}\n",
+       ".anim-state label {\n",
+       "    margin-right: 8px;\n",
+       "}\n",
+       ".anim-state input {\n",
+       "    margin: 0;\n",
+       "    vertical-align: middle;\n",
+       "}\n",
+       "</style>\n",
+       "\n",
+       "<div class=\"animation\">\n",
+       "  <img id=\"_anim_img5d5d507abfb44300af9e02f42533f849\">\n",
+       "  <div class=\"anim-controls\">\n",
+       "    <input id=\"_anim_slider5d5d507abfb44300af9e02f42533f849\" type=\"range\" class=\"anim-slider\"\n",
+       "           name=\"points\" min=\"0\" max=\"1\" step=\"1\" value=\"0\"\n",
+       "           oninput=\"anim5d5d507abfb44300af9e02f42533f849.set_frame(parseInt(this.value));\">\n",
+       "    <div class=\"anim-buttons\">\n",
+       "      <button title=\"Decrease speed\" aria-label=\"Decrease speed\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.slower()\">\n",
+       "          <i class=\"fa fa-minus\"></i></button>\n",
+       "      <button title=\"First frame\" aria-label=\"First frame\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.first_frame()\">\n",
+       "        <i class=\"fa fa-fast-backward\"></i></button>\n",
+       "      <button title=\"Previous frame\" aria-label=\"Previous frame\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.previous_frame()\">\n",
+       "          <i class=\"fa fa-step-backward\"></i></button>\n",
+       "      <button title=\"Play backwards\" aria-label=\"Play backwards\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.reverse_animation()\">\n",
+       "          <i class=\"fa fa-play fa-flip-horizontal\"></i></button>\n",
+       "      <button title=\"Pause\" aria-label=\"Pause\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.pause_animation()\">\n",
+       "          <i class=\"fa fa-pause\"></i></button>\n",
+       "      <button title=\"Play\" aria-label=\"Play\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.play_animation()\">\n",
+       "          <i class=\"fa fa-play\"></i></button>\n",
+       "      <button title=\"Next frame\" aria-label=\"Next frame\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.next_frame()\">\n",
+       "          <i class=\"fa fa-step-forward\"></i></button>\n",
+       "      <button title=\"Last frame\" aria-label=\"Last frame\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.last_frame()\">\n",
+       "          <i class=\"fa fa-fast-forward\"></i></button>\n",
+       "      <button title=\"Increase speed\" aria-label=\"Increase speed\" onclick=\"anim5d5d507abfb44300af9e02f42533f849.faster()\">\n",
+       "          <i class=\"fa fa-plus\"></i></button>\n",
+       "    </div>\n",
+       "    <form title=\"Repetition mode\" aria-label=\"Repetition mode\" action=\"#n\" name=\"_anim_loop_select5d5d507abfb44300af9e02f42533f849\"\n",
+       "          class=\"anim-state\">\n",
+       "      <input type=\"radio\" name=\"state\" value=\"once\" id=\"_anim_radio1_5d5d507abfb44300af9e02f42533f849\"\n",
+       "             >\n",
+       "      <label for=\"_anim_radio1_5d5d507abfb44300af9e02f42533f849\">Once</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"loop\" id=\"_anim_radio2_5d5d507abfb44300af9e02f42533f849\"\n",
+       "             checked>\n",
+       "      <label for=\"_anim_radio2_5d5d507abfb44300af9e02f42533f849\">Loop</label>\n",
+       "      <input type=\"radio\" name=\"state\" value=\"reflect\" id=\"_anim_radio3_5d5d507abfb44300af9e02f42533f849\"\n",
+       "             >\n",
+       "      <label for=\"_anim_radio3_5d5d507abfb44300af9e02f42533f849\">Reflect</label>\n",
+       "    </form>\n",
+       "  </div>\n",
+       "</div>\n",
+       "\n",
+       "\n",
+       "<script language=\"javascript\">\n",
+       "  /* Instantiate the Animation class. */\n",
+       "  /* The IDs given should match those used in the template above. */\n",
+       "  (function() {\n",
+       "    var img_id = \"_anim_img5d5d507abfb44300af9e02f42533f849\";\n",
+       "    var slider_id = \"_anim_slider5d5d507abfb44300af9e02f42533f849\";\n",
+       "    var loop_select_id = \"_anim_loop_select5d5d507abfb44300af9e02f42533f849\";\n",
+       "    var frames = new Array(75);\n",
+       "    \n",
+       "  frames[0] = \"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90\\\n",
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+       "v/6qTJkymR0LAFIMBRAA/uLWrVsqU6aMTp8+rT179qhcuXJmRwKAFMUxgADwFydOnNAff/yhpKQk\\\n",
+       "/f7772bHAYAUxxZAAPiTO3fuqFq1aqpQoYJ8fX01YcIEhYWFKX/+/GZHA4AUQwEEgD/p16+flixZ\\\n",
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+       "AGAxFEAAAACLoQACAABYDAUQAADAYiiAAAAAFkMBBAAAsJj/B0eiXFrYfkREAAAAAElFTkSuQmCC\\\n",
+       "\"\n",
+       "\n",
+       "\n",
+       "    /* set a timeout to make sure all the above elements are created before\n",
+       "       the object is initialized. */\n",
+       "    setTimeout(function() {\n",
+       "        anim5d5d507abfb44300af9e02f42533f849 = new Animation(frames, img_id, slider_id, 50.0,\n",
+       "                                 loop_select_id);\n",
+       "    }, 0);\n",
+       "  })()\n",
+       "</script>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "make_animation(pressures[-4])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Evolution of the permeation flux as a function of pressure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "steady_state_fluxes = np.abs([flux.data[-1] for flux in fluxes])\n",
+    "\n",
+    "plt.plot(pressures, steady_state_fluxes, marker=\"o\")\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel(\"Pressure\")\n",
+    "plt.ylabel(\"Steady state permeation flux\")\n",
+    "\n",
+    "Ps_linear = np.logspace(-7, -1)\n",
+    "Ps_squared = np.logspace(1, 6)\n",
+    "plt.plot(Ps_linear, Ps_linear * 100, linestyle=\"--\", color=\"gray\")\n",
+    "plt.plot(Ps_squared, Ps_squared**0.5 * 10, linestyle=\"--\", color=\"gray\")\n",
+    "\n",
+    "plt.annotate(r\"$\\propto P$\", (1e-6, 1e-3), color=\"gray\")\n",
+    "plt.annotate(r\"$\\propto P^{0.5}$\", (1e3, 1e3) , color=\"gray\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Validity of hypotheses on surface concentrations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(pressures, [c.data[-1] for c in concentrations_0], marker=\"o\")\n",
+    "plt.xscale(\"log\")\n",
+    "plt.yscale(\"log\")\n",
+    "plt.xlabel(\"Pressure\")\n",
+    "plt.ylabel(\"Steady state surface concentration\")\n",
+    "\n",
+    "plt.plot(\n",
+    "    pressures, (np.array(pressures) * K_d / K_r) ** 0.5, linestyle=\"--\", color=\"gray\"\n",
+    ")\n",
+    "\n",
+    "for i, P in enumerate(pressures):\n",
+    "    plt.scatter(np.ones_like(concentrations_0[i].data) * P, concentrations_0[i].data, alpha=0.1)\n",
+    "\n",
+    "plt.annotate(\"Sievert's law\", (1e-4, 1e0), textcoords=\"data\", color=\"gray\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i, P in enumerate(pressures):\n",
+    "    ratio = np.array(concentrations_L[i].data) / np.array(concentrations_0[i].data)\n",
+    "    plt.loglog(\n",
+    "        concentrations_L[i].t, ratio, label=f\"P={P}\", color=plt.cm.viridis(norm(P))\n",
+    "    )\n",
+    "\n",
+    "plt.xlabel(\"Time\")\n",
+    "plt.ylabel(\"Ratio of surface concentrations\")\n",
+    "plt.colorbar(\n",
+    "    plt.cm.ScalarMappable(norm=norm, cmap=\"viridis\"), label=\"Pressure\", ax=plt.gca()\n",
+    ")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "At high pressures (diffusion-limited regime), the concentration on the downstream is negligible to the concentration on the upstream surface.\n",
+    "\n",
+    "However, at low pressures (surface-limited regime), both concentrations are more and more comparable and assuming $c=0$ on the downstream face isn't valid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, '$c_L$')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "c0s = np.linspace(0, 1e4)\n",
+    "cls = np.linspace(0, 1e4)\n",
+    "P = 1e6\n",
+    "c00, cll = np.meshgrid(c0s, cls)\n",
+    "\n",
+    "flux_left = -K_d * P + K_r * c00**2\n",
+    "flux_right = K_r * cll**2\n",
+    "\n",
+    "ZZ = flux_left - flux_right\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.figure()\n",
+    "plt.contour(c0s, cls, ZZ, levels=[0], colors=\"black\")\n",
+    "# plt.contourf(c0s, cls, np.abs(ZZ), levels=100)\n",
+    "\n",
+    "plt.xlabel(\"$c_0$\")\n",
+    "plt.ylabel(\"$c_L$\")\n",
+    "# plt.xscale('log')\n",
+    "# plt.yscale('log')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "festim-workshop",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}