CEE314Problemsets5Q4Teaching.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/AlexCHEN-Engineer/CEE314HW/blob/main/CEE314Problemsets5Q4Teaching.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mediterranean-century"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "# Do not revise here. \n",
        "try:\n",
        "    import google.colab\n",
        "except ImportError:\n",
        "    import ufl\n",
        "    import dolfin\n",
        "    import mshr\n",
        "else:\n",
        "    try:\n",
        "        import ufl\n",
        "        import dolfin\n",
        "        import mshr\n",
        "    except ImportError:\n",
        "        !wget \"https://fem-on-colab.github.io/releases/fenics-install.sh\" -O \"/tmp/fenics-install.sh\" && bash \"/tmp/fenics-install.sh\"\n",
        "        import ufl\n",
        "        import dolfin\n",
        "        import mshr"
      ],
      "id": "mediterranean-century"
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Variational formulation\n",
        "\n",
        "In this part, we will solve a coupled poromechanics problems.\n",
        "\n",
        "For a domain denoted as $\\Omega$, the boundary is $\\Gamma = \\Gamma_u\\cup \\Gamma_t = \\Gamma_p\\cup\\Gamma_q$, $\\Gamma_u\\cap \\Gamma_t=\\phi$ and $\\Gamma_p\\cup\\Gamma_q=\\phi$. \n",
        "\n",
        "The strong form can be expressed as:\n",
        "\\begin{equation}\n",
        "\\begin{aligned}\n",
        "&\\nabla\\cdot(\\boldsymbol{\\sigma}^\\prime-p\\boldsymbol{1})+\\rho\\boldsymbol{g}=\\boldsymbol{0},   \\\\\n",
        "&\\nabla⋅\\dot{\\boldsymbol{u}}+\\nabla⋅{\\boldsymbol{q}}=0, \\\\\n",
        "& \\boldsymbol{u} = \\overline{\\boldsymbol{u}}\\quad on \\quad \\Gamma_u, \\\\\n",
        "& \\boldsymbol{\\sigma}^\\prime\\cdot\\boldsymbol{n} = \\overline{\\boldsymbol{t}}\\quad on\\quad \\Gamma_t, \\\\\n",
        "& p = \\overline{p}\\quad on \\quad \\Gamma_p, \\\\\n",
        "& \\boldsymbol{q}\\cdot \\boldsymbol{n} = \\overline{q}\\quad on \\quad \\Gamma_q.\n",
        "\\end{aligned}\n",
        "\\end{equation}\n",
        "\n",
        "As for the constitutive equations, we need to refer to\n",
        "\\begin{equation}\n",
        "\\begin{aligned}\n",
        "& \\boldsymbol{\\sigma}^\\prime = \\mathbb{C}^e:\\boldsymbol{\\epsilon} ,\\\\\n",
        "& \\boldsymbol{q} = -\\frac{\\boldsymbol{\\kappa}}{\\mu_f}\\cdot \\nabla p.\n",
        "\\end{aligned}\n",
        "\\end{equation}\n"
      ],
      "metadata": {
        "id": "P2bXKmcEqOJN"
      },
      "id": "P2bXKmcEqOJN"
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Derive the weak form\n",
        "\n",
        "The trial space is defined as \n",
        "\\begin{equation}\n",
        "\\begin{aligned}\n",
        "& S_u = \\{\\boldsymbol{u}:\\Omega→\\mathbb{R}^{ndim}|\\boldsymbol{u}→\\boldsymbol{H}^1,\\ \\boldsymbol{u}=\\overline{\\boldsymbol{u}}\\quad on \\quad \\Gamma_u \\} ,\\\\\n",
        "&S_p = \\{p:\\Omega→\\mathbb{R}|p→H^1,\\ p=\\overline{p}\\quad on \\quad \\Gamma_p \\}\n",
        "\\end{aligned}\n",
        "\\end{equation}\n",
        "\n",
        "For the weighting space,\n",
        "\\begin{equation}\n",
        "\\begin{aligned}\n",
        "& V_u = \\{\\boldsymbol{\\eta}:\\Omega→\\mathbb{R}^{ndim}|\\boldsymbol{\\eta}→\\boldsymbol{H}^1,\\ \\boldsymbol{\\eta}={\\boldsymbol{0}}\\quad on \\quad \\Gamma_u \\} ,\\\\\n",
        "&V_\\psi = \\{\\psi:\\Omega→\\mathbb{R}|\\psi→H^1,\\ \\psi=0\\quad on \\quad \\Gamma_\\psi \\}\n",
        "\\end{aligned}\n",
        "\\end{equation}\n"
      ],
      "metadata": {
        "id": "MLHKWGvgv_Cg"
      },
      "id": "MLHKWGvgv_Cg"
    },
    {
      "cell_type": "markdown",
      "source": [
        "The weak form becomes:\n",
        "\\begin{equation}\n",
        "\\begin{aligned}\n",
        "& \\mathcal{G}_1 = \\int_{\\Omega}(\\nabla^s\\boldsymbol{\\eta}:\\boldsymbol{\\sigma}^\\prime-p\\nabla\\cdot\\boldsymbol{\\eta}-\\boldsymbol{\\eta}\\cdot{\\rho}\\boldsymbol{g})dV - \\int_{\\Gamma_t}\\boldsymbol{\\eta}\\cdot\\overline{\\boldsymbol{t}}dA = \\boldsymbol{0} \\\\\n",
        "& \\mathcal{G}_2 = \\int_{\\Omega}(\\psi\\nabla\\cdot\\dot{\\boldsymbol{u}}-\\nabla \\psi\\cdot \\boldsymbol{q})dV + \\int_{\\Gamma_q} \\psi\\bar{q}dA\\\\\n",
        "\\end{aligned}\n",
        "\\end{equation}"
      ],
      "metadata": {
        "id": "62rA3t9lxyo6"
      },
      "id": "62rA3t9lxyo6"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yWGBMCZ5jAX2"
      },
      "source": [
        "# Import necessary library"
      ],
      "id": "yWGBMCZ5jAX2"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "infectious-train"
      },
      "outputs": [],
      "source": [
        "from fenics import *\n",
        "from mshr import *\n",
        "from ufl import nabla_div"
      ],
      "id": "infectious-train"
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Parameters\n",
        "\n",
        "For the conversion between elastic modulus, refer to this [wiki page](https://en.wikipedia.org/wiki/Elastic_modulus)."
      ],
      "metadata": {
        "id": "PsmZYVTj5Fd3"
      },
      "id": "PsmZYVTj5Fd3"
    },
    {
      "cell_type": "code",
      "source": [
        "##############################\n",
        "## TODO: Set the parameters ##\n",
        "##############################\n",
        "# You need to set different parameters to run the simulation!\n",
        "# T = 1\n",
        "# num_steps = 100\n",
        "\n",
        "dt = T / (1.0*num_steps) #time step size\n",
        "\n",
        "rho_l = 1000\n",
        "\n",
        "E = 10.e7 #Pa\n",
        "nu = 0\n",
        "k = 1.15740741e-10 \t#intrinsic permeability\n",
        "mu_l = 1e-2 \t#dynamic viscosity\n",
        "\n",
        "lambda_= E*nu/(1+nu)/(1-2*nu)\n",
        "mu = E/2/(1+nu);"
      ],
      "metadata": {
        "id": "4Au2rvfqZMTc"
      },
      "id": "4Au2rvfqZMTc",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create mesh and define expression\n",
        "# Parameters\n",
        "R = 1.\n",
        "# Create geometry\n",
        "s = Sphere(Point(0, 0, 0), 1)\n",
        "# s2 = Sphere(Point(x, y, z), r)\n",
        "b1 = Box(Point(0., 0., 0.), Point(1., 1., 1.))\n",
        "geometry = s*b1\n",
        "# Create mesh\n",
        "mesh = generate_mesh(geometry, 15)\n",
        "plot(mesh)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "MffHpj3RrAzL",
        "outputId": "bf875d35-c65f-4010-f65d-820fc0f96657"
      },
      "id": "MffHpj3RrAzL",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outer =  CompiledSubDomain(\"x[0]*x[0] + x[1]*x[1] + x[2]*x[2] > 0.9\")\n",
        "cutX =  CompiledSubDomain(\"near(x[0], side)\", side = 0.0)\n",
        "cutY =  CompiledSubDomain(\"near(x[1], side)\", side = 0.0)\n",
        "cutZ = CompiledSubDomain(\"near(x[2], side)\", side = 0.0)\n",
        "\n",
        "boundary = MeshFunction('size_t', mesh, mesh.topology().dim()-1)\n",
        "boundary.set_all(1)\n",
        "outer.mark(boundary, 2)\n",
        "ds = Measure('ds', domain = mesh, subdomain_data = boundary)\n",
        "\n",
        "\n",
        "T  = 100 * Expression(('-x[0]', '-x[1]','-x[2]'), degree=1)  # Load on the boundary\n",
        "\n",
        "#Define Mixed Space (R2,R) -> (u,p)\n",
        "V = VectorElement(\"CG\", mesh.ufl_cell(), 2)\n",
        "W = FiniteElement(\"CG\", mesh.ufl_cell(), 1)\n",
        "L = FunctionSpace(mesh,W)\n",
        "MS = dolfin.FunctionSpace(mesh, MixedElement([V,W]))\n",
        "\n",
        "# Define boundary condition\n",
        "bcu1 = DirichletBC(MS.sub(0).sub(0), 0.0, cutX)  # slip condition\n",
        "bcu2 = DirichletBC(MS.sub(0).sub(1), 0.0, cutY)  # slip condition\n",
        "bcu3 = DirichletBC(MS.sub(0).sub(2), 0.0, cutZ)  # slip condition\n",
        "bcp = DirichletBC(MS.sub(1), 0.0, outer) # drained condition\n",
        "bc=[bcu1,bcu2,bcu3,bcp]\n",
        "\n",
        "# Define strain\n",
        "def epsilon(u):\n",
        "    return 0.5*(nabla_grad(u) + nabla_grad(u).T)\n",
        "\n",
        "def sigma(u):\n",
        "   return lambda_ * tr(epsilon(u))*Identity(3) + 2.0*mu*epsilon(u)\n",
        "\n",
        "# Define variational problem and initial condition\n",
        "X0 = Function(MS)\n",
        "B = TestFunction(MS)\n",
        "\n",
        "e_u0 = Expression(('0.0', '0.0', '0.0'), degree=1)\n",
        "e_p0 = Expression('0.0', degree=1)\n",
        "\n",
        "u0 = interpolate(e_u0, MS.sub(0).collapse())\n",
        "p0 = interpolate(e_p0, MS.sub(1).collapse())\n",
        "\n",
        "Xn = Function(MS)\n",
        "assign(Xn, [u0, p0])\n",
        "\n",
        "(u, p)=split(X0)\n",
        "(u_n, p_n)=split(Xn)\n",
        "(v, q)=split(B)\n",
        "\n",
        "# n = FacetNormal(mesh)\n",
        "\n",
        "F = nabla_div(u-u_n)*q*dx + dt*(k/(mu_l))*dot(grad(p), grad(q))*dx \n",
        "F += inner(sigma(u), epsilon(v))*dx  - p*nabla_div(v)*dx - dot(T,v)*ds(2)\n",
        "\n",
        "\n",
        "#solver tuning\n",
        "dX0 = TrialFunction(MS)\n",
        "J = derivative(F, X0, dX0)\n",
        "Problem = NonlinearVariationalProblem(F, X0, J = J, bcs = bc)\n",
        "Solver  = NonlinearVariationalSolver(Problem)\n",
        "Solver.parameters['newton_solver']['convergence_criterion'] = 'incremental'\n",
        "Solver.parameters['newton_solver']['relative_tolerance'] = 1.e-11\n",
        "Solver.parameters['newton_solver']['absolute_tolerance'] = 5.e-10\n",
        "\n",
        "#if you want to store the results\n",
        "#vtkfile_u = File('Sphere/u.pvd')\n",
        "#vtkfile_p = File('Sphere/p.pvd')\n",
        "\n",
        "t = 0\n",
        "\n",
        "p_out = []\n",
        "\n",
        "from tqdm import tqdm_notebook\n",
        "for n in tqdm_notebook(range(num_steps)):\n",
        "\tt += dt\n",
        "\tSolver.solve()    \n",
        "\tassign(Xn,X0)\n",
        "\n",
        "\t(_u,_p)=X0.split()\n",
        "\tp_out.append(_p(0, 0, 0))\n",
        "\t#vtkfile_u << (_u,t)\n",
        "\t#vtkfile_p << (_p,t)"
      ],
      "metadata": {
        "id": "pw-EBzjqQiha",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85,
          "referenced_widgets": [
            "107af0031cab4bf8b2f35951bbf3e14e",
            "f32ef66982e1480a828dc42ca29c875a",
            "6356aff35db74c0fa245258334cec34a",
            "2c5081706ccd4a75b4d7de76d889a056",
            "133abf7487d146d0b73958613e6e94ff",
            "a46c43130f54435082333ee068dd30f9",
            "d5feeb6598a94f2a890d6a1a2cc1c445",
            "9dad74387a514e8183f2604fc1c1594c",
            "f5f2e8d82ea24237a8f3aa91335bf1fb",
            "83dd97c3c9634b129eb23726dfc9f577",
            "ffb902df3892430fb644944e7b4638a3"
          ]
        },
        "outputId": "4c08f211-a302-4ad1-9af9-f54a60c388a4"
      },
      "id": "pw-EBzjqQiha",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:75: TqdmDeprecationWarning: This function will be removed in tqdm==5.0.0\n",
            "Please use `tqdm.notebook.tqdm` instead of `tqdm.tqdm_notebook`\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/100 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "107af0031cab4bf8b2f35951bbf3e14e"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "u_result, p_result = X0.split()\n",
        "import matplotlib.pyplot as plt\n",
        "c=plot(p_result)\n",
        "plt.colorbar(c)\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "G0dWBTs8TB3q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 254
        },
        "outputId": "6e062fda-6e10-4f2b-e001-19334b3c7c26"
      },
      "id": "G0dWBTs8TB3q",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Postprocess"
      ],
      "metadata": {
        "id": "bZFw87laa7Tp"
      },
      "id": "bZFw87laa7Tp"
    },
    {
      "cell_type": "code",
      "source": [
        "# Use the following method to zip the file.\n",
        "!zip -r 'Sphere.zip' '/content/Sphere' "
      ],
      "metadata": {
        "id": "joHFy9lSTN27",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "28ae2a9c-b760-4d0a-f277-580120ccf31e"
      },
      "id": "joHFy9lSTN27",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "updating: content/Sphere/ (stored 0%)\n",
            "updating: content/Sphere/u.pvd (deflated 29%)\n",
            "updating: content/Sphere/u000000.vtu (deflated 63%)\n",
            "updating: content/Sphere/p000000.vtu (deflated 64%)\n",
            "updating: content/Sphere/p.pvd (deflated 29%)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4(b)"
      ],
      "metadata": {
        "id": "rtxvdCroiuq_"
      },
      "id": "rtxvdCroiuq_"
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "time = np.linspace(0,1,100)\n",
        "pressure = np.array(p_out)\n",
        "plt.xlabel(r\"$t$\")\n",
        "plt.ylabel(r\"$p$\")\n",
        "plt.semilogx(100/9.8*1*time/4, pressure, 'k')"
      ],
      "metadata": {
        "id": "BgAwNRBDfINY",
        "outputId": "9e9b4f36-c209-4800-a222-ed60dc33f4ca",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 303
        }
      },
      "id": "BgAwNRBDfINY",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f40195af990>]"
            ]
          },
          "metadata": {},
          "execution_count": 69
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
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