{
 "cells": [
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   "source": [
    "# Elastodynamics\n",
    "***\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## General formulation of the problem\n",
    "\n",
    "---\n",
    "\n",
    "For a fixed time horizon $T>0$ let us denote\n",
    "\\begin{align*}\n",
    "    I:= [0,T],\n",
    "    &&\n",
    "    Q := I \\times \\Omega,\n",
    "    &&\n",
    "    \\Sigma := I \\times \\partial \\Omega,\n",
    "    &&\n",
    "    \\Sigma_D := I \\times \\partial \\Gamma_D,\n",
    "    &&\n",
    "    \\Sigma_N := I \\times \\partial \\Gamma_N,\n",
    "\\end{align*}\n",
    "where $\\Omega$ is a bounded spatial domain, $\\partial \\Omega$ is its boundary, and $\\Gamma_D$, $\\Gamma_N$ denote the part of boundary where Dirichlet and Neumann boundary condition is prescribed.\n",
    "\n",
    "Using this notation the evolution problem reads\n",
    "\\begin{align*}\n",
    "\t\\rho \\ddot{\\mathbf{u}} &= \\text{div} \\boldsymbol{\\sigma} + \\mathbf{b} && \\text{in } Q, \\\\\n",
    "\t\\sigma \\mathbf{n} &= \\mathbf{g} && \\text{on } \\Sigma_N, \\\\\n",
    "\t\\mathbf{u} &= \\mathbf{u}_D && \\text{on } \\Sigma_D, \\\\\n",
    "    \\mathbf{u}(0,\\cdot) &= \\mathbf{u}_0 && \\text{in } \\Omega, \\\\\n",
    "    \\dot{\\mathbf{u}}(0,\\cdot) &= \\mathbf{v}_0 && \\text{in } \\Omega, \\\\\n",
    "\\end{align*}\n",
    "where $\\dot{\\mathbf{u}}$, $\\ddot{\\mathbf{u}}$ denote\n",
    "the first and the second derivative of displacement with respect to time. The spatial fields $\\mathbf{u}_0$, $\\mathbf{v}_0$ denote the initial condition for displacement and velocity. The rest of the notation remains the same as earlier, i.e. $\\mathbf{b}$ is the volumetric force density, $\\mathbf{g}$ is the normal traction on the Neumann part of the boundary of $\\Omega$,\n",
    "and $\\mathbf{u}_D$ is the prescribed displacement at the Dirichlet part of $\\partial \\Omega$. The symbol $\\boldsymbol{\\sigma}$ denotes the stress tensor which is, for an isotropic material, given by\n",
    "\\begin{equation}\n",
    "    \\boldsymbol{\\sigma}=\\lambda\\mathrm{tr}(\\boldsymbol{\\varepsilon})\\mathbf{I} + 2\\mu\\boldsymbol{\\varepsilon}, \\end{equation}\n",
    "where the strain tensor $\\boldsymbol{\\varepsilon}$ takes the form\n",
    "\\begin{equation}\n",
    "    \\boldsymbol{\\varepsilon}=\\frac{1}{2}\\left(\\nabla\\mathbf{u}+ \\left( \\nabla\\mathbf{u} \\right)^{\\top} \\right),\n",
    "\\end{equation}\n",
    "while $\\lambda, \\mu$ are Lame's constants which can be expressed in terms of the Young's modulus $E$ and Poisson's ratio $\\nu$ as\n",
    "\\begin{equation}\n",
    "    \\lambda = \\frac{E \\nu}{(1 + \\nu) (1 - 2 \\nu)},\n",
    "    \\qquad\n",
    "    \\mu = \\frac{E}{2(1 + \\nu)}.\n",
    "\\end{equation}\n",
    "\n",
    "The weak formulation of our evolution problem reads: Find $\\mathbf{u}$ s.t. for almost all times $t \\in I$\n",
    "we have $\\mathbf{u}(t)-\\bar{\\mathbf{u}}(t) \\in \\mathbf{V}$ and\n",
    "\\begin{align*}\n",
    "    \\left\\langle \\sqrt{\\rho} \\ddot{\\mathbf{u}}, \\sqrt{\\rho} \\delta\\mathbf{u} \\right\\rangle_{\\mathbf{V}^*,\\mathbf{V}}\n",
    "    +\n",
    "    \\int_{\\Omega} \\boldsymbol{\\sigma} : \\delta \\boldsymbol{\\varepsilon} \\, \\mathrm{dV}\n",
    "    = \\int_{\\Omega} \\mathbf{b}\\cdot\\delta\\mathbf{u} \\, \\mathrm{dV}\n",
    "    + \\int_{\\Gamma_N}\\mathbf{g}\\cdot\\delta\\mathbf{u} \\, \\mathrm{dS},\n",
    "    \\qquad \\forall \\delta\\mathbf{u} \\in \\mathbf{V},\n",
    "\\end{align*}\n",
    "where $\\mathbf{V} = \\{ v \\in H^1(\\Omega)| v = 0\\ \\text{on}\\ \\Gamma_\\mathrm{D}\\}$\n",
    "and $\\left\\langle \\cdot, \\cdot \\right\\rangle_{\\mathbf{V}^*,\\mathbf{V}}$ denotes the duality.\n",
    "The initial conditions need to be imposed separately."
   ]
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   "metadata": {
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   "source": [
    "Why do we need the duality? It is acctually very natural, because the general strong form of the equation is $\\ddot{\\mathbf{u}} = - \\nabla E$, where $E$ is the energy. And since the derivative of $E$ lies in the co-tangent bundel (i.e. dual), so does the second derivative. In this example, $\\boldsymbol{\\sigma}$ is a priori only in $L^2$ and hence the derivative of energy is a functional that cannot be written as an itegral of some function multiplied by $\\delta \\mathbf{u}$. In other words, we cannot obtain better a priori estimates for $\\ddot{\\mathbf{u}}$. If we knew e.g. that $\\boldsymbol{\\sigma} \\in H(\\text{div};\\Omega)$, we would obtain, after integration by parts, that $\\rho \\ddot{\\mathbf{u}} = (\\text{div } \\boldsymbol{\\sigma} + \\mathbf{b}) \\in L^2$ and the duality would indeed become a simple integral."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time discretization and integration schemes\n",
    "\n",
    "---\n",
    "\n",
    "After discretizing in time, the weak formulation at a specific time instant $t_{i+1}$ reads: Find $\\mathbf{u}_{i+1}$ s.t.\n",
    "\\begin{equation}\n",
    "    \\int_{\\Omega} \\rho \\ddot{\\mathbf{u}}_{i+1} \\cdot \\delta\\mathbf{u} \\, \\mathrm{dV}\n",
    "    + \\int_\\Omega\\boldsymbol{\\sigma}_{i+1}:\\delta\\boldsymbol{\\varepsilon}\\ \\mathrm{dV}\n",
    "    = \\int_\\Omega \\mathbf{b}\\cdot\\delta\\mathbf{u}\\ \\mathrm{dV}\n",
    "    + \\int_{\\partial\\Omega}\\mathbf{g}\\cdot\\delta\\mathbf{u}\\ \\mathrm{dS},\n",
    "    \\quad \\forall \\delta\\mathbf{u}.\n",
    "\\end{equation}\n",
    "The time integration scheme depends on the type of discretization of the second derivative. Below, we introduce disretizations which lead to implicit and explicit integrators. However, in the implementation we shall treat the implicit integrator only. It is a simple exercise to modify the code to the case of an explicit integrator."
   ]
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   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "Note that in the above formula the duality was substituted by an integral. The reason why is that we approximate the second derivative by more regular functions for which the duality is given by an integral of their functional values solely, no derivatives are involved; c.f. the Gelfand triple."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Implicit integrator\n",
    "For constant acceleration Newmark method, velocity and displacement at time $t_{i+1}$ can be expressed in terms of the previous time instant $t_i$ as\n",
    "\\begin{equation}\n",
    "\\dot{\\mathbf{u}}_{i+1}=\\dot{\\mathbf{u}}_{i} + \\frac{\\Delta t}{2}(\\ddot{\\mathbf{u}}_{i} + \\ddot{\\mathbf{u}}_{i+1}),\n",
    "\\end{equation}\n",
    "\\begin{equation}\n",
    "\\mathbf{u}_{i+1} = \\mathbf{u}_{i} + \\Delta t\\dot{\\mathbf{u}}_{i} + \\frac{\\Delta t^2}{4}(\\ddot{\\mathbf{u}}_{i} + \\ddot{\\mathbf{u}}_{i+1}),\n",
    "\\end{equation}\n",
    "which can be rearranged to\n",
    "\\begin{equation}\n",
    "\\ddot{\\mathbf{u}}_{i+1} = \\frac{4}{\\Delta t^2}(\\mathbf{u}_{i+1} - \\tilde{\\mathbf{u}}_{i}),\n",
    "\\end{equation}\n",
    "where we introduced an auxiliary variable\n",
    "\\begin{equation}\n",
    "\\tilde{\\mathbf{u}}_{i} = \\mathbf{u}_{i} + \\Delta t\\dot{\\mathbf{u}}_{i} + \\frac{\\Delta t^2}{4}\\ddot{\\mathbf{u}}_{i}.\n",
    "\\end{equation}\n",
    "After substituting the expression for $\\ddot{\\mathbf{u}}_{i+1}$ into the weak form, we arrive at an equation for $\\mathbf{u}_{i+1}$\n",
    "\\begin{equation}\n",
    "    \\int_\\Omega\\rho\\left(\\frac{4}{\\Delta t^2}(\\mathbf{u}_{i+1} - \\tilde{\\mathbf{u}}_{i})\\right)\\cdot\\delta\\mathbf{u}\\,\\mathrm{dV}\n",
    "    + \\int_\\Omega\\boldsymbol{\\sigma}_{i+1}:\\delta\\boldsymbol{\\varepsilon}\\ \\mathrm{dV}\n",
    "    = \\int_\\Omega \\mathbf{b}\\cdot\\delta\\mathbf{u}\\ \\mathrm{dV}\n",
    "    + \\int_{\\partial\\Omega}\\mathbf{g}\\cdot\\delta\\mathbf{u}\\ \\mathrm{dS}\n",
    "    , \\quad \\forall \\delta\\mathbf{u},\n",
    "\\end{equation}\n",
    "where the value of the initial $\\mathbf{u}_0$ has to be such that the prescribed initial displacement and velocity are met."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Explicit integrator\n",
    "\n",
    "In the forward Euler method, acceleration at time $t_{i+1}$ is approximated by the forward finite difference as\n",
    "\\begin{equation}\n",
    "\\ddot{\\mathbf{u}}_{i+1}=\\frac{\\mathbf{u}_{i+2} - 2\\mathbf{u}_{i+1} + \\mathbf{u}_{i}}{\\Delta t^2}.\n",
    "\\end{equation}\n",
    "\n",
    "After substituting this expression into the weak form, we get an equation for $\\mathbf{u}_{i+2}$\n",
    "\\begin{equation}\n",
    "    \\int_\\Omega\\rho\\frac{\\mathbf{u}_{i+2} - 2\\mathbf{u}_{i+1} + \\mathbf{u}_{i}}{\\Delta t^2}\\cdot\\delta\\mathbf{u}\\,\\mathrm{dV} \n",
    "    +\n",
    "    \\int_\\Omega \\boldsymbol{\\sigma}_{i+1}:\\delta\\boldsymbol{\\varepsilon} \\, \\mathrm{dV} \n",
    "    =\n",
    "    \\int_\\Omega \\mathbf{b}\\cdot\\delta\\mathbf{u} \\, \\mathrm{dV} \n",
    "    +\n",
    "    \\int_{\\partial\\Omega}\\mathbf{g}\\cdot\\delta\\mathbf{u} \\, \\mathrm{dS} = 0, \n",
    "    \\quad \\forall \\delta\\mathbf{u},\n",
    "\\end{equation}\n",
    "where the values of the initial $\\mathbf{u}_0$, $\\mathbf{u}_1$ have to be such that the prescribed initial displacement and velocity are met."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementation\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We again import all neccessary packages and define auxiliary functions and parameters. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import fenics as fe\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import time\n",
    "\n",
    "# --------------------\n",
    "# Parameters\n",
    "# --------------------\n",
    "# Lame's constants\n",
    "lmbda = 1.25\n",
    "mu = 1.0\n",
    "# Density\n",
    "rho = 1.0\n",
    "\n",
    "# Geometry of the domain\n",
    "l_x, l_y, l_z = 1.0, 1.0, 0.1  # Domain dimensions\n",
    "# Discretization of the domain\n",
    "n_x, n_y, n_z = 100, 100, 2  # Number of elements\n",
    "\n",
    "# Load\n",
    "f_int = 1.0e-1\n",
    "\n",
    "\n",
    "# --------------------\n",
    "# Functions and classes\n",
    "# --------------------\n",
    "def bottom(x, on_boundary):\n",
    "    return (on_boundary and fe.near(x[1], 0.0))\n",
    "\n",
    "\n",
    "def indent_area(x, on_boundary):\n",
    "    return (on_boundary and fe.near(x[1], l_y) and abs(x[0] - 0.5*l_x) < 0.2*l_x)\n",
    "\n",
    "\n",
    "# Strain function\n",
    "def epsilon(u):\n",
    "    return 0.5*(fe.grad(u) + fe.grad(u).T)\n",
    "\n",
    "\n",
    "# Stress function\n",
    "def sigma(u):\n",
    "    return lmbda*fe.div(u)*fe.Identity(2) + 2*mu*epsilon(u)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We also define start time, end time and time step. There are many options how to construct a time loop, we do so by using NumPy's `linspace()` function which returns an array of equidistantly spaced numbers over a specified interval."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Time-stepping\n",
    "t_start = 0.0  # start time\n",
    "t_end = 1.0e-1  # end time\n",
    "t_steps = 100  # number of time steps\n",
    "\n",
    "t, dt = np.linspace(t_start, t_end, t_steps, retstep=True)\n",
    "dt = np.asscalar(dt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mesh geometry is imported from an external `.xml` file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# --------------------\n",
    "# Geometry\n",
    "# --------------------\n",
    "mesh = fe.Mesh(\"external_mesh.xml\")\n",
    "\n",
    "fe.plot(mesh)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we create a vector-valued function space and trial/test functions corresponding to this space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --------------------\n",
    "# Function spaces\n",
    "# --------------------\n",
    "V = fe.VectorFunctionSpace(mesh, \"CG\", 1)\n",
    "u_tr = fe.TrialFunction(V)\n",
    "u_test = fe.TestFunction(V)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Neumann boundary conditions are prescribed as previously. For a time-dependent Dirichlet boundary condition we can define new `DirichletBC` object for each time step and send it to the solver. A more elegant way is to use the FEniCS' object `Expression` which is a user-defined function written in the C/C++ syntax which can contain any number of free parameters. In our case we parametrize Dirichlet boundary function by a pseudo time $t$ which is constant in space (`degree=0`). The update of the expression is done via the command `u_D.t=...`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --------------------\n",
    "# Boundary conditions\n",
    "# --------------------\n",
    "u_D = fe.Expression(\" t < 1.0e-2 ? -100*t : -1.0\", t=0.0, degree=0)\n",
    "\n",
    "bc1 = fe.DirichletBC(V, fe.Constant((0.0, 0.0)), bottom)\n",
    "bc2 = fe.DirichletBC(V.sub(1), u_D, indent_area)\n",
    "bc = [bc1, bc2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can initialize all the functions we need. Here, `u_bar` represents $\\tilde{\\mathbf{u}}$, `du` is $\\dot{\\mathbf{u}}$ and `ddu` is $\\ddot{\\mathbf{u}}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --------------------\n",
    "# Initialization\n",
    "# --------------------\n",
    "u = fe.Function(V)\n",
    "u_bar = fe.Function(V)\n",
    "du = fe.Function(V)\n",
    "ddu = fe.Function(V)\n",
    "ddu_old = fe.Function(V)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To be able to save the results we set up an output `.xdmf` file which is suitable to work with in a dynamic regime."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "file = fe.XDMFFile(\"FEniCS_2a_output.xdmf\")\n",
    "file.parameters[\"flush_output\"] = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The parameter `flush_output` enables the user to preview the solution (e.g. in ParaView) during the process of long computations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we are in position to write down the weak formulation of our problem and solve it. The weak formulation for the constant acceleration Newmark method reads as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --------------------\n",
    "# Weak form\n",
    "# --------------------\n",
    "A_form = fe.inner(sigma(u_tr), epsilon(u_test))*fe.dx + 4*rho/(dt*dt)*fe.dot(u_tr - u_bar, u_test)*fe.dx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The problem is then solved using a `for` loop over time. As a first step we update the Dirichlet boundary condition `u_D` for the current time step `ti` and we assign the auxiliary variable `u_bar` a new value corresponding to the current time step `ti`. We then solve the algebraic problem in a standard fashion. The rest is just updating of the auxiliary variables `ddu_old`, `ddu` and `du`. Note that for the `.assign` method to work the input functions must be elements of the same function space as the function that's being assigned a new value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# --------------------\n",
    "# Time loop\n",
    "# --------------------\n",
    "for ti in t:\n",
    "    u_D.t = ti\n",
    "    u_bar.assign(u + dt*du + 0.25*dt*dt*ddu)\n",
    "    \n",
    "    #A, b = fe.assemble_system(fe.lhs(A_form), fe.rhs(A_form), bc)\n",
    "    #fe.solve(A, u.vector(), b, \"cg\", \"jacobi\")\n",
    "    fe.solve(fe.lhs(A_form) == fe.rhs(A_form), u, bc)\n",
    "    \n",
    "    ddu_old.assign(ddu)\n",
    "    ddu.assign(4/(dt*dt)*(u - u_bar))\n",
    "    du.assign(du + 0.5*dt*(ddu + ddu_old))\n",
    "\n",
    "    file.write(u, ti)\n",
    "    \n",
    "    #print(ti)\n",
    "file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The line `file.write(u, ti)` writes the computed displacement `u` at time `ti` to the output file. Remember to `.close()` the file when you are done with it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Complete code\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import fenics as fe\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import time\n",
    "\n",
    "\n",
    "# --------------------\n",
    "# Functions and classes\n",
    "# --------------------\n",
    "def bottom(x, on_boundary):\n",
    "    return (on_boundary and fe.near(x[1], 0.0))\n",
    "\n",
    "\n",
    "def indent_area(x, on_boundary):\n",
    "    return (on_boundary and fe.near(x[1], l_y) and abs(x[0] - 0.5*l_x) < 0.2*l_x)\n",
    "\n",
    "\n",
    "# Strain function\n",
    "def epsilon(u):\n",
    "    return 0.5*(fe.nabla_grad(u) + fe.nabla_grad(u).T)\n",
    "\n",
    "\n",
    "# Stress function\n",
    "def sigma(u):\n",
    "    return lmbda*fe.div(u)*fe.Identity(2) + 2*mu*epsilon(u)\n",
    "\n",
    "\n",
    "# --------------------\n",
    "# Parameters\n",
    "# --------------------\n",
    "# Young's modulus and Poisson's ratio\n",
    "E = 0.02e9\n",
    "nu = 0.1\n",
    "\n",
    "# Lame's constants\n",
    "lmbda = E*nu/(1+nu)/(1-2*nu)\n",
    "mu = E/2/(1+nu)\n",
    "rho = 200.0\n",
    "\n",
    "l_x, l_y = 5.0, 5.0  # Domain dimensions\n",
    "\n",
    "# Time-stepping\n",
    "t_start = 0.0  # start time\n",
    "t_end = 1.0e-1  # end time\n",
    "t_steps = 100  # number of time steps\n",
    "\n",
    "t, dt = np.linspace(t_start, t_end, t_steps, retstep=True)\n",
    "dt = float(dt)  # time step needs to be converted from class 'numpy.float64' to class 'float' for the .assign() method to work (see below) \n",
    "\n",
    "# --------------------\n",
    "# Geometry\n",
    "# --------------------\n",
    "mesh = fe.Mesh(\"external_mesh.xml\")\n",
    "\n",
    "fe.plot(mesh)\n",
    "plt.show()\n",
    "\n",
    "# --------------------\n",
    "# Function spaces\n",
    "# --------------------\n",
    "V = fe.VectorFunctionSpace(mesh, \"CG\", 1)\n",
    "u_tr = fe.TrialFunction(V)\n",
    "u_test = fe.TestFunction(V)\n",
    "\n",
    "# --------------------\n",
    "# Boundary conditions\n",
    "# --------------------\n",
    "u_D = fe.Expression(\" t < 1.0e-2 ? -100*t : -1.0\", t=0.0, degree=0)\n",
    "\n",
    "bc1 = fe.DirichletBC(V, fe.Constant((0.0, 0.0)), bottom)\n",
    "bc2 = fe.DirichletBC(V.sub(1), u_D, indent_area)\n",
    "bc = [bc1, bc2]\n",
    "\n",
    "# --------------------\n",
    "# Initialization\n",
    "# --------------------\n",
    "u = fe.Function(V)\n",
    "u_bar = fe.Function(V)\n",
    "du = fe.Function(V)\n",
    "ddu = fe.Function(V)\n",
    "ddu_old = fe.Function(V)\n",
    "\n",
    "file = fe.XDMFFile(\"FEniCS_explicit_output.xdmf\")  # XDMF file\n",
    "\n",
    "# --------------------\n",
    "# Weak form\n",
    "# --------------------\n",
    "A_form = fe.inner(sigma(u_tr), epsilon(u_test))*fe.dx + 4*rho/(dt*dt)*fe.dot(u_tr - u_bar, u_test)*fe.dx\n",
    "\n",
    "# --------------------\n",
    "# Time loop\n",
    "# --------------------\n",
    "for ti in t:\n",
    "    u_D.t = ti\n",
    "    u_bar.assign(u + dt*du + 0.25*dt*dt*ddu)\n",
    "    \n",
    "    #A, b = fe.assemble_system(fe.lhs(A_form), fe.rhs(A_form), bc)\n",
    "    #fe.solve(A, u.vector(), b, \"cg\", \"jacobi\")\n",
    "    fe.solve(fe.lhs(A_form) == fe.rhs(A_form), u, bc)\n",
    "    \n",
    "    ddu_old.assign(ddu)\n",
    "    ddu.assign(4/(dt*dt)*(u - u_bar))\n",
    "    du.assign(du + 0.5*dt*(ddu + ddu_old))\n",
    "\n",
    "    file.write(u, ti)\n",
    "    \n",
    "    #print(ti)\n",
    "file.close()"
   ]
  }
 ],
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