|
|
- {
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "#1 Loading functions and modules\n",
- "from fenics import *\n",
- "import matplotlib.pyplot as plt\n",
- "T = 2.0\n",
- "num_steps = 20\n",
- "dt = T/num_steps\n",
- "rho = 7500\n",
- "Cp = 500\n",
- "k = 50\n",
- "alpha = k/(rho*Cp)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": "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
- "text/plain": [
- "<Figure size 432x288 with 1 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "#2 Create mesh and define function space\n",
- "nx = 0.008\n",
- "ny = 0.003\n",
- "mesh = RectangleMesh(Point(0,0),Point(nx,ny),30, 30,'left')\n",
- "V = FunctionSpace(mesh, 'Lagrange', 1) #Lagrange are triangular elements\n",
- "plot(mesh)\n",
- "plt.show()\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "# Boundary conditions\n",
- "u0 = Constant(100)\n",
- "def boundary(x, on_boundary):\n",
- " return on_boundary\n",
- "\n",
- "bc = DirichletBC(V,u0, boundary)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
- ]
- }
- ],
- "source": [
- "u_n = project(1, V)\n",
- "u = TrialFunction(V)\n",
- "v = TestFunction(V)\n",
- "f = Constant(0.0)\n",
- "F = u*v*dx + alpha*dt*dot(grad(u), grad(v))*dx-u_n*v*dx\n",
- "a, L = lhs(F), rhs(F)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Calling FFC just-in-time (JIT) compiler, this may take some time.\n"
- ]
- },
- {
- "data": {
- "image/png": "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
- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- },
- {
- "data": {
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "output_type": "display_data"
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "<Figure size 432x288 with 2 Axes>"
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- "<Figure size 432x288 with 2 Axes>"
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
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- "metadata": {
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- "<Figure size 432x288 with 2 Axes>"
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
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- "text/plain": [
- "<Figure size 432x288 with 2 Axes>"
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "u = Function(V)\n",
- "t = 0\n",
- "for n in range(num_steps):\n",
- " t += dt\n",
- " #u0.t = t\n",
- " solve(a == L, u, bc)\n",
- " c = plot(u,)\n",
- " plt.colorbar(c)\n",
- " plt.show()\n",
- " u_n.assign(u)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "1e-07"
- ]
- },
- "execution_count": 10,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "1E-7"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "100.0"
- ]
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "1e2"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "100.0000001"
- ]
- },
- "execution_count": 11,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "1E-7+1e2"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "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": "3.6.7"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
- }
|