{ "cells": [ { "cell_type": "markdown", "id": "3ac3d68b", "metadata": {}, "source": [ "## An introductory demonstration of PyFVTool" ] }, { "cell_type": "markdown", "id": "3cdf0aad-6303-482e-8984-740b9fd19255", "metadata": {}, "source": [ "The general form of the partial differential equations solved in PyFVTool is \n", " $$ \\alpha \\frac{\\partial \\varphi}{\\partial t} + \\nabla\\cdot\\left(\\vec{u}\\varphi\\right) + \\nabla\\cdot\\left(-D\\nabla\\varphi\\right) + \\beta \\varphi = \\gamma $$\n", "\n", "with general boundary conditions\n", " $$ a\\nabla\\varphi\\cdot \\vec{e} + b\\varphi = c $$.\n" ] }, { "cell_type": "markdown", "id": "d5219045-4998-478f-8113-ff28514e5c92", "metadata": {}, "source": [ "PyFVTool works in a standard scientific Python environment, so make NumPy and Matplotlib available. " ] }, { "cell_type": "code", "execution_count": 1, "id": "ee81e01d", "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "id": "b14239d3-3dbf-4603-aaa3-907dc46b91a9", "metadata": {}, "outputs": [], "source": [ "# import the error function from scipy\n", "from scipy.special import erf" ] }, { "cell_type": "markdown", "id": "a125a021-5fb9-4e3e-9a1c-7a2e9a8aeffc", "metadata": {}, "source": [ "The recommended way of importing PyFVTool is to use `pf` as the shortcut." ] }, { "cell_type": "code", "execution_count": 3, "id": "2e07005d", "metadata": {}, "outputs": [], "source": [ "import pyfvtool as pf" ] }, { "cell_type": "markdown", "id": "9d3ace33", "metadata": {}, "source": [ "### Create a 1D mesh and visualize it" ] }, { "cell_type": "markdown", "id": "e932e6ce-1fef-40e7-bdc6-745b5926eef1", "metadata": {}, "source": [ "The simplest mesh is the Cartesian 1D grid, an example of which will be created here.\n", "\n", "The mesh-structure object is created via the `Grid1D` class." ] }, { "cell_type": "code", "execution_count": 4, "id": "2a6cb98e", "metadata": {}, "outputs": [], "source": [ "L = 1.0 # length of the domain\n", "Nx = 10 # number of cells in the domain" ] }, { "cell_type": "code", "execution_count": 5, "id": "f81d1e37", "metadata": {}, "outputs": [], "source": [ "m = pf.Grid1D(Nx, L) # mesh-structure" ] }, { "cell_type": "markdown", "id": "3bf37774-a3ca-451a-a25f-062c4e8e2dac", "metadata": {}, "source": [ "We can have a look at the structure of the mesh that was created.\n", "\n", "The `_x`, `_y`, `_z` are the coordinate labels used internally by PyFVTool. These are not intended to be used directly by the user.\n", "\n", "The coordinate labels for the user are given in the `coordlabels` dictionary. In this particular `Grid1D` case, the user `x` label maps to the internal `_x` label. The other coordinates are not used, as the mesh is one-dimensional." ] }, { "cell_type": "code", "execution_count": 6, "id": "303024df-a057-4fd7-afe1-68d799e98d8d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dims: [10]\n", "cellsize: _x: [0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]\n", "_y: [0.]\n", "_z: [0.]\n", "coordlabels: {'x': '_x'}\n", "\n", "cellcenters: _x: [0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95]\n", "_y: [0.]\n", "_z: [0.]\n", "coordlabels: {'x': '_x'}\n", "\n", "facecenters: _x: [0. 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1. ]\n", "_y: [0.]\n", "_z: [0.]\n", "coordlabels: {'x': '_x'}\n", "\n", "corners: [1]\n", "edges: [1]\n", "\n" ] } ], "source": [ "print(m)" ] }, { "cell_type": "markdown", "id": "52a91719-0094-47dc-94a6-2fffa8629fe3", "metadata": {}, "source": [ "1D meshes can be created in two ways because the function is overloaded, as shown in the help docstring." ] }, { "cell_type": "code", "execution_count": 7, "id": "c2f86bcf", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Help on class Grid1D in module pyfvtool.mesh:\n", "\n", "class Grid1D(MeshStructure)\n", " | Grid1D(*args)\n", " |\n", " | Mesh based on a 1D Cartesian grid (x)\n", " | =====================================\n", " |\n", " | This class can be instantiated in different ways: from a list of cell face\n", " | locations or from the number of cells and domain length.\n", " |\n", " | Instantiation Options:\n", " | ----------------------\n", " | - Grid1D(Nx, Lx)\n", " | - Grid1D(face_locationsX)\n", " |\n", " |\n", " | Parameters\n", " | ----------\n", " | Grid1D(Nx, Lx)\n", " | Nx : int\n", " | Number of cells in the x direction.\n", " | Lx : float\n", " | Length of the domain in the x direction.\n", " |\n", " | Grid1D(face_locationsX)\n", " | face_locationsX : ndarray\n", " | Locations of the cell faces in the x direction.\n", " |\n", " | Examples\n", " | --------\n", " | >>> import numpy as np\n", " | >>> from pyfvtool import Grid1D\n", " | >>> mesh = Grid1D(10, 10.0)\n", " | >>> print(mesh)\n", " |\n", " | Method resolution order:\n", " | Grid1D\n", " | MeshStructure\n", " | builtins.object\n", " |\n", " | Methods defined here:\n", " |\n", " | __init__(self, *args)\n", " | Initialize self. See help(type(self)) for accurate signature.\n", " |\n", " | __repr__(self)\n", " | Return repr(self).\n", " |\n", " | cell_numbers(self)\n", " |\n", " | ----------------------------------------------------------------------\n", " | Methods inherited from MeshStructure:\n", " |\n", " | __str__(self)\n", " | Return str(self).\n", " |\n", " | ----------------------------------------------------------------------\n", " | Readonly properties inherited from MeshStructure:\n", " |\n", " | cellvolume\n", " |\n", " | ----------------------------------------------------------------------\n", " | Data descriptors inherited from MeshStructure:\n", " |\n", " | __dict__\n", " | dictionary for instance variables\n", " |\n", " | __weakref__\n", " | list of weak references to the object\n", "\n" ] } ], "source": [ "help(pf.Grid1D)" ] }, { "cell_type": "code", "execution_count": 8, "id": "caa4c0f5", "metadata": {}, "outputs": [], "source": [ "# 1D, 2D, 3D, 1D radial (axial symmetry), and 2D cylindrical grids can be constructed: \n", "# help(pf.Grid1D)\n", "# help(pf.Grid2D)\n", "# help(pf.Grid3D)\n", "# help(pf.CylindricalGrid1D)\n", "# help(pf.CylindricalGrid2D)" ] }, { "cell_type": "code", "execution_count": 9, "id": "a00da477", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Visualize the 1D discretization that we created above\n", "hfig, ax = plt.subplots(1,1, num='Grid discretization')\n", "ax.plot(m.cellcenters.x, np.ones(np.shape(m.cellcenters.x), dtype=float), 'or', label='cell centers')\n", "ax.plot(m.facecenters.x, np.ones(np.shape(m.facecenters.x), dtype=float), '-+b', label='face centers')\n", "plt.legend(fontsize=12, loc='best')\n", "ax.set_title('Visualization of a 1D discretized domain');" ] }, { "cell_type": "markdown", "id": "350aeeca-5319-4052-8c2a-06f660b8385d", "metadata": {}, "source": [ "### Create a 2D grid and visualize it" ] }, { "cell_type": "code", "execution_count": 10, "id": "dbed1d79", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "Nx, Ny = 5, 7\n", "Lx, Ly = 10.0, 20.0\n", "m = pf.Grid2D(Nx, Ny, Lx, Ly)\n", "\n", "X, Y = np.meshgrid(m.cellcenters.x, m.cellcenters.y, indexing='ij')\n", "Xf, Yf = np.meshgrid(m.facecenters.x, m.facecenters.y, indexing='ij')\n", "\n", "plt.figure()\n", "plt.plot(X, Y, 'or', label='nodes')\n", "plt.plot(Xf, Yf, 'b-', label='faces (west/east)')\n", "plt.plot(Xf.T, Yf.T, 'b-', label='faces (north/south)');" ] }, { "cell_type": "markdown", "id": "c3b7ae01-f1cc-4df0-9b0d-0ba9e4365646", "metadata": {}, "source": [ "### Create a 3D grid and visualize it" ] }, { "cell_type": "code", "execution_count": 11, "id": "09786667", "metadata": {}, "outputs": [], "source": [ "Nx, Ny, Nz = 2, 3, 4\n", "Lx, Ly, Lz = 1.0, 2.0, 3.0\n", "\n", "m = pf.Grid3D(Nx, Ny, Nz, Lx, Ly, Lz)" ] }, { "cell_type": "markdown", "id": "965b740b-9a3d-4545-9431-45fd146b506e", "metadata": {}, "source": [ "We can obtain information of the positions of the cell centers.\n", "\n", "As can be seen, the user coordinate labels `x`, `y` and `z` map internally to `_x`, `_y`, `_z`. The correspondence is trivial in this case, but this is not so in the case of cylindrical or spherical coordinates." ] }, { "cell_type": "code", "execution_count": 12, "id": "f4c714e3-22ce-4b6d-9056-3b1ab09a5c66", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "_x: [0.25 0.75]\n", "_y: [0.33333333 1. 1.66666667]\n", "_z: [0.375 1.125 1.875 2.625]\n", "coordlabels: {'x': '_x', 'y': '_y', 'z': '_z'}" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "m.cellcenters" ] }, { "cell_type": "markdown", "id": "bd408fed-d44e-4d59-8d4f-545419a2b6cb", "metadata": {}, "source": [ "The (compact) information on the cell centers can be converted into a full grid in the following way." ] }, { "cell_type": "code", "execution_count": 13, "id": "e1c36e74-ced4-4071-92f8-35b395210c93", "metadata": {}, "outputs": [], "source": [ "X, Y, Z = np.meshgrid(m.cellcenters.x,\n", " m.cellcenters.y,\n", " m.cellcenters.z,\n", " indexing='ij')\n", "Xf, Yf, Zf = np.meshgrid(m.facecenters.x,\n", " m.facecenters.y,\n", " m.facecenters.z, \n", " indexing='ij')" ] }, { "cell_type": "code", "execution_count": 14, "id": "3e771f2e", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot the 3D grid\n", "\n", "# TO DO: make this interactive! this will require ipywidgets\n", "# This can probably only be done once these Notebooks are not used as pytest tests anymore.\n", "# The Notebooks used for tests should be converted to simple test scripts, and the Notebooks\n", "# can then simply be used as examples.\n", "\n", "hfig = plt.figure()\n", "ax = plt.axes(projection='3d')\n", "\n", "ax.plot3D(X.flatten(), Y.flatten(), Z.flatten(), 'ro', label='cell centers')\n", "ax.plot3D(Xf.flatten(), Yf.flatten(), Zf.flatten(), 'b+', label='cell corners')\n", "ax.legend(fontsize=12, loc='best');" ] }, { "cell_type": "markdown", "id": "73495793", "metadata": {}, "source": [ "### Boundary conditions" ] }, { "cell_type": "markdown", "id": "15a46690", "metadata": {}, "source": [ "One of the most important features of PyFVTool is the ability to implement different boundary conditions (BCs) for variables in the most convenient way. \n", "\n", "The implementation of BCs in PyFVTool enables the user to define either a periodic boundary condition or a general boundary condition of the following form:\n", "\n", "$$a (\\nabla \\phi .\\mathbf{n}) + b \\phi = c $$\n", "\n", "In the above equation, $\\phi$ is the unknown, and $a$, $b$, and $c$ are constants. In practice, this boundary condition equation will be discretized to the following system of algebraic equations:\n", "\n", "$$M_{bc} \\phi = {RHS}_{bc}$$\n", "\n", "By adjusting the values of $a$, $b$ and $c$, one of the following well-known types of boundary conditions can easily be defined:\n", "\n", " - Neumann ($a$ is nonzero; $b$ is 0)\n", " - Dirichlet ($a$ is zero; $b$ is nonzero)\n", " - Robin ($a$ and $b$ are both nonzero)" ] }, { "cell_type": "markdown", "id": "ec14b1b8-231c-4323-8d32-23ff4ed4ebf2", "metadata": {}, "source": [ "First, let's create a simple mesh again." ] }, { "cell_type": "code", "execution_count": 15, "id": "cb5b41fd-3ff1-49ce-9595-28369128de21", "metadata": {}, "outputs": [], "source": [ "Nx = 10 # number of cells in the domain\n", "Lx = 1.0 # length of the domain\n", "m = pf.Grid1D(Nx, Lx) # createMesh and createMesh are identical" ] }, { "cell_type": "markdown", "id": "49f7abbc-14b0-4f57-84f2-5593cb326083", "metadata": {}, "source": [ "Then, on this mesh, we will define a solution variable, via the `CellVariable` class. We will initialize its value to be 0.0 everywhere." ] }, { "cell_type": "code", "execution_count": 16, "id": "713bdff0-c41f-4ab1-9497-cb1ae9217d4e", "metadata": {}, "outputs": [], "source": [ "phi = pf.CellVariable(m, 0.0)" ] }, { "cell_type": "markdown", "id": "ab481003-b592-4d0a-897a-a378f36d56f4", "metadata": {}, "source": [ "The `CellVariable` object carries with it boundary conditions, that have been created by default. These boundary conditions will be applied by PyFVTool where required.\n", "\n", "Let's have a look at the BC structure.\n", "\n", "This also prints info on the mesh, which may be a bit confusing." ] }, { "cell_type": "code", "execution_count": 17, "id": "e8cd6f72", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "domain : dims: [10]\n", "cellsize: _x: [0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1]\n", "_y: [0.]\n", "_z: [0.]\n", "coordlabels: {'x': '_x'}\n", "\n", "cellcenters: _x: [0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95]\n", "_y: [0.]\n", "_z: [0.]\n", "coordlabels: {'x': '_x'}\n", "\n", "facecenters: _x: [0. 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1. ]\n", "_y: [0.]\n", "_z: [0.]\n", "coordlabels: {'x': '_x'}\n", "\n", "corners: [1]\n", "edges: [1]\n", "\n", "left : _a : [1.]\n", "_b : [0.]\n", "_c : [0.]\n", "_periodic : False\n", "\n", "right : _a : [1.]\n", "_b : [0.]\n", "_c : [0.]\n", "_periodic : False\n", "\n", "bottom : _a : []\n", "_b : []\n", "_c : []\n", "_periodic : False\n", "\n", "top : _a : []\n", "_b : []\n", "_c : []\n", "_periodic : False\n", "\n", "back : _a : []\n", "_b : []\n", "_c : []\n", "_periodic : False\n", "\n", "front : _a : []\n", "_b : []\n", "_c : []\n", "_periodic : False\n", "\n", "\n" ] } ], "source": [ "print(phi.BCs) # display the BC structure" ] }, { "cell_type": "markdown", "id": "57b04d60-f337-4d7d-8ece-79c509de1725", "metadata": {}, "source": [ "For simplicity, display only information for the left boundary, and then only information for the right boundary." ] }, { "cell_type": "code", "execution_count": 18, "id": "5d9f18ff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Left BC\n", "_a : [1.]\n", "_b : [0.]\n", "_c : [0.]\n", "_periodic : False\n", "\n", "\n", "Right BC\n", "_a : [1.]\n", "_b : [0.]\n", "_c : [0.]\n", "_periodic : False\n", "\n" ] } ], "source": [ "print(\"Left BC\")\n", "print(phi.BCs.left) # a non-zero, b and c == 0, --> homogeneous Neumann BC at left boundary\n", "print()\n", "print(\"Right BC\")\n", "print(phi.BCs.right) # same as left boundary --> homogeneous Neumann BC at right-boundary" ] }, { "cell_type": "markdown", "id": "6ed652a6-fb87-4149-86ba-ac1903ca5318", "metadata": {}, "source": [ "Both the left and right BCs have the same values for $a$, $b$ and $c$. These are the default BCs that are created: Neumann-style BCs with a zero value of the derivative at the boundary. Such BCs are also called \"zero flux boundary conditions\"." ] }, { "cell_type": "markdown", "id": "86860abb-ce32-4ec5-89cd-a5853def28dd", "metadata": {}, "source": [ "Boundary conditions can be adapted \"on the fly\"." ] }, { "cell_type": "code", "execution_count": 19, "id": "7b7e4e20-5c60-4211-b411-005898a5d11a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "_a : [0.]\n", "_b : [1.]\n", "_c : [0.]\n", "_periodic : True\n", "\n" ] } ], "source": [ "phi.BCs.left.a = 0.0\n", "phi.BCs.left.b = 1.0 # homogeneous Dirichlet boundary condition\n", "phi.BCs.left.c = 0.0 \n", "\n", "# Periodic boundary conditions override the other settings (take precedence)\n", "phi.BCs.left.periodic = True\n", "\n", "print(phi.BCs.left)" ] }, { "cell_type": "markdown", "id": "42a7ce37", "metadata": {}, "source": [ "For boundary condition structures created for 2D and 3D grids, we will have left, right, bottom, top, back, and front boundaries and thus substructures. Let me show them to you in action:" ] }, { "cell_type": "code", "execution_count": 20, "id": "4b6bb4c1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "domain : dims: [3 4]\n", "cellsize: _x: [0.33333333 0.33333333 0.33333333 0.33333333 0.33333333]\n", "_y: [0.5 0.5 0.5 0.5 0.5 0.5]\n", "_z: [0.]\n", "coordlabels: {'x': '_x', 'y': '_y'}\n", "\n", "cellcenters: _x: [0.16666667 0.5 0.83333333]\n", "_y: [0.25 0.75 1.25 1.75]\n", "_z: [0.]\n", "coordlabels: {'x': '_x', 'y': '_y'}\n", "\n", "facecenters: _x: [0. 0.33333333 0.66666667 1. ]\n", "_y: [0. 0.5 1. 1.5 2. ]\n", "_z: [0.]\n", "coordlabels: {'x': '_x', 'y': '_y'}\n", "\n", "corners: [ 0 24 5 29]\n", "edges: [1]\n", "\n", "left : _a : [1. 1. 1. 1.]\n", "_b : [0. 0. 0. 0.]\n", "_c : [[0. 0. 0. 0.]]\n", "_periodic : False\n", "\n", "right : _a : [1. 1. 1. 1.]\n", "_b : [0. 0. 0. 0.]\n", "_c : [0. 0. 0. 0.]\n", "_periodic : False\n", "\n", "bottom : _a : [1. 1. 1.]\n", "_b : [0. 0. 0.]\n", "_c : [0. 0. 0.]\n", "_periodic : False\n", "\n", "top : _a : [1. 1. 1.]\n", "_b : [0. 0. 0.]\n", "_c : [0. 0. 0.]\n", "_periodic : False\n", "\n", "back : _a : []\n", "_b : []\n", "_c : []\n", "_periodic : False\n", "\n", "front : _a : []\n", "_b : []\n", "_c : []\n", "_periodic : False\n", "\n", "\n" ] } ], "source": [ "m = pf.Grid2D(3, 4, 1.0, 2.0) # Nx, Ny, Lx, Ly\n", "\n", "phi = pf.CellVariable(m, 0.0)\n", "\n", "print(phi.BCs)" ] }, { "cell_type": "code", "execution_count": 21, "id": "a8324023-7b2e-45de-8b48-6d499d5aa6ec", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "_a : [1. 1. 1.]\n", "_b : [0. 0. 0.]\n", "_c : [0. 0. 0.]\n", "_periodic : False\n", "\n" ] } ], "source": [ "print(phi.BCs.top)" ] }, { "cell_type": "markdown", "id": "de3f0876", "metadata": {}, "source": [ "Yes, that's right. a, b, and c are vectors. It means that you can have different boundary conditions for different cell faces at each boundary. For instance, I can have a Neumann boundary condition for the first cell and a Dirichlet boundary condition for the last cell at the top boundary:\n" ] }, { "cell_type": "code", "execution_count": 22, "id": "e80812de", "metadata": {}, "outputs": [], "source": [ "# homogeneous Neumann\n", "phi.BCs.top.a[0] = 1.0\n", "phi.BCs.top.b[0] = 0.0\n", "phi.BCs.top.c[0] = 0.0\n", "\n", "# homogeneous Dirichlet\n", "phi.BCs.top.a[-1] = 0.0\n", "phi.BCs.top.b[-1] = 1.0\n", "phi.BCs.top.c[-1] = 0.0\n" ] }, { "cell_type": "code", "execution_count": 23, "id": "77350ce4-35c5-4721-b342-f3edc864251b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " a b c (top)\n", "---------------\n", "[[1. 0. 0.]\n", " [1. 0. 0.]\n", " [0. 1. 0.]]\n" ] } ], "source": [ "# Some fancy display!\n", "print(' a b c (top)')\n", "print('---------------')\n", "print(np.hstack((np.atleast_2d(phi.BCs.top.a).T, \n", " np.atleast_2d(phi.BCs.top.b).T,\n", " np.atleast_2d(phi.BCs.top.c).T)))\n", "\n", "# top. a b c\n", "# ---------------\n", "# 1 0 0\n", "# 1 0 0\n", "# 0 1 0" ] }, { "cell_type": "markdown", "id": "ef99e2e6", "metadata": {}, "source": [ "The same procedure can be followed for a 3D grid. However, $a$, $b$, and $c$ values are 2D matrices for a 3D grid. This will be discussed in more details when we reach the practical examples. \n", "\n" ] }, { "cell_type": "code", "execution_count": 24, "id": "ce32e0c2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " a b c (right)\n", "---------------\n", "[[0. 1. 0.]\n", " [0. 1. 0.]\n", " [0. 1. 0.]\n", " [0. 1. 0.]]\n" ] } ], "source": [ "phi.BCs.right.a = 0.0\n", "phi.BCs.right.b = 1.0\n", "phi.BCs.right.c = 0.0\n", "\n", "print(' a b c (right)')\n", "print('---------------')\n", "print(np.hstack((np.atleast_2d(phi.BCs.right.a).T,\n", " np.atleast_2d(phi.BCs.right.b).T,\n", " np.atleast_2d(phi.BCs.right.c).T)))" ] }, { "cell_type": "markdown", "id": "fb3c7042", "metadata": {}, "source": [ "### Solve a diffusion equation" ] }, { "cell_type": "markdown", "id": "fd40c4b6", "metadata": {}, "source": [ "As the first example, we solve a steady-state diffusion equation of the following form\n", "\n", "$$\\nabla\\cdot\\left(-D\\nabla c\\right)=0$$\n", "\n", "where $D$ is the diffusivity and $c$ is the concentration. Let me assume that we have a 1D domain, with Dirichlet boundary conditions at both boundaries, i.e., at $x$=0, $c$=1; and at $x$=$L$, $c$=0. First of all, we need to define our domain, discretize it, and define the boundaries at the borders.\n", "\n", "*Note:* This is a boundary value problem and we will be solving for the steady-state solution, without any transient term." ] }, { "cell_type": "markdown", "id": "dc5d2af7-bf15-4e23-8044-f95729340cf1", "metadata": {}, "source": [ "First create a 1D Cartesian grid and a solution variable called `c`." ] }, { "cell_type": "code", "execution_count": 25, "id": "717f65cb", "metadata": {}, "outputs": [], "source": [ "L = 0.01 # a 1 cm domain\n", "Nx = 10 # number of cells\n", "m = pf.Grid1D(Nx, L) \n", "\n", "c = pf.CellVariable(m, 0.0)" ] }, { "cell_type": "markdown", "id": "4e3a6234-0a7f-4b96-8037-729c9aa73a0d", "metadata": {}, "source": [ "Now switch from the default 'no flux' boundary conditions to Dirichlet conditions, on both sides of the domain.\n" ] }, { "cell_type": "code", "execution_count": 26, "id": "1007260d-1c6c-4b3d-8e7d-202eb853cc36", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "_a : [0.]\n", "_b : [1.]\n", "_c : [0.]\n", "_periodic : False\n", "\n", "_a : [0.]\n", "_b : [1.]\n", "_c : [1.]\n", "_periodic : False\n", "\n" ] } ], "source": [ "# left boundary \n", "c.BCs.left.a = 0.0\n", "c.BCs.left.b = 1.0\n", "c.BCs.left.c = 0.0\n", "\n", "# right boundary\n", "c.BCs.right.a = 0.0\n", "c.BCs.right.b = 1.0\n", "c.BCs.right.c = 1.0 \n", "\n", "print(c.BCs.left)\n", "print(c.BCs.right)" ] }, { "cell_type": "markdown", "id": "6db759e2", "metadata": {}, "source": [ "The next step is to define the diffusion coefficient. In this FVTool, the physical properties of the domain are defined for each cell, again as a `CellVariable` object.\n", "\n", "*Remark.* This variable is not a solution variable, and even though the `CellVariable` will internally contain a default `BCs` structure, these 'dummy' boundary conditions will of course not be used, are of no consequence and can be forgotten." ] }, { "cell_type": "code", "execution_count": 27, "id": "61e6ba07", "metadata": {}, "outputs": [], "source": [ "D = pf.CellVariable(m, 1e-5) # assign a constant value of 1e-5 to diffusivity value on each cell" ] }, { "cell_type": "markdown", "id": "2550225c", "metadata": {}, "source": [ "However, the diffusion coefficients must be known on the *face* of each cell. \n", "\n", "To obtain the values at the faces from the values at the centers, we have a few typical FVM averaging schemes at our disposal. For a 1D domain, we can use a harmonic mean scheme.\n", "\n", "Notes:\n", " - this \"averaging\" is actually an interpolation. It takes the nearest neighbor harmonic mean\n", " - the harmonic mean skews towards outliers with small values" ] }, { "cell_type": "code", "execution_count": 28, "id": "f781954c", "metadata": {}, "outputs": [], "source": [ "D_face = pf.harmonicMean(D) # average diffusivity value on the cell faces." ] }, { "cell_type": "markdown", "id": "553c4774", "metadata": {}, "source": [ "Now, we can convert the PDE to a, algebraic system of linear equations, i.e. a matrix equation to be solved.\n", "\n", "$$\\nabla\\cdot\\left(-D\\nabla c\\right) \\rightarrow \\mathbf{M}\\mathbf{c} = \\textrm{rhs}$$\n", "\n", "$\\mathbf{M}$ is the matrix of coefficients that is going to be constructed by PyFVTool, on basis of the finite-volume formulation. In this manner, PyFVTool will also construct the vector $\\textrm{rhs}$ which is commonly called the right-hand side.\n", "\n", "$\\mathbf{M}$ and $\\textrm{rhs}$ will be constructed from the definition of the solution variable, in particular its boundary conditions, and (in this case) from the diffusion term. The latter will be placed in a list of equation terms that will be supplied to the solver function `solvePDE()`. If you look at it in detail, `pf.diffusionTerm()` creates a matrix that will be added to the overall matrix $\\mathbf{M}$ for the matrix equation. This provides a mechanism for adding several different terms (diffusion, advection/convection, source/reaction) to the equation.\n", "\n", "`solvePDE()` will take care of constructing the matrix equation, and then calling the numerical (sparse matrix) solver.\n", "\n", "The vector $\\mathbf{c}$ will contain the finite-volume cell values of the concentration as the numerical solution of the matrix equation." ] }, { "cell_type": "code", "execution_count": 29, "id": "605cd76b-f313-4ba3-9e0f-37a8096e84a9", "metadata": {}, "outputs": [], "source": [ "eqnterms = [-pf.diffusionTerm(D_face)]" ] }, { "cell_type": "code", "execution_count": 30, "id": "4033ce24", "metadata": {}, "outputs": [], "source": [ "pf.solvePDE(c, eqnterms);" ] }, { "cell_type": "code", "execution_count": 31, "id": "31d50e92", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# visualize the solution\n", "plt.figure()\n", "pf.visualizeCells(c)" ] }, { "cell_type": "markdown", "id": "30919e8e", "metadata": {}, "source": [ "Just to get excited a little bit, only change the mesh definition command from `Grid1D(Nx,L)` to `Grid2D(Nx,Nx,L,L)`, run the code and see what happens." ] }, { "cell_type": "code", "execution_count": 32, "id": "d6b90a73", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 2D\n", "L = 0.01 # a 1 cm domain\n", "Nx = 10 # number of cells\n", "m = pf.Grid2D(Nx, Nx, L, L)\n", "c = pf.CellVariable(m, 0.0)\n", "\n", "# Now switch from Neumann boundary conditions to Dirichlet conditions:\n", "# left boundary: homogeneous Dirichlet left-side \n", "c.BCs.left.a, c.BCs.left.b, c.BCs.left.c = 0.0, 1.0, 0.0\n", "# right boundary: inhomogeneous Dirchlet right-side\n", "c.BCs.right.a, c.BCs.right.b, c.BCs.right.c = 0.0, 1.0, 1.0\n", "\n", "# Create a face-variable for the diffusion coefficient\n", "D = pf.CellVariable(m, 1e-5) # define the diffusivity\n", "D_face = pf.harmonicMean(D) # interpolate to face positions\n", "\n", "# Solve the problem in 2D\n", "eqnterms = [-pf.diffusionTerm(D_face)]\n", "pf.solvePDE(c, eqnterms)\n", "\n", "# Visualize the solution\n", "plt.figure()\n", "pf.visualizeCells(c)\n", "plt.colorbar();" ] }, { "cell_type": "markdown", "id": "4c6760b0-3aad-4968-ba43-b68616a321fb", "metadata": {}, "source": [ "For even more excitement, change to `Grid3D(Nx,Nx,Nx,L,L,L)`!" ] }, { "cell_type": "code", "execution_count": 33, "id": "4d353611", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 3D\n", "L = 0.01 # a 1 cm domain\n", "Nx = 10 # number of cells\n", "m = pf.Grid3D(Nx, Nx, Nx, L, L, L) \n", "c = pf.CellVariable(m, 0.0)\n", "\n", "# Now switch from Neumann boundary conditions to Dirichlet conditions:\n", "# left boundary: homogeneous Dirichlet left-side \n", "c.BCs.left.a, c.BCs.left.b, c.BCs.left.c = 0.0, 1.0, 0.0\n", "# right boundary: inhomogeneous Dirchlet right-side\n", "c.BCs.right.a, c.BCs.right.b, c.BCs.right.c = 0.0, 1.0, 1.0\n", "\n", "\n", "# Create a face-variable for the diffusion coefficient\n", "D = pf.CellVariable(m, 1e-5) # define the diffusivity\n", "D_face = pf.harmonicMean(D) # interpolate to face positions\n", "\n", "# Solve the problem in 3D\n", "eqnterms = [-pf.diffusionTerm(D_face)]\n", "pf.solvePDE(c, eqnterms)\n", "\n", "# Visualize the solution\n", "hfig = plt.figure()\n", "# ax = hfig.add_subplot(projection='3d')\n", "pf.visualizeCells(c)\n", "# plt.colorbar()" ] }, { "cell_type": "markdown", "id": "53dcfd1b-be3f-42c3-843b-0ecb99e30220", "metadata": {}, "source": [ "This is usually the way we develop new mathematical models for a physical phenomenon. Write the equation, solve it in 1D, compare it to the analytical solution, then solve it numerically in 2D and 3D for more realistic cases with heterogeneous transfer coefficients and other nonidealities (and perhaps compare it to some experimental data)" ] }, { "cell_type": "markdown", "id": "c01db4bf", "metadata": {}, "source": [ "### Solving a steady-state convection-diffusion problem, building up the matrix equation term-by-term" ] }, { "cell_type": "markdown", "id": "375df653", "metadata": {}, "source": [ "*This tutorial is adapted from a [FiPy convection-diffusion example](https://www.ctcms.nist.gov/fipy/examples/convection/index.html).*\n", "\n", "Here, we are going to add a convection term to the equation solved in the previous example. Additionally, we demonstrate a more 'low level' approach to setting up the solver, building up the matrix equation step-by-step by adding the relevant terms and finally solving the matrix equation. This gives a better idea how PyFVTool works internally.\n", "\n", "The differential equation reads\n", "\n", "$$\\nabla\\cdot\\left(\\mathbf{u} \\phi -D\\nabla \\phi \\right)=0$$\n", "\n", "Here, $\\mathbf{u}$ is a velocity vector (face variable) and $D$ is the diffusion coefficient (again a face variable). Please see the PDF document for an explanation of cell and face variables. We use Dirichlet (constant value) boundary conditions on the left and right boundaries. It is zero at the left boundary and one at the right boundary. The analytical solution of this differential equation reads\n", "\n", "$$c = \\frac{1-\\exp(ux/D)}{1-\\exp(uL/D)}$$" ] }, { "cell_type": "code", "execution_count": 34, "id": "eb98fba8", "metadata": {}, "outputs": [], "source": [ "# Define the domain and mesh\n", "L = 1.0 # domain length\n", "Nx = 25 # number of cells\n", "meshstruct = pf.Grid1D(Nx, L)\n", "x = meshstruct.cellcenters.x # extract the cell center positions for plotting purposes" ] }, { "cell_type": "code", "execution_count": 35, "id": "2efc62e1-6818-4601-9581-41c0452743bb", "metadata": {}, "outputs": [], "source": [ "c = pf.CellVariable(meshstruct, 0.0)" ] }, { "cell_type": "code", "execution_count": 36, "id": "37e65b9e-1e27-4da3-a52e-71114a32b66b", "metadata": {}, "outputs": [], "source": [ "# switch the left boundary to homogeneous Dirichlet\n", "c.BCs.left.a, c.BCs.left.b, c.BCs.left.c = 0.0, 1.0, 0.0\n", "c.BCs.right.a, c.BCs.right.b, c.BCs.right.c = 0.0, 1.0, 1.0" ] }, { "cell_type": "code", "execution_count": 37, "id": "ca55cf41-8542-47a0-9f19-f26688a77c2f", "metadata": {}, "outputs": [], "source": [ "# Make an identical, separate copy for the upwind calculation\n", "# to ensure independent calculations\n", "c_upwind = c.copy()" ] }, { "cell_type": "code", "execution_count": 38, "id": "44582f92-14de-428f-b288-525313c1a862", "metadata": {}, "outputs": [], "source": [ "# Define the transfer coefficients\n", "\n", "# Diffusion\n", "D_val = 1.0 # diffusion coefficient value\n", "D = pf.CellVariable(meshstruct, D_val) # assign diff. coeff. to all the cells\n", "Dave = pf.harmonicMean(D) # convert a cell variable to face variable" ] }, { "cell_type": "code", "execution_count": 39, "id": "92e5d6db-d17b-462b-a4e1-6cc98fe6116d", "metadata": {}, "outputs": [], "source": [ "# Convection\n", "u = -10.0 # velocity value\n", "u_face = pf.FaceVariable(meshstruct, u) # assign velocity value to cell faces" ] }, { "cell_type": "code", "execution_count": 40, "id": "8cb80936-62e6-4469-a2a3-40d99f60724e", "metadata": {}, "outputs": [], "source": [ "# solve using the central scheme, updating the CellVariable\n", "pf.solvePDE(c, [ pf.convectionTerm(u_face),\n", " -pf.diffusionTerm(Dave)]);" ] }, { "cell_type": "code", "execution_count": 41, "id": "a23f2e10-9554-47b1-9e4d-d547d0690f8f", "metadata": {}, "outputs": [], "source": [ "# solve using the upwind scheme\n", "pf.solvePDE(c_upwind, [ pf.convectionUpwindTerm(u_face),\n", " -pf.diffusionTerm(Dave)]);" ] }, { "cell_type": "code", "execution_count": 42, "id": "b26611d2-6593-4fd9-9522-eb50a22b8e30", "metadata": {}, "outputs": [], "source": [ "# analytic solution\n", "c_analytical = (1-np.exp(u*x/D_val))/(1-np.exp(u*L/D_val))" ] }, { "cell_type": "code", "execution_count": 43, "id": "24766548-2610-4e50-9358-86eca116dc64", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# visualization\n", "plt.figure()\n", "plt.plot(x, c.value, '-', label='central')\n", "plt.plot(x, c_upwind.value, '--', label='upwind')\n", "plt.plot(x, c_analytical, '.', label='analytic')\n", "plt.legend(fontsize=12, loc='best');" ] }, { "cell_type": "markdown", "id": "0d6405ba", "metadata": {}, "source": [ "As you see here, we obtain a more accurate result by using a central difference discretization scheme for the convection term compared to the first order upwind." ] }, { "cell_type": "markdown", "id": "7fc2ff8c", "metadata": {}, "source": [ "### Solve a transient diffusion equation" ] }, { "cell_type": "markdown", "id": "aedce5ac", "metadata": {}, "source": [ "This example is adapted from the FiPy 1D diffusion example\n", "\n", "The transient diffusion equation reads\n", "\n", "$$\\alpha\\frac{\\partial c}{\\partial t}+\\nabla \\cdot \\left(-D\\nabla c\\right)=0,$$\n", "\n", "where $c$ is the independent variable (concentration, temperature, etc) , $D$ is the diffusion coefficient, and $\\alpha$ is a constant." ] }, { "cell_type": "code", "execution_count": 44, "id": "32e5f01e", "metadata": {}, "outputs": [], "source": [ "# Define the domain and create a mesh structure\n", "L = 50.0 # domain length\n", "Nx = 20 # number of cells\n", "m = pf.Grid1D(Nx, L)\n", "x = m.cellcenters.x # cell centers position" ] }, { "cell_type": "code", "execution_count": 45, "id": "6bef1c44-0e4d-42ba-9037-26345477dd0f", "metadata": {}, "outputs": [], "source": [ "# Solution variable\n", "\n", "# Define the initial condition\n", "c_init = 0.0\n", "\n", "c = pf.CellVariable(m, c_init)" ] }, { "cell_type": "code", "execution_count": 46, "id": "3b1eec08", "metadata": {}, "outputs": [], "source": [ "# Switch the left and right boundaries to Dirichlet\n", "# left boundary\n", "c.BCs.left.a = 0.0\n", "c.BCs.left.b = 1.0\n", "c.BCs.left.c = 1.0\n", "# right boundary\n", "c.BCs.right.a = 0.0\n", "c.BCs.right.b = 1.0\n", "c.BCs.right.c = 0.0 " ] }, { "cell_type": "code", "execution_count": 47, "id": "f18ea390", "metadata": {}, "outputs": [], "source": [ "# Define the transfer coefficients:\n", "D_val = 1.0\n", "D = pf.CellVariable(m, D_val)\n", "Dave = pf.harmonicMean(D) # convert it to face variables\n", "\n", "# Define alfa, the coefficient of the transient term:\n", "alfa_val = 1.0\n", "alfa = pf.CellVariable(m, alfa_val)" ] }, { "cell_type": "code", "execution_count": 48, "id": "7b85b0af", "metadata": {}, "outputs": [], "source": [ "# Now define the time step and the final time:\n", "dt = 0.1 # time step\n", "final_t = 100.0" ] }, { "cell_type": "markdown", "id": "35c28d41", "metadata": {}, "source": [ "Here, we first create the term matrices that will not change as we progress stepwise in time, *i.e.* diffusion term. The matrix equation terms ($\\mathbf{M}$ and $\\textrm{rhs}$) corresponding to the boundary condition are handled automatically by PyFVTool via `solvePDE()`." ] }, { "cell_type": "code", "execution_count": 49, "id": "c18d087b", "metadata": {}, "outputs": [], "source": [ "diffterm = pf.diffusionTerm(Dave) # does not change when stepping in time" ] }, { "cell_type": "markdown", "id": "622917f4", "metadata": {}, "source": [ "The transitionTerm function gives a matrix of coefficient and a RHS vector. The matrix of coefficient does not change in each time step, but the RHS does. Therefore, we need to call the `transientTerm()` function inside the time loop. \n", "\n", "Here's the time stepping loop:" ] }, { "cell_type": "code", "execution_count": 50, "id": "761e4fae", "metadata": {}, "outputs": [], "source": [ "tt = []\n", "ci = []\n", "ca = []\n", "t = 0.\n", "while t < final_t:\n", " transterm = pf.transientTerm(c, dt, alfa) # re-evaluate at each time step\n", " eqnterms = [ transterm,\n", " -diffterm]\n", " pf.solvePDE(c, eqnterms)\n", " t += dt # solution time\n", "\n", " tt.append(t)\n", " ci.append(c.copy()) # store all solutions (copy all contents)\n", " ca.append( 1.0-erf(x/(2*np.sqrt(D_val*t)))) # store analytic" ] }, { "cell_type": "code", "execution_count": 51, "id": "7c5239b7", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Visualize the final results\n", "plt.figure()\n", "plt.plot(x, ci[-1].value, 'o', label='Numerical')\n", "plt.plot(x, ca[-1], '-', label='Analytic')\n", "plt.xlabel('Length [m]')\n", "plt.ylabel('c')\n", "plt.legend(fontsize=12, loc='best');" ] }, { "cell_type": "code", "execution_count": 52, "id": "2f1aa301", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plotting and visualization of the 1D transient diffusion solution \n", "hfig1, ax1 = plt.subplots()\n", "\n", "ax1.plot(x, ca[0], 'g-', label='first time step analytic')\n", "ax1.plot(x, ci[0].value, 'bo', label='first time step numerical ')\n", "\n", "ax1.plot(x, ca[-1], 'k-', label='final analytic')\n", "ax1.plot(x, ci[-1].value, 'ro', label='final numerical')\n", "\n", "ax1.set_xlim((0, L))\n", "ax1.set_ylim((0.0, 1.0))\n", "\n", "ax1.set_xlabel('x')\n", "ax1.set_ylabel('c')\n", "ax1.set_title('Transient diffusion')\n", "ax1.legend(fontsize=8);" ] }, { "cell_type": "raw", "id": "c38288af-b5dc-41c8-b979-135e5d4ea60e", "metadata": {}, "source": [ "# ANIMATION NEEDS TO BE FIXED TO WORK IN JUPYTER NOTEBOOK\n", "\n", "# ========= #\n", "\n", "from matplotlib.animation import FuncAnimation\n", "\n", "# create a figure to handle the solution animation\n", "# pre-generate the handles to the axes and the line\n", "hfig2 = plt.figure()\n", "ax2 = plt.axes(xlim=(0, L), ylim=(0.0, 1.0))\n", "line, = ax2.plot([], [], 'k-', lw=3, label='Numerical solution')\n", "circ, = ax2.plot([], [], 'o', lw=3, label='Analytic solution')\n", "\n", "ax2.set_xlabel('x')\n", "ax2.set_ylabel('c')\n", "ax2.set_title('1D transient diffusion solution')\n", "ax2.legend(fontsize=8)\n", "\n", "\n", "def init():\n", " line.set_data([], [])\n", " circ.set_data([], [])\n", " return line, circ\n", "\n", "def animate(ii):\n", " global x\n", " global ci\n", " global ca\n", " global Nx\n", " line.set_data(x, ci[ii].value\n", " circ.set_data(x, ca[ii]) \n", " return line, circ\n", "\n", "anim = FuncAnimation(hfig2, animate, init_func=init,\n", " frames=400, interval=20, blit=True)" ] }, { "cell_type": "markdown", "id": "5b21937d", "metadata": {}, "source": [ "### Convection equations; different discretization schemes" ] }, { "cell_type": "markdown", "id": "5b593dab", "metadata": {}, "source": [ "One special feature of this FVTool to be highlighted is its collection of discretization schemes for a linear convection term, which includes central difference (second order), upwind (first order), and TVD upwind scheme with various flux limiters.\n", "\n", "Convective terms in transport PDEs are notoriously difficult to handle numerically, since all discretization schemes for convection display to a certain extent a numerical artefact aptly called \"numerical diffusion\" (illustrated below). This is sometimes combined with unphysical oscillations appearing in the numerical solution (especially when trying to reduce numerical diffusion). Specific clever numerical schemes have been developed to mitigate both effects, but these come often at increased computational cost.\n", "\n", "Here, we are going to compare the performance of several schemes for solving a simple linear transient convection equation with an initial condition containing discontinuities. The discontinuties (or shocks) clearly bring out the numerical diffusion and the oscillations." ] }, { "cell_type": "markdown", "id": "7cb00aa3", "metadata": {}, "source": [ "We define a simple linear transient convection PDE, with an initial condition having discontinuties,\n", "\n", "$$ \\frac{\\partial \\varphi}{\\partial t} + \\nabla\\cdot\\left(\\vec{u}\\varphi\\right) = \\vec{0} $$ \n", "\n", "and periodic boundary conditions on a Cartesian 1D-domain with constant flow velocity coefficients $u$=0.3 m/s.\n", "\n", "The periodic boundary conditions make that the stuff that goes out on one side of the domain re-enters on the other side (like Pac-Man and the ghosts in the original arcade game). This provides a means to transport by convection the initial condition one complete cycle such that the numerical solution is superposed with the initial condition. In the case of pure 1D convection, the solution after one complete cycle should be identical to the initial condition.\n", "\n", "Initial condition:\n", "$$\\varphi\\left(x, 0\\right) \\,=\\, \\begin{equation}\n", "\\left\\{ \n", " \\begin{aligned}\n", " &0,\\,\\, &0.0 \\le \\,&x<0.04 \\\\\n", " &1\\,\\, &0.04\\le \\,&x<0.24 \\\\\n", " &0\\,\\, &0.24\\le \\,&x<0.36 \\\\ \n", " &\\sin\\left(10\\,\\pi\\,x\\right)\\,\\, &0.36\\le \\,&x<0.8 \\\\ \n", " &0,\\,\\, &0.8 \\le \\,&x\\le1.0 \\\\\n", " \\end{aligned}\n", " \\right.\n", "\\end{equation}\n", "$$" ] }, { "cell_type": "code", "execution_count": 53, "id": "4708b4cb-340e-44b3-9164-8115c27e3acc", "metadata": {}, "outputs": [], "source": [ "# define a 1D domain and mesh\n", "W = 1.0\n", "Nx = 500\n", "mesh1 = pf.Grid1D(Nx, W)\n", "x = mesh1.cellcenters.x" ] }, { "cell_type": "code", "execution_count": 54, "id": "69a288b4-fe75-4f0c-920a-6ea6fa6ad894", "metadata": {}, "outputs": [], "source": [ "# Set up a variable with initial values and BCs, that can be copied to have\n", "# the same IC and BCs for solving with different numerical schemes\n", "phiinit = pf.CellVariable(mesh1, 0.0)\n", "\n", "phiinit.value[(0.04 <= x) & (x < 0.24)] = 1.0\n", "phiinit.value[(0.36 <= x) & (x < 0.8)] = np.sin(x[(0.36 <= x) & (x < 0.8)]*10*np.pi) \n", "\n", "# Periodic boundary conditions:\n", "phiinit.BCs.left.periodic = True \n", "phiinit.BCs.right.periodic = True" ] }, { "cell_type": "code", "execution_count": 55, "id": "288f331e-4805-4b9c-9d30-e798b82b5918", "metadata": {}, "outputs": [], "source": [ "# velocity field\n", "u = 0.3 # m/s\n", "uf = pf.FaceVariable(mesh1, u)\n", "\n", "# transient term coefficient\n", "alfa = pf.CellVariable(mesh1, 1.0)" ] }, { "cell_type": "markdown", "id": "c5b3878f-1093-4820-8e25-a66845763c26", "metadata": {}, "source": [ "The time step and simulation length are set so that the solution has traveled exactly one cycle over the periodic boundaries." ] }, { "cell_type": "code", "execution_count": 56, "id": "dbcc4376-b4e2-4e15-9374-3502e78100a1", "metadata": {}, "outputs": [], "source": [ "# set time step and simulation length\n", "dt = 0.001 # [s], time step\n", "final_t = W/u" ] }, { "cell_type": "markdown", "id": "87acebe4-0343-497d-aeb9-fe854feabb9c", "metadata": {}, "source": [ "#### Standard central difference scheme for convection\n", "\n", "The standard `convectionTerm()` in PyFVTool uses the second order central differencing (CD) scheme. This scheme is not always recommended, especially at high Péclet numbers where convection dominates (see Chapter 4 of Versteeeg & Malalasekera (2007), \"An Introduction to Computational Fluid Dynamics: The Finite Volume Method.\", 2nd Edition).\n", "\n", "The following solver uses the CD scheme." ] }, { "cell_type": "code", "execution_count": 57, "id": "5f5ac7d9-e2b5-434a-89d4-5dd96fe0cae1", "metadata": {}, "outputs": [], "source": [ "# Solver: standard central difference\n", "\n", "# Initialize solution variable\n", "phi = phiinit.copy()\n", "\n", "tt = 0.0\n", "count = 0\n", "\n", "phi_cendif = []\n", "\n", "# Constant matrix eqn terms:\n", "convterm = pf.convectionTerm(uf) # standard central difference\n", "\n", "while (tt" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Visualize the numerical solutions obtained with the different schemes\n", "hfig, ax = plt.subplots(1, 1)\n", "ax.plot(x, phiinit.value, 'k-', label='initial value')\n", "ax.plot(x, phi_cendif[-1].value, 'b-', label='centr. diff.')\n", "ax.plot(x, phi_uw[-1].value, '-', color='orange', label='upwind');\n", "ax.plot(x, phi_tvd[-1].value, 'r-', label='TVD')\n", "ax.legend(fontsize=8);" ] }, { "cell_type": "markdown", "id": "2c33e49f-9a45-4591-99d7-230234e97157", "metadata": {}, "source": [ "In the figure, we can clearly see the strong numerical diffusion in the basic upwind scheme. Remember, that the correct solution of the PDE in these conditions should be identical to the initial condition.\n", "\n", "The central difference solution does not look too bad in this case, but has strange (and asymmetric) wiggles.\n", "\n", "TVD-upwind has much less numerical diffusion than simple upwind, without any oscillation, but requires 5 times(!) more calculations." ] }, { "cell_type": "markdown", "id": "25c7c7f3-9149-4aa6-8e84-43e249892077", "metadata": {}, "source": [ "Finally, we check mass conservation in this system." ] }, { "cell_type": "code", "execution_count": 61, "id": "c92a7e21-afea-4786-be53-49e5fa2e7ad9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total mass in system\n", "- initial 0.1780\n", "- central differencing 0.1780\n", "- upwind 0.1776\n", "- TVD upwind 0.1780\n" ] } ], "source": [ "print('Total mass in system')\n", "for name, totalmass in zip(['initial',\n", " 'central differencing',\n", " 'upwind',\n", " 'TVD upwind'],\n", " [phiinit.domainIntegral(),\n", " phi_cendif[-1].domainIntegral(),\n", " phi_uw[-1].domainIntegral(),\n", " phi_tvd[-1].domainIntegral()]):\n", " print(f'- {name:20s} {totalmass:.4f}')" ] }, { "cell_type": "raw", "id": "f25beda9-1c22-43c5-93b7-aa851c0c1688", "metadata": {}, "source": [ "# ANIMATION NEEDS TO BE FIXED TO WORK IN JUPYTER NOTEBOOK\n", "\n", "# ========= #\n", "\n", "from matplotlib.animation import FuncAnimation\n", "\n", "# create a figure to handle the solution animation\n", "# pre-generate the handles to the axes and the line\n", "hfig2 = plt.figure()\n", "ax2 = plt.axes(xlim=(0, W), ylim=(-1.25, 1.25))\n", "line, = ax2.plot([], [], 'ro', lw=3, label='TVD solution')\n", "circ, = ax2.plot([], [], '-', color='orange', lw=3, label='Upwind solution')\n", "\n", "ax2.set_xlabel('x')\n", "ax2.set_ylabel('c')\n", "ax2.set_title('1D transient convective-diffusion: Constant coeff.')\n", "ax2.legend(fontsize=8)\n", "\n", "\n", "def init():\n", " line.set_data([], [])\n", " circ.set_data([], [])\n", " return line, circ\n", "\n", "def animate(ii):\n", " global x\n", " global ci\n", " global ca\n", " global Nx\n", "\n", " circ.set_data(x, phi_tvd[ii]) \n", " line.set_data(x, phi_uw[ii].value) \n", " return line, circ\n", "\n", "anim = FuncAnimation(hfig2, animate, init_func=init,\n", " frames=400, interval=20, blit=True)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.9" } }, "nbformat": 4, "nbformat_minor": 5 }