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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from simulation import Lattice, Geometry\n",
"from symbolic.generator import LBM\n",
"import symbolic.D2Q9 as D2Q9"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"lbm = LBM(D2Q9)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def cavity(geometry, x, y):\n",
" if x == 1 or y == 1 or x == geometry.size_x-2:\n",
" return 2\n",
" elif y == geometry.size_y-2:\n",
" return 3\n",
" else:\n",
" return 1"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"boundary = \"\"\"\n",
" if ( m == 2 ) {\n",
" u_0 = 0.0;\n",
" u_1 = 0.0;\n",
" }\n",
" if ( m == 3 ) {\n",
" u_0 = 0.1;\n",
" u_1 = 0.0;\n",
" }\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib\n",
"import matplotlib.pyplot as plt\n",
"import numpy"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"def generate_moment_plot(lattice, m):\n",
" velocity = numpy.ndarray(shape=tuple(reversed(lattice.geometry.inner_size())))\n",
" for x, y in lattice.geometry.inner_cells():\n",
" velocity[y-1,x-1] = numpy.sqrt(m[1,lattice.gid(x,y)]**2 + m[2,lattice.gid(x,y)]**2)\n",
" plt.figure(figsize=(8,8))\n",
" plt.imshow(velocity, origin='lower', vmin=0.0, cmap=plt.get_cmap('seismic'))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"def test(nX=64, nY=64, nSteps=1000, tau=0.6):\n",
" lattice = Lattice(\n",
" descriptor = D2Q9,\n",
" geometry = Geometry(nX, nY),\n",
"\n",
" moments = lbm.moments(optimize = False),\n",
" collide = lbm.bgk(f_eq = lbm.equilibrium(), tau = tau),\n",
"\n",
" boundary_src = boundary)\n",
" lattice.setup_geometry(cavity)\n",
" \n",
" for i in range(0,nSteps):\n",
" lattice.evolve()\n",
" generate_moment_plot(lattice, lattice.get_moments())"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"import ipywidgets as widgets\n",
"from IPython.display import display\n",
"from ipywidgets import interactive"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ba655c48ce2b4f4898ca9fcb61e693a5",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"interactive(children=(IntSlider(value=64, description='nX', max=1024, min=32, step=32), IntSlider(value=64, de…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"interactive(test, nX=(32,1024,32), nY=(32,1024,32), nSteps=(0,100000,500), tau=(0.515,1.0,0.01))"
]
},
{
"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": "3.7.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|
