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   "cells": [
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Texto y c\u00f3digo sujeto bajo Creative Commons Attribution license, CC-BY-SA. (c) Original por Lorena A. Barba y Gilbert Forsyth en 2013, traducido por F.J. Navarro-Brull para CAChemE.org"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "[@LorenaABarba](https://twitter.com/LorenaABarba)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "12 pasos para Navier-Stokes\n",
      "=====\n",
      "***"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\u00bfYa llegaste aqu\u00ed? \u00a1Este es el \u00faltimo paso! \u00bfCu\u00e1nto tiempo te llev\u00f3 a escribir su propio programa de soluci\u00f3n de Navier-Stokes en Python siguiendo este m\u00f3dulo interactivo? \u00a1Cu\u00e9ntanoslo!"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Paso 12: Conducci\u00f3n por un canal con Navier-Stokes\n",
      "----\n",
      "***"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "La \u00fanica diferencia entre este \u00faltimo paso y el paso 11 es que vamos a a\u00f1adir un t\u00e9rmino fuente de la ecuaci\u00f3n de momento-$u$, para imitar el efecto de presi\u00f3n ejercida en un canal. Aqu\u00ed est\u00e1n nuestras ecuaciones de Navier-Stokes modificadas:"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "\\begin{eqnarray}\n",
      "\\frac{\\partial u}{\\partial t}+u\\frac{\\partial u}{\\partial x}+v\\frac{\\partial u}{\\partial y}&=&-\\frac{1}{\\rho}\\frac{\\partial p}{\\partial x}+\\nu\\left(\\frac{\\partial^2 u}{\\partial x^2}+\\frac{\\partial^2 u}{\\partial y^2}\\right)+F\\\\\\\n",
      "\\frac{\\partial v}{\\partial t}+u\\frac{\\partial v}{\\partial x}+v\\frac{\\partial v}{\\partial y}&=&-\\frac{1}{\\rho}\\frac{\\partial p}{\\partial y}+\\nu\\left(\\frac{\\partial^2 v}{\\partial x^2}+\\frac{\\partial^2 v}{\\partial y^2}\\right)\n",
      "\\end{eqnarray}\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "$$\\frac{\\partial^2 p}{\\partial x^2}+\\frac{\\partial^2 p}{\\partial y^2}=-\\rho\\left(\\frac{\\partial u}{\\partial x}\\frac{\\partial u}{\\partial x}+2\\frac{\\partial u}{\\partial y}\\frac{\\partial v}{\\partial x}+\\frac{\\partial v}{\\partial y}\\frac{\\partial v}{\\partial y}\\right)\n",
      "$$"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Ecuaciones discretizadas"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Con paciencia y cuidado, escribimos la forma de las ecuaciones discretizadas. Es muy recomendable que escribas esto a mano, siguiendo mentalmente cada t\u00e9rmino mientras lo escribes.\n",
      "\n",
      "La ecuaci\u00f3n de momento-$u$:\n",
      "\n",
      "\\begin{eqnarray}\n",
      "&&\\frac{u_{i,j}^{n+1}-u_{i,j}^{n}}{\\Delta t}+u_{i,j}^{n}\\frac{u_{i,j}^{n}-u_{i-1,j}^{n}}{\\Delta x}+v_{i,j}^{n}\\frac{u_{i,j}^{n}-u_{i,j-1}^{n}}{\\Delta y}\\\\\\\n",
      "&&=-\\frac{1}{\\rho}\\frac{p_{i+1,j}^{n}-p_{i-1,j}^{n}}{2\\Delta x}\\\\\\\n",
      "&&+\\nu\\left(\\frac{u_{i+1,j}^{n}-2u_{i,j}^{n}+u_{i-1,j}^{n}}{\\Delta x^2}+\\frac{u_{i,j+1}^{n}-2u_{i,j}^{n}+u_{i,j-1}^{n}}{\\Delta y^2}\\right)+F_{i,j}\n",
      "\\end{eqnarray}\n",
      "\n",
      "La ecuaci\u00f3n de momento-$v$:\n",
      "\n",
      "\\begin{eqnarray}\n",
      "&&\\frac{v_{i,j}^{n+1}-v_{i,j}^{n}}{\\Delta t}+u_{i,j}^{n}\\frac{v_{i,j}^{n}-v_{i-1,j}^{n}}{\\Delta x}+v_{i,j}^{n}\\frac{v_{i,j}^{n}-v_{i,j-1}^{n}}{\\Delta y}\\\\\\\n",
      "&&=-\\frac{1}{\\rho}\\frac{p_{i,j+1}^{n}-p_{i,j-1}^{n}}{2\\Delta y}\\\\\\\n",
      "&&+\\nu\\left(\\frac{v_{i+1,j}^{n}-2v_{i,j}^{n}+v_{i-1,j}^{n}}{\\Delta x^2}+\\frac{v_{i,j+1}^{n}-2v_{i,j}^{n}+v_{i,j-1}^{n}}{\\Delta y^2}\\right)\n",
      "\\end{eqnarray}\n",
      "\n",
      "Y la ecuaci\u00f3n de presi\u00f3n\n",
      "\n",
      "\\begin{eqnarray}\n",
      "&&\\frac{p_{i+1,j}^{n}-2p_{i,j}^{n}+p_{i-1,j}^{n}}{\\Delta x^2}+\\frac{p_{i,j+1}^{n}-2*p_{i,j}^{n}+p_{i,j-1}^{n}}{\\Delta y^2}\\\\\\\n",
      "&&=\\rho\\left(\\frac{1}{\\Delta t}\\left(\\frac{u_{i+1,j}-u_{i-1,j}}{2\\Delta x}+\\frac{v_{i,j+1}-v_{i,j-1}}{2\\Delta y}\\right)\\right.\\\\\\\n",
      "&&-\\frac{u_{i+1,j}-u_{i-1,j}}{2\\Delta x}\\frac{u_{i+1,j}-u_{i-1,j}}{2\\Delta x}\\\\\\\n",
      "&&-2\\frac{u_{i,j+1}-u_{i,j-1}}{2\\Delta y}\\frac{v_{i+1,j}-v_{i-1,j}}{2\\Delta x}\\\\\\\n",
      "&&-\\left.\\frac{v_{i,j+1}-v_{i,j-1}}{2\\Delta y}\\frac{v_{i,j+1}-v_{i,j-1}}{2\\Delta y}\\right)\n",
      "\\end{eqnarray}"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Como siempre, tenemos que volver a organizar estas ecuaciones a la forma que necesitamos en el c\u00f3digo para que las iteraciones avancen:\n",
      "\n",
      "Para los componentes $u$- y $v$ de la ecuaci\u00f3n de momento, despejamos la velocidad en el instante `n+1`:\n",
      "\n",
      "$$u_{i,j}^{n+1} = u_{i,j}^{n} - u_{i,j}^{n}\\frac{\\Delta t}{\\Delta x}(u_{i,j}^{n}-u_{i-1,j}^{n})-v_{i,j}^{n}\\frac{\\Delta t}{\\Delta y}(u_{i,j}^{n}-u_{i,j-1}^{n})\n",
      "-\\frac{\\Delta t}{\\rho 2\\Delta x}(p_{i+1,j}^{n}-p_{i-1,j}^{n})$$\n",
      "$$+\\nu\\left[\\frac{\\Delta t}{\\Delta x^2}(u_{i+1,j}^{n}-2u_{i,j}^{n}+u_{i-1,j}^{n})\\right.\n",
      "+\\left.\\frac{\\Delta t}{\\Delta y^2}(u_{i,j+1}^{n}-2u_{i,j}^{n}+u_{i,j-1}^{n})\\right] + F\\Delta t$$\n",
      "\n",
      "$$\n",
      "v_{i,j}^{n+1}=v_{i,j}^{n}-u_{i,j}^{n}\\frac{\\Delta t}{\\Delta x}(v_{i,j}^{n}-v_{i-1,j}^{n})-v_{i,j}^{n}\\frac{\\Delta t}{\\Delta y}(v_{i,j}^{n}-v_{i,j-1}^{n})\n",
      "-\\frac{\\Delta t}{\\rho 2\\Delta y}(p_{i,j+1}^{n}-p_{i,j-1}^{n})$$\n",
      "$$+\\nu\\left[\\frac{\\Delta t}{\\Delta x^2}(v_{i+1,j}^{n}-2v_{i,j}^{n}+v_{i-1,j}^{n})\\right.\n",
      "+\\left.\\frac{\\Delta t}{\\Delta y^2}(v_{i,j+1}^{n}-2v_{i,j}^{n}+v_{i,j-1}^{n})\\right]$$\n",
      "\n",
      "Y para la ecuaci\u00f3n de la presi\u00f3n, despejamos $p_{i,j}^n$ para iterar en el pseudo-tiempo:\n",
      "\n",
      "$$\n",
      "p_{i,j}^{n}=\\frac{(p_{i+1,j}^{n}+p_{i-1,j}^{n})\\Delta y^2+(p_{i,j+1}^{n}+p_{i,j-1}^{n})\\Delta x^2}{2(\\Delta x^2+\\Delta y^2)}-\\frac{\\rho\\Delta x^2\\Delta y^2}{2(\\Delta x^2+\\Delta y^2)}\\times\n",
      "$$\n",
      "$$\\left[\\frac{1}{\\Delta t}\\left(\\frac{u_{i+1,j}-u_{i-1,j}}{2\\Delta x}+\\frac{v_{i,j+1}-v_{i,j-1}}{2\\Delta y}\\right)- \\frac{u_{i+1,j}-u_{i-1,j}}{2\\Delta x}\\frac{u_{i+1,j}-u_{i-1,j}}{2\\Delta x} \\right.$$\n",
      "$$- 2\\frac{u_{i,j+1}-u_{i,j-1}}{2\\Delta y}\\frac{v_{i+1,j}-v_{i-1,j}}{2\\Delta x}-\\left.\\frac{v_{i,j+1}-v_{i,j-1}}{2\\Delta y}\\frac{v_{i,j+1}-v_{i,j-1}}{2\\Delta y}\\right]$$"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "La condici\u00f3n inicial es $u, v, p=0$ en todos los puntos, y en la frontera la condici\u00f3n es:\n",
      "\n",
      "$u, v, p$ son peri\u00f3dicas en $x=0,2$\n",
      "\n",
      "$u, v =0$ en $y =0,2$\n",
      "\n",
      "$\\frac{\\partial p}{\\partial y}=0$ at $y =0,2$\n",
      "\n",
      "$F=1$ en el resto.\n",
      "\n",
      "Vamos a comenzar importando nuestras librer\u00edas:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline\n",
      "from mpl_toolkits.mplot3d import Axes3D\n",
      "from matplotlib import cm\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "En el paso 11, se aisl\u00f3 una parte de la ecuaci\u00f3n incorporada para que fuera m\u00e1s f\u00e1cil de analizar y aqu\u00ed vamos a hacer lo mismo. Una cosa a destacar es que tenemos condiciones de contorno peri\u00f3dicas en toda esta malla, por lo que necesitamos para calcular de forma expl\u00edcita los valores en el borde de entrada y salida de nuestra `vector` u."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def buildUpB(rho, dt, dx, dy, u, v):\n",
      "    b = np.zeros_like(u)\n",
      "    \n",
      "    b[1:-1,1:-1]=rho*(1/dt*((u[2:,1:-1]-u[0:-2,1:-1])/(2*dx)+(v[1:-1,2:]-v[1:-1,0:-2])/(2*dy))-\\\n",
      "\t\t((u[2:,1:-1]-u[0:-2,1:-1])/(2*dx))**2-\\\n",
      "\t\t2*((u[1:-1,2:]-u[1:-1,0:-2])/(2*dy)*(v[2:,1:-1]-v[0:-2,1:-1])/(2*dx))-\\\n",
      "\t\t((v[1:-1,2:]-v[1:-1,0:-2])/(2*dy))**2)\t\n",
      "\t\n",
      "\t#### Condici\u00f3n de contorno peri\u00f3dica de presi\u00f3n @ x = 2\n",
      "    b[-1,1:-1]=rho*(1/dt*((u[0,1:-1]-u[-2,1:-1])/(2*dx)+(v[-1,2:]-v[-1,0:-2])/(2*dy))-\\\n",
      "\t\t((u[0,1:-1]-u[-2,1:-1])/(2*dx))**2-\\\n",
      "\t\t2*((u[-1,2:]-u[-1,0:-2])/(2*dy)*(v[0,1:-1]-v[-2,1:-1])/(2*dx))-\\\n",
      "\t\t((v[-1,2:]-v[-1,0:-2])/(2*dy))**2)\t\n",
      "\n",
      "\t#### Condici\u00f3n de contorno peri\u00f3dica de presi\u00f3n @ x = 0\n",
      "    b[0,1:-1]=rho*(1/dt*((u[1,1:-1]-u[-1,1:-1])/(2*dx)+(v[0,2:]-v[0,0:-2])/(2*dy))-\\\n",
      "\t\t((u[1,1:-1]-u[-1,1:-1])/(2*dx))**2-\\\n",
      "\t\t2*((u[0,2:]-u[0,0:-2])/(2*dy)*(v[1,1:-1]-v[-1,1:-1])/(2*dx))-\\\n",
      "\t\t((v[0,2:]-v[0,0:-2])/(2*dy))**2)\n",
      "    \n",
      "    return b"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Tambi\u00e9n vamos a definir una funci\u00f3n de presi\u00f3n-Poisson iterativa tal y como lo hicimos en el paso 11. Una vez m\u00e1s, ten en cuenta que hay que incluir las condiciones de contorno peri\u00f3dicas en el borde de entrada y salida. Tambi\u00e9n tenemos que especificar las condiciones de contorno en la parte superior e inferior de nuestra malla."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def presPoissPeriodic(p, dx, dy):\n",
      "    pn = np.empty_like(p)\n",
      "    \n",
      "    for q in range(nit):\n",
      "        pn[:]=p[:]\n",
      "        p[1:-1,1:-1] = ((pn[2:,1:-1]+pn[0:-2,1:-1])*dy**2+(pn[1:-1,2:]+pn[1:-1,0:-2])*dx**2)/\\\n",
      "            (2*(dx**2+dy**2)) - dx**2*dy**2/(2*(dx**2+dy**2))*b[1:-1,1:-1]\n",
      "        \n",
      "        #### Condici\u00f3n de contorno peri\u00f3dica de presi\u00f3n @ x = 2\n",
      "        p[-1,1:-1] = ((pn[0,1:-1]+pn[-2,1:-1])*dy**2+(pn[-1,2:]+pn[-1,0:-2])*dx**2)/\\\n",
      "            (2*(dx**2+dy**2)) - dx**2*dy**2/(2*(dx**2+dy**2))*b[-1,1:-1]\n",
      "        \n",
      "        #### Condici\u00f3n de contorno peri\u00f3dica de presi\u00f3n @ x = 0\n",
      "        p[0,1:-1] = ((pn[1,1:-1]+pn[-1,1:-1])*dy**2+(pn[0,2:]+pn[0,0:-2])*dx**2)/\\\n",
      "\t\t\t(2*(dx**2+dy**2)) -\\\n",
      "\t\t\tdx**2*dy**2/(2*(dx**2+dy**2))*b[0,1:-1]\n",
      "\t\t\n",
      "\t\t#### Condicion de contorno en la pared, presi\u00f3n\n",
      "        # dp/dy = 0 at y = 2\n",
      "        p[-1,:] = p[-2,:]\n",
      "        # dp/dy = 0 at y = 0\n",
      "        p[0,:] = p[1,:]\n",
      "    \n",
      "    return p"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Ahora que tenemos nuestra lista familiar de variables y condiciones iniciales para crearlas antes de empezar."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "## Creaci\u00f3n de variables\n",
      "nx = 41\n",
      "ny = 41\n",
      "nt = 10\n",
      "nit=50 \n",
      "c = 1\n",
      "dx = 2.0/(nx-1)\n",
      "dy = 2.0/(ny-1)\n",
      "x = np.linspace(0,2,nx)\n",
      "y = np.linspace(0,2,ny)\n",
      "Y,X = np.meshgrid(y,x)\n",
      "\n",
      "\n",
      "## Variables f\u00edsicas\n",
      "rho = 1\n",
      "nu = .1\n",
      "F = 1\n",
      "dt = .01\n",
      "\n",
      "# Condiciones inciales\n",
      "u = np.zeros((ny,nx)) ## Crea un vecotr XxY de 0\n",
      "un = np.zeros((ny,nx)) ## Crea un vecotr XxY de 0\n",
      "\n",
      "v = np.zeros((ny,nx)) ## Crea un vecotr XxY de 0\n",
      "vn = np.zeros((ny,nx)) ## Crea un vecotr XxY de 0\n",
      "\n",
      "p = np.ones((ny,nx)) ## Crea un vecotr XxY de unos\n",
      "pn = np.ones((ny,nx)) ## Crea un vecotr XxY de unos\n",
      "\n",
      "b = np.zeros((ny,nx))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Para el bien de de nuestros c\u00e1lculos, vamos a llegar de nuevo a un truco que se utiliz\u00f3 en el Paso 9 de la ecuaci\u00f3n de Laplace. Estamos interesados en lo que se ver\u00e1 en nuestra figura una vez que hemos llegado a un estado casi estacionario. Tenemos la posibilidad de especificar un n\u00famero de pasos en el tiempo `nt` e incrementarlo hasta que estemos satisfechos con los resultados, o bien, podemos decirle a nuestro c\u00f3digo que se ejecute hasta que la diferencia entre dos iteraciones consecutivas sea muy peque\u00f1a.\n",
      "\n",
      "Tambi\u00e9n tenemos que manejar ** 8 ** condiciones de contorno separadas para cada iteraci\u00f3n. El siguiente c\u00f3digo escribe cada uno de ellos de forma expl\u00edcita. Si est\u00e1s interesado en un desaf\u00edo, se puede tratar de escribir una funci\u00f3n que puede manejar todas o algunas de estas condiciones de contorno. Si quieres intentarlo, probablemente deber\u00edas leer el uso de diccionarios en Python [(dictionaries)](http://docs.python.org/2/tutorial/datastructures.html#dictionaries). "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "udiff = 1\n",
      "stepcount = 0\n",
      "\n",
      "while udiff > .001:\n",
      "    un[:] = u[:]\n",
      "    vn[:] = v[:]\n",
      "\t\n",
      "    b = buildUpB(rho, dt, dx, dy, u, v)\n",
      "    p = presPoissPeriodic(p, dx, dy)\n",
      "\t\t\n",
      "    u[1:-1,1:-1] = un[1:-1,1:-1]-\\\n",
      "\t\tun[1:-1,1:-1]*dt/dx*(un[1:-1,1:-1]-un[0:-2,1:-1])-\\\n",
      "\t\tvn[1:-1,1:-1]*dt/dy*(un[1:-1,1:-1]-un[1:-1,0:-2])-\\\n",
      "\t\tdt/(2*rho*dx)*(p[2:,1:-1]-p[0:-2,1:-1])+\\\n",
      "\t\tnu*(dt/dx**2*(un[2:,1:-1]-2*un[1:-1,1:-1]+un[0:-2,1:-1])+\\\n",
      "\t\tdt/dy**2*(un[1:-1,2:]-2*un[1:-1,1:-1]+un[1:-1,0:-2]))+F*dt\n",
      "\t\n",
      "    v[1:-1,1:-1] = vn[1:-1,1:-1]-\\\n",
      "\t\tun[1:-1,1:-1]*dt/dx*(vn[1:-1,1:-1]-vn[0:-2,1:-1])-\\\n",
      "\t\tvn[1:-1,1:-1]*dt/dy*(vn[1:-1,1:-1]-vn[1:-1,0:-2])-\\\n",
      "\t\tdt/(2*rho*dy)*(p[1:-1,2:]-p[1:-1,0:-2])+\\\n",
      "\t\tnu*(dt/dx**2*(vn[2:,1:-1]-2*vn[1:-1,1:-1]+vn[0:-2,1:-1])+\\\n",
      "\t\t(dt/dy**2*(vn[1:-1,2:]-2*vn[1:-1,1:-1]+vn[1:-1,0:-2])))\n",
      "\t\n",
      "\t#### Condici\u00f3n peri\u00f3dica de contorno u @ x = 2\n",
      "    u[-1,1:-1] = un[-1,1:-1]-\\\n",
      "\t\tun[-1,1:-1]*dt/dx*(un[-1,1:-1]-un[-2,1:-1])-\\\n",
      "\t\tvn[-1,1:-1]*dt/dy*(un[-1,1:-1]-un[-1,0:-2])-\\\n",
      "\t\tdt/(2*rho*dx)*(p[0,1:-1]-p[-2,1:-1])+\\\n",
      "\t\tnu*(dt/dx**2*(un[0,1:-1]-2*un[-1,1:-1]+un[-2,1:-1])+\\\n",
      "\t\tdt/dy**2*(un[-1,2:]-2*un[-1,1:-1]+un[-1,0:-2]))+F*dt\n",
      "\n",
      "\t#### Condici\u00f3n peri\u00f3dica de contorno u @ x = 0\n",
      "    u[0,1:-1] = un[0,1:-1]-\\\n",
      "\t\tun[0,1:-1]*dt/dx*(un[0,1:-1]-un[-1,1:-1])-\\\n",
      "\t\tvn[0,1:-1]*dt/dy*(un[0,1:-1]-un[0,0:-2])-\\\n",
      "\t\tdt/(2*rho*dx)*(p[1,1:-1]-p[-1,1:-1])+\\\n",
      "\t\tnu*(dt/dx**2*(un[1,1:-1]-2*un[0,1:-1]+un[-1,1:-1])+\\\n",
      "\t\tdt/dy**2*(un[0,2:]-2*un[0,1:-1]+un[0,0:-2]))+F*dt\n",
      "\n",
      "\t#### Condici\u00f3n peri\u00f3dica de contorno v @ x = 2\n",
      "    v[-1,1:-1] = vn[-1,1:-1]-\\\n",
      "\t\tun[-1,1:-1]*dt/dx*(vn[-1,1:-1]-vn[-2,1:-1])-\\\n",
      "\t\tvn[-1,1:-1]*dt/dy*(vn[-1,1:-1]-vn[-1,0:-2])-\\\n",
      "\t\tdt/(2*rho*dy)*(p[-1,2:]-p[-1,0:-2])+\\\n",
      "\t\tnu*(dt/dx**2*(vn[0,1:-1]-2*vn[-1,1:-1]+vn[-2,1:-1])+\\\n",
      "\t\t(dt/dy**2*(vn[-1,2:]-2*vn[-1,1:-1]+vn[-1,0:-2])))\n",
      "\n",
      "\t#### Condici\u00f3n peri\u00f3dica de contorno v @ x = 0\n",
      "    v[0,1:-1] = vn[0,1:-1]-\\\n",
      "\t\tun[0,1:-1]*dt/dx*(vn[0,1:-1]-vn[-1,1:-1])-\\\n",
      "\t\tvn[0,1:-1]*dt/dy*(vn[0,1:-1]-vn[0,0:-2])-\\\n",
      "\t\tdt/(2*rho*dy)*(p[0,2:]-p[0,0:-2])+\\\n",
      "\t\tnu*(dt/dx**2*(vn[1,1:-1]-2*vn[0,1:-1]+vn[-1,1:-1])+\\\n",
      "\t\t(dt/dy**2*(vn[0,2:]-2*vn[0,1:-1]+vn[0,0:-2])))\n",
      "\n",
      "\t#### Pared C.C: u,v = 0 @ y = 0,2\n",
      "    u[:,0] = 0\n",
      "    u[:,-1] = 0\n",
      "    v[:,0] = 0\n",
      "    v[:,-1]=0\n",
      "\t\n",
      "    udiff = (np.sum(u)-np.sum(un))/np.sum(u)\n",
      "    stepcount += 1"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Puedes ver que tambi\u00e9n hemos incluido una variable `stepcount` para ver cuantas iteraciones realiz\u00f3 nuestro bucle antes de que llegar\u00e1 a la condici\u00f3n de parada."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print stepcount"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "499\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Si quieres ver c\u00f3mo el n\u00famero de iteraciones aumenta a medida que nuestra condici\u00f3n de `udiff` se hace m\u00e1s y m\u00e1s peque\u00f1a, trata de definir una funci\u00f3n para realizar el bucle `while` escrito arriba para que tenga una entrada `udiff` y devuelva el n\u00famero de iteraciones que la funci\u00f3n ejecuta.\n",
      "\n",
      "Por ahora, vamos a ver los resultados. Hemos utilizado una representaci\u00f3n de flechas (quiver) para a ver los resultados de flujo en una cavidad y tambi\u00e9n funciona bien para el flujo en un canal."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure(figsize = (11,7), dpi=100)\n",
      "plt.quiver(X[::3, ::3], Y[::3, ::3], u[::3, ::3], v[::3, ::3])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "<matplotlib.quiver.Quiver at 0x7f3aeb733590>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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GjRsNfl1zR0CTXnFcsGABevfurX1X2qNHD7N4t9GYhQsXonv37tqpPSQkxCK6lyxZgoCA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\n1niutEwmo86dOwvdERERRne7urparJvo/69iKJVKatu2rdHdLi4uJu0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seXh4SJ0kSnl5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\nAQAAAEAUDI4AAAAAIAoGRwAAAAAQ5f8BzzdmkaqFw50AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f3aeb78a290>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "La estructura del comando `quiver` que es `[::3, ::3]` son \u00fatiles cuando se trata de grandes cantidades de datos que se desean visualizar. El que se ha utilizado arriba dice a `matplotlib` que s\u00f3lo trace el tercero de cada punto. Si prescindimos de ello, se puede ver que los resultados pueden parecer un poco abarrotados."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fig = plt.figure(figsize = (11,7), dpi=100)\n",
      "plt.quiver(X, Y, u, v)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
       "text": [
        "<matplotlib.quiver.Quiver at 0x7f3aeb6e49d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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jx7nbjRITE2nmzJncTQ+LFy9muvqvy6lTp7ibHlJTU2n69OncTQ/Lly/nbjc6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\nb9++uGbNGlEGZ2dnp7Z2q1atcM6cOXjnzh29tbNnz1artbCwwA8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+/PhXPE/suSw0NJT0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\n54kOGAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f3aeb766b90>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Aprende m\u00e1s\n",
      "***"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### \u00bfCu\u00e1l es el significado del t\u00e9rmino $F$?\n",
      "\n",
      "El Paso 12 es un ejercicio que demuestra el problema de flujo en un canal o tubo. Si recuerdas la clase de mec\u00e1nica de fluidos, un gradiente de presi\u00f3n especificado es lo que impulsa el flujo de Poisseulle.\n",
      "\n",
      "Recordemos la ecuaci\u00f3n de momento-$x$\n",
      "\n",
      "$$\\frac{\\partial u}{\\partial t}+u \\cdot \\nabla u = -\\frac{\\partial p}{\\partial x}+\\nu \\nabla^2 u$$\n",
      "\n",
      "Lo que se hace realmente en el paso 12 es dividir la presi\u00f3n en componentes estacionarias y no estacionarias $p=P+p'$. El gradiente de presi\u00f3n constante aplicado es la constante $-\\frac{\\partial P}{\\partial x}=F$ (interpretado como un t\u00e9rmino fuente), y el componente de inestabilidad es $\\frac{\\partial p'}{\\partial x}$. As\u00ed que la presi\u00f3n que se resuelve en el Paso 12 es en realidad $p'$, lo que para un flujo constante es, de hecho, igual a cero en todas partes.\n",
      "\n",
      "**\u00bfPor qu\u00e9 hicimos esto?**\n",
      "\n",
      "Ten en cuenta que usamos condiciones de contorno peri\u00f3dicas para este flujo. Para un flujo con un gradiente de presi\u00f3n constante, el valor de la presi\u00f3n en el borde izquierdo del dominio debe ser diferente de la presi\u00f3n en el borde derecho. As\u00ed que no podemos aplicar las condiciones de contorno peri\u00f3dicas a la presi\u00f3n directamente. Es m\u00e1s f\u00e1cil fijar el gradiente y luego resolver para las perturbaciones en la presi\u00f3n.\n",
      "\n",
      "**\u00bfNo debemos esperar siempre una $p'$ uniforme/constante entonces?**\n",
      "\n",
      "Eso es cierto s\u00f3lo en el caso de flujos laminares estables. A altos n\u00fameros de Reynolds, los flujos en los canales pueden llegar a ser turbulentos, y vamos a ver las fluctuaciones inestables en la presi\u00f3n, lo que resultar\u00e1 en valores distintos de cero para $p'$. \n",
      "\n",
      "En el paso 12, ten en cuenta que el campo de presi\u00f3n en s\u00ed no es constante, sino que es el campo de perturbaci\u00f3n de presi\u00f3n que hay. El campo de presi\u00f3n var\u00eda linealmente a lo largo del canal con pendiente igual al gradiente de presi\u00f3n. Tambi\u00e9n, para flujos incompresibles, el valor absoluto de la presi\u00f3n es intrascendente."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "##### Explora m\u00e1s materiales online de CFD"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "El m\u00f3dulo interactivo **12 pasos para Navier-Stokes** es uno de los varios componentes de la clase de *Computational Fluid Dynamics* impartida por la Prof. Lorena A. Barba en la Universidad de Boston entre 2009 y 2013.\n",
      "\n",
      "Para una muestra de otros materiales de esta clase, se puede explorar la secci\u00f3n de **Resources** en la parte de *Spring 2013* de [course's Piazza site](https://piazza.com/bu/spring2013/me702/resources).\n",
      "\n",
      "\n",
      "***"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.core.display import HTML\n",
      "def css_styling():\n",
      "    styles = open(\"../styles/custom.css\", \"r\").read()\n",
      "    return HTML(styles)\n",
      "css_styling()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<style>\n",
        "    @font-face {\n",
        "        font-family: \"Computer Modern\";\n",
        "        src: url('http://mirrors.ctan.org/fonts/cm-unicode/fonts/otf/cmunss.otf');\n",
        "    }\n",
        "    div.cell{\n",
        "        width:800px;\n",
        "        margin-left:16% !important;\n",
        "        margin-right:auto;\n",
        "    }\n",
        "    h1 {\n",
        "        font-family: Helvetica, serif;\n",
        "    }\n",
        "    h2 {\n",
        "        font-family: Helvetica, serif;\n",
        "    }\n",
        "    h4{\n",
        "        margin-top:12px;\n",
        "        margin-bottom: 3px;\n",
        "       }\n",
        "    div.text_cell_render{\n",
        "        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n",
        "        line-height: 135%;\n",
        "        font-size: 120%;\n",
        "        width:600px;\n",
        "        margin-left:auto;\n",
        "        margin-right:auto;\n",
        "    }\n",
        "    .CodeMirror{\n",
        "            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n",
        "    }\n",
        "/*    .prompt{\n",
        "        display: None;\n",
        "    }*/\n",
        "    .text_cell_render h5 {\n",
        "        font-weight: 300;\n",
        "        font-size: 16pt;\n",
        "        color: #4057A1;\n",
        "        font-style: italic;\n",
        "        margin-bottom: .5em;\n",
        "        margin-top: 0.5em;\n",
        "        display: block;\n",
        "    }\n",
        "    \n",
        "    .warning{\n",
        "        color: rgb( 240, 20, 20 )\n",
        "        }  \n",
        "</style>\n",
        "<script>\n",
        "    MathJax.Hub.Config({\n",
        "                        TeX: {\n",
        "                           extensions: [\"AMSmath.js\"]\n",
        "                           },\n",
        "                tex2jax: {\n",
        "                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n",
        "                    displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ]\n",
        "                },\n",
        "                displayAlign: 'center', // Change this to 'center' to center equations.\n",
        "                \"HTML-CSS\": {\n",
        "                    styles: {'.MathJax_Display': {\"margin\": 4}}\n",
        "                }\n",
        "        });\n",
        "</script>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "<IPython.core.display.HTML at 0x611dd68>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "> (La celda de arriba establece el formato de este notebook)"
     ]
    }
   ],
   "metadata": {}
  }
 ]
}