{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Bubble Point" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Imagine an experiment in which a liquid mixture of known composition is slowly heated under constant pressure. The bubble point temperature is reached when the first bubble of vapor appears. This is the temperature at which a mixture begins to boil.\n", "\n", "Next, imagine an experiment in which the pressure is lowered for a liquid mixture of known composition. The temperature is held constant. In this case the bubble point pressure is reach when the first bubble appears.\n", "\n", "In each case, the composition $y_n, n = 1,2,\\ldots,N$ of the bubble is given by\n", "\n", "$$ y_n = x_n \\frac{P^{sat}_n(T)}{P}$$\n", "\n", "which, at the bubble point, must satisfy the condition\n", "\n", "$$ \\sum_{n=1}^N x_n \\frac{P^{sat}_n(T)}{P} = 1$$" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Notebook Initialization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Initialize the IPython workspace with pylab and set useful plotting defaults useful for presentations." ] }, { "cell_type": "code", "collapsed": false, "input": [ "%pylab inline\n", "pylab.rcParams['figure.figsize'] = (10,4)\n", "pylab.rcParams['font.size'] = 12\n", "pylab.rcParams['lines.linewidth'] = 1.6" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 15 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example: Bubble Point Pressure of Pure Water" ] }, { "cell_type": "code", "collapsed": false, "input": [], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 26 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Dew Point" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, solving for $x_n$, then summing gives the dew point calculation\n", "\n", "$$ x_n = y_n \\frac{P}{P^{sat}_n(T)}\\qquad \\implies \\qquad \\sum_{n=1}^N y_n \\frac{P}{P^{sat}_n(T)} = 1$$\n", "\n", "For binary mixtures $x_B = 1-x_A$\n", "\n", "$$ x_A\\left( P^{sat}_A(T) - P^{sat}_B(T)\\right) = P - P^{sat}_B(T) $$\n", "\n", "which gives\n", "\n", "$$ x_A = \\frac{P - P^{sat}_B(T)}{P^{sat}_A(T) - P^{sat}_B(T)} \\qquad x_B = \\frac{P^{sat}_A - P}{P^{sat}_A(T) - P^{sat}_B(T)}$$\n", "\n", "$$ y_A = x_A\\frac{P^{sat}_A(T)}{P} \\qquad\\quad\\quad\\quad y_B = x_B\\frac{P^{sat}_B(T)}{P}$$" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Txy Diagrams" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from scipy.optimize import brentq as fzero\n", "\n", "A = 'methanol'\n", "B = 'water'\n", "\n", "def Tbub(P,xA):\n", " fbub = lambda T: xA*Psat[A](T)/P + (1-xA)*Psat[B](T)/P - 1\n", " return fzero(fbub,0.99*Tsat[A](P),1.01*Tsat[B](P))\n", "\n", "def Tdew(P,yA):\n", " fdew = lambda T:yA*P/Psat[A](T) + (1-yA)*P/Psat[B](T) - 1\n", " return fzero(fdew,0.99*Tsat[A](P),1.01*Tsat[B](P))\n", "\n", "x = linspace(0,1)\n", "plot(x,map(lambda x: Tbub(760,x),x))\n", "plot(x,map(lambda x: Tdew(760,x),x))\n", "xlabel('x,y ' + A)\n", "ylabel('Temperature $^{\\circ}C$')\n", "title('Txy Diagram: ' + A + \"/\" + B)\n", "legend(['Bubble','Dew'],'best')\n", "grid()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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BxsYGDw+PVHG5uLjg5uaGu7s71tbWbNq0CYBNmzYxcOBANm3aRO3atWnbti2+vr6pRqR1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"text": [ "" ] } ], "prompt_number": 30 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "xy Diagrams" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example: Methanol/Benzene Azeotrope" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Raoult's law work" ] }, { "cell_type": "code", "collapsed": false, "input": [ "A = 'methanol'\n", "B = 'benzene'\n", "\n", "Txy = array([\\\n", " [70.67, 0.026, 0.267],\\\n", " [66.44, 0.050, 0.371],\\\n", " [62.87, 0.088, 0.457],\\\n", "])\n", "\n", "Txy = array([\\\n", " [351.76, 0.00200, 0.04100],\\\n", " [350.80, 0.00280, 0.06600],\\\n", " [350.67, 0.00300, 0.06840],\\\n", " [350.43, 0.00300, 0.08120],\\\n", " [350.37, 0.00410, 0.08200],\\\n", " [349.20, 0.00550, 0.11720],\\\n", " [348.45, 0.00580, 0.13860],\\\n", " [346.92, 0.01340, 0.19240],\\\n", " [346.21, 0.01900, 0.20600],\\\n", " [344.11, 0.02760, 0.26580],\\\n", " [341.10, 0.04600, 0.33920],\\\n", " [340.90, 0.04800, 0.34400],\\\n", " [337.17, 0.08300, 0.43000],\\\n", " [334.23, 0.14370, 0.49980],\\\n", " [334.19, 0.17000, 0.51800],\\\n", " [333.07, 0.18580, 0.52120],\\\n", " [332.55, 0.27600, 0.54420],\\\n", " [331.58, 0.36400, 0.57360],\\\n", " [331.30, 0.45580, 0.58700],\\\n", " [331.19, 0.52400, 0.59810],\\\n", " [331.12, 0.59700, 0.61140],\\\n", " [331.12, 0.63700, 0.62000],\\\n", " [331.13, 0.67390, 0.62900],\\\n", " [331.14, 0.68000, 0.63220],\\\n", " [331.20, 0.70240, 0.64080],\\\n", " [331.21, 0.70710, 0.64160],\\\n", " [331.28, 0.72980, 0.65090],\\\n", " [331.37, 0.74400, 0.65310],\\\n", " [331.60, 0.77680, 0.66910],\\\n", " [331.80, 0.80310, 0.68380],\\\n", " [332.14, 0.83800, 0.70900],\\\n", " [332.75, 0.87540, 0.74800],\\\n", " [333.33, 0.89980, 0.77420],\\\n", " [333.75, 0.91780, 0.80020],\\\n", " [334.05, 0.92500, 0.81180],\\\n", " [334.79, 0.94240, 0.85100],\\\n", " [335.75, 0.96520, 0.89980],\\\n", " [336.72, 0.98490, 0.94920],\\\n", " [336.87, 0.98800, 0.95720],\\\n", " [336.93, 0.98900, 0.96100],\\\n", " [337.10, 0.99180, 0.96840],\\\n", " [337.36, 0.99490, 0.97990]])\n", "\n", "P = 760\n", "T = linspace(Tsat[A](P),Tsat[B](P))\n", "\n", "x = map(lambda T: (P - Psat[B](T))/(Psat[A](T)-Psat[B](T)), T)\n", "y = map(lambda T: xA(T)*Psat[A](T)/P, T)\n", "\n", "figure(figsize=(6,6))\n", "plot(x,y)\n", "plot(Txy.T[1],Txy.T[2],'r',linewidth=2)\n", "plot(Txy.T[1],Txy.T[2],'ro',markersize=10)\n", "plot([0,1],[0,1],'k--')\n", "axis('equal')\n", "ylim([0,1])\n", "xlim([0,1])\n", "xlabel('x: ' + A)\n", "ylabel('y: ' + A)\n", "title('xy Diagram: ' + A + '/' + B)\n", "grid()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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k1KhRNG7cONWYjGRMef7tt9/m/fffZ+3atfj5+XHmzBk2bdpErVq10p1n48aNtG/fPpXb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\nNm+rJSIlOET3lC3k9OyJYaGhql2vtBT429+kbikWDCLSIoc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"text": [ "" ] } ], "prompt_number": 63 }, { "cell_type": "code", "collapsed": false, "input": [ "def P(T,x):\n", " z = 0\n", " for k in range(len(x)):\n", " z += x[k]*Psat[species[k]](T)\n", " return z" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 20 }, { "cell_type": "code", "collapsed": false, "input": [ "Tbub(760,1)" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 21, "text": [ "80.0999933615606" ] } ], "prompt_number": 21 }, { "cell_type": "code", "collapsed": false, "input": [ "P(85,.1)" ], "language": "python", "metadata": {}, "outputs": [ { "ename": "TypeError", "evalue": "object of type 'float' has no len()", "output_type": "pyerr", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mP\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m85\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m.1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m\u001b[0m in \u001b[0;36mP\u001b[0;34m(T, x)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mP\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mz\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4\u001b[0m \u001b[0mz\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mPsat\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mspecies\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mz\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mTypeError\u001b[0m: object of type 'float' has no len()" ] } ], "prompt_number": 22 }, { "cell_type": "code", "collapsed": false, "input": [ "P(84" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example: Boiling Point of Ethylene Glycol/Water Mixtures" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Mixtures of Ethylene glycol and water are widely used for engine cooling in automobiles. The following chart [Source: Ethylene Glycol Product Guide, MEGlobal] shows the boiling point of ethylene glycol/water mixtures as a function of solution composition and pressure. Construct your own chart based on Raoult's law and Antoine's equations, and compare the results.\n", "\n", "" ] }, { "cell_type": "code", "collapsed": false, "input": [ "E = 'ethylene-glycol'\n", "W = 'water'\n", "\n", "MW = dict()\n", "MW[E] = 62.07\n", "MW[W] = 18.01528\n", "\n", "Psat = dict()\n", "Psat[E] = lambda T: 10**(8.0908 - 2088.9/(T + 203.5))\n", "\n", "Psat[W] = lambda T: \\\n", " (T <= 60) and 10**(8.10765 - 1750.286/(T + 235.0)) or \\\n", " (T > 60) and 10**(7.96681 - 1668.21/(T + 228.0))\n", "\n", "def Pbub(T,w):\n", " x = (w/MW[E])/(w/MW[E] + (1-w)/MW[W])\n", " return x*Psat[E](T) + (1-x)*Psat[W](T)\n", "\n", "from scipy.optimize import brentq as fzero\n", "def Tbub(P,w):\n", " return fzero(lambda T: Pbub(T,w)-P, 0, 300)\n", " \n", "w = linspace(0,1)\n", "figure(figsize=(9,6))\n", "plot(100*w,map(lambda w:Tbub(200,w),w))\n", "plot(100*w,map(lambda w:Tbub(760,w),w))\n", "plot(100*w,map(lambda w:Tbub(1520,w),w))\n", "legend(['200 mmHg','760 mmHg','1520 mmHg'],'best')\n", "\n", "tick_params(labelsize=14)\n", "xlim(0,100)\n", "ylim(50,300)\n", "xlabel('Ethylene Glycol, % by Weight in Water',fontsize=14)\n", "ylabel('Temperature, $^{\\circ}C$',fontsize=14)\n", "grid()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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qBDg66vW0OiVEvXv3xvDhwzFgwADs3r0bAJCbm6vXilDlw/54+WFM5IXxkBfG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\ndeWW+VR12cWF+6xUaumzQYhtoy6zeqKAiJDGp9dzY2Z0Om5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