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{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Chapter 4 : Minimization of Gibbs Free energy"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 4.1 Page: 67"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"import math \n",
"\n",
"T = 671.7 #[R] Equilibrium temperature\n",
"m_steam = 1. #[lbm] Condenmath.sing amount of the steam\n",
"delta_h_condensation = -970.3 #[Btu/lbm] Enthalpy change of the steam\n",
"delta_s_condensation = -1.4446 #[Btu/(lbm*R)] Entropy change of the steam\n",
"\n",
"delta_g_condensation = delta_h_condensation - T*delta_s_condensation #[Btu/lbm]\n",
"\n",
"\n",
"print \"Gibb''s free energy change of the steam is %0.1f Btu/lbm\"%(delta_g_condensation)\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Gibb''s free energy change of the steam is 0.0 Btu/lbm\n"
]
}
],
"prompt_number": 4
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"\n",
"Example 4.2 Page: 77\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"from numpy import *\n",
"from matplotlib.pyplot import *\n",
"import math \n",
"\n",
"%matplotlib inline\n",
"\n",
"g_g = 0.00 #[kJ/mol] \n",
"g_d = 2.90 #[kJ/mol]\n",
"\n",
"v_g = 5.31*10**(-1) #[kJ/(mol*kbar)]\n",
"v_d = 3.42*10**(-1) #[kJ/(mol*kbar)]\n",
"\n",
"\n",
"D_g = v_g #[J/(mol*Pa)] For graphite\n",
"D_d = v_d #[J/(mol*Pa)] For diamond\n",
"\n",
"\n",
"P = linspace(0,30,30).T\n",
"\n",
"plot(P, D_d*P+g_d )\n",
"plot(P,D_g*P+g_g )\n",
"xlabel(\"Pressure, P, kbar\");\n",
"ylabel(\"Gibb''s free energy per mol, g, kJ/mol\");\n",
"legend(['Diamond, slope = 0.342 (kJ/mol)/kbar','Graphite, slope = 0.532 (kJ/mol)/kbar']);\n",
"\n",
"show()\n",
"print \" Gibb's free energy-pressure diagram for graphite-diamond system at 25 degC is as shown in the graphic window. \"\n",
"\n",
"\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"WARNING: pylab import has clobbered these variables: ['draw_if_interactive']\n",
"`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
]
},
{
"metadata": {},
"output_type": "display_data",
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MFKQveDweJk6cCFtbW7Rt2xbt27cX3C/Rs2dP7N69G7Nnz4ampibat28v9eJIioqKOHPm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\nYUomACGEGKZkAhBCiGFKJgAhhBim/g/7Wr9ElF0y4wAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x2896e50>"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
" Gibb's free energy-pressure diagram for graphite-diamond system at 25 degC is as shown in the graphic window. \n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
" Example 4.3 Page: 80\n"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"from scipy.optimize import fsolve \n",
"import math \n",
"\n",
"\n",
"K = 4.52\n",
"\n",
"\n",
"def f(x_iso): \n",
"\t return x_iso/(1-x_iso)-K\n",
"x_iso = fsolve(f,0)\n",
"\n",
"print \" Mole fraction of isobumath.tane isomer in equilibrium is %0.2f\"%(x_iso)\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
" Mole fraction of isobumath.tane isomer in equilibrium is 0.82\n"
]
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [],
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
|