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|
{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Chapter 6 : Vapour Pressure"
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Example 6.1 pageno : 133"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"\n",
"# variables \n",
"P = 500. #kPa liquid\n",
"SV = 0.2813 #m**3/kg wet steam\n",
"\n",
"# Calculation \n",
"Vsaturatedl = 1.093 * 10**-3 #m**3/kg\n",
"Vsaturatedv = 0.3747 #m**3/kg\n",
"\n",
"# let the fraction of vapour be y\n",
"#(1-y)*Vsaturatedl + y*Vsaturatedv = SV\n",
"#then we get, (1-y)*(1.093*10**-3) + y*(0.3747) = 0.2813\n",
"y = (SV - Vsaturatedl)/(Vsaturatedv - Vsaturatedl) \n",
"P1 = y * 100 \n",
"P2 = 100 - P1 \n",
"\n",
"# Result\n",
"print \"Percentage of Vapour = %.f %%\"%P1\n",
"print \"Percentage of Liquid = %.f %%\"%P2\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Percentage of Vapour = 75 %\n",
"Percentage of Liquid = 25 %\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Example 6.2 pageno : 134"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import math \n",
"\n",
"# Variables \n",
"T1 = 363. #K water\n",
"T2 = 373. #K water\n",
"P2s = 101.3 #kPa pressure\n",
"\n",
"# Calculation \n",
"J = 2275. * 18 #kJ/kmol\n",
"R = 8.314 #kJ/kmolK\n",
"#ln (P2s/P1s) = J * (1/T1 - 1/T2) / R\n",
"P1s = P2s/math.exp(J * (1/T1 - 1/T2) / R) \n",
"\n",
"# Result\n",
"print \"Vapour pressure of water at 363 K = %.2f kPa\"%P1s\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Vapour pressure of water at 363 K = 70.41 kPa\n"
]
}
],
"prompt_number": 3
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Example 6.3 pageno : 135"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import math \n",
"\n",
"# Variables \n",
"P1s = 194.9 #kPa acetone\n",
"P2s = 8.52 #kPa pressure\n",
"T1 = 353. #K acetone\n",
"T2 = 273. #K acetone\n",
"T3 = 300. #K dry air\n",
"Pair = 101.3 #kPa dry air\n",
"#math.log (P2s/P1s) = J * (1/T1 - 1/T2) / R\n",
"#let J / R = L\n",
"\n",
"# Calculation \n",
"L = math.log (P2s/P1s)/(1./T1 - 1/T2) \n",
"P3s = P1s * math.exp(L * (1./T1 - 1/T3)) \n",
"Ptotal = P3s + Pair #at saturation vapour pressure = partial pressure\n",
"\n",
"# Result \n",
"print \"(a)Final pressure of the mixture = %.2f kPa\"%Ptotal\n",
"MP = P3s * 100 / Ptotal \n",
"# mole percent = moles of acetone * 100 / total moles\n",
"#= Partial pressure of acetone * 100 / total Pressure\n",
"print \"(b)Mole percent of acetone in the final mixture = %.1f %%\"%MP\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(a)Final pressure of the mixture = 130.83 kPa\n",
"(b)Mole percent of acetone in the final mixture = 22.6 %\n"
]
}
],
"prompt_number": 5
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Example 6.4 pageno : 137"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import math \n",
"\n",
"\n",
"# Variables \n",
"A = 13.8587 # antone constants for n-heptane\n",
"B = 2911.32 \n",
"C = 56.56 \n",
"T1 = 325. #K\n",
"#Pressure at normal condition = 101.3kPa\n",
"P2 = 101.3 #kPa\n",
"\n",
"# Calculation \n",
"#Antoine equation - lnP = A - B / (T - C)\n",
"lnP = A - (B / (T1 - C)) \n",
"P1 = math.exp(lnP) \n",
"\n",
"# Result \n",
"print \"(a)Vapour pressure of n-heptane at 325K = %.2f kPa\"%P1\n",
"T2 = B/(A - math.log(P2)) + C \n",
"print \"(b)Normal boiling point of n-heptane = %.2f K\"%T2\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"(a)Vapour pressure of n-heptane at 325K = 20.36 kPa\n",
"(b)Normal boiling point of n-heptane = 371.62 K\n"
]
}
],
"prompt_number": 7
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Example 6.5 pageno : 140"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline\n",
"\n",
"from matplotlib.pyplot import *\n",
"\n",
"# variables \n",
"T = [273, 293, 313, 323, 333, 353, 373];\n",
"Ps = [0.61, 2.33, 7.37, 12.34, 19.90, 47.35, 101.3];\n",
"\n",
"# Calculation and Result\n",
"plot(T,Ps);\n",
"T1 = [273, 353]\n",
"Ps1 = [8.52, 194.9]\n",
"plot(T,Ps);\n",
"suptitle(\"Construction of the cox chart\")\n",
"xlabel(\"Temperature, K\")\n",
"ylabel(\"Pressure, kPa\")\n",
"show()\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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s+WSh1MMiIirGYIpCJqt+P5PcPHoxzM1M0czGCk0b1a/09/a8UhoR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\nEBGRVv8PkUOu8xTNWfQAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x27db050>"
]
}
],
"prompt_number": 2
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Example 6.6 page no : 143"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%matplotlib inline\n",
"\n",
"import math \n",
"from matplotlib.pyplot import *\n",
"\n",
"# Variables \n",
"Pswater1 = 6.08; #kPa \n",
"T1 = 313.; #K\n",
"\n",
"\n",
"# Calculation \n",
"#lnPs = 16.26205 - 3799.887/(T - 46.854)\n",
"Tb1 =3799.887/(16.26205 - math.log(Pswater1)) + 46.854;\n",
"print \"boiling point of water at 6.08kPa vapour pressure = %.2f K\"%Tb1\n",
"Pswater2 = 39.33; #kPa\n",
"T2 = 353.; #K\n",
"Tb2 =3799.887/(16.26205 - math.log(Pswater2)) + 46.854;\n",
"\n",
"# Result \n",
"print \"boiling point of water at 39.33 kPa vapour pressure = %.2f K\"%Tb2\n",
"Tb = [Tb1 ,Tb2];\n",
"T = [T1 ,T2];\n",
"plot(T,Tb);\n",
"suptitle(\"Equal pressure reference plot for sulphuric acid\")\n",
"xlabel(\"Boiling point of solution, K\")\n",
"ylabel(\"Boiling point of water, K\")\n",
"show()\n",
"T3 = 333.; #K\n",
"\n",
"#corresponding to T3 on x axis, on y we get\n",
"Tb3 = 329.; #K\n",
"Pswater3 = math.exp(16.26205 - 3799.887/(Tb3 - 46.854));\n",
"print \"Vapour pressure of solution at 333K %.2f kPa\"%Pswater3\n",
"\n",
"# deviation\n",
"deviation = .04/16.53 * 100\n",
"print \"%% deviation = %.2f %%\"%deviation"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n",
"boiling point of water at 6.08kPa vapour pressure = 309.69 K\n",
"boiling point of water at 39.33 kPa vapour pressure = 348.67 K\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",
"png": 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zmjdvTm5uLs7Ozjz55JNs3LjR1nEJIa7Thg3g46OtG7F/vyQJUX5K7FHceuut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\nIUSx/h89BNR1L4MHOAAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x46afd50>"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Vapour pressure of solution at 333K 16.35 kPa\n",
"% deviation = 0.24 %\n"
]
}
],
"prompt_number": 3
}
],
"metadata": {}
}
]
}
|
