{ "metadata": { "name": "ch3", "signature": "sha256:3744cb249ffd9e10c950b9110990dfac9cd54ad63b8fe61f5671a88b4822fb4c" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Chapter 3 : Mass transfer coefficient and interphase mass transfer" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.1" ] }, { "cell_type": "code", "collapsed": false, "input": [ "\n", "# Variable Declaration \n", "v=6.; #velocity in m/s\n", "l=6.; #length in m\n", "pa1=10.; #pressure at 1 in atm\n", "pa2=0; #pressure at 2 in atm\n", "t=373.; # temperature in kelvin\n", "p=1.; #pressure of naphthalene in atm at 373kelvin\n", "D=5.15*10**-6; #diffusivity of naphthalene in C02 in m**2/s\n", "d=0.946; #density of air in kg/m**3\n", "u=.021*10**-3; #viscosity of air in Newton*s/m**2\n", "ID=0.075; #diameter in m\n", "\n", "# Calculation\n", "nre=(ID*v*d)/(u); #calc. of reynolds no.\n", "cf=2*0.023*(nre)**(-0.2); #friction factor\n", "nsc=(u)/(d*D); #calc of schmidt no.\n", "kc=(cf*v)/(2*(nsc)**(2./3));\n", "na=(kc*10**5*(pa1/760-0))/(8314*t); #difussion flux in kmol/m**2*s\n", "sub=na*2*3.14*(ID/2)*l; #rate of sublimation\n", "\n", "# Result\n", "print \"\\nrate of sublimation :%f *10**-6 kmol/s\\n\"%(sub/10**-6);\n", "#End" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "rate of sublimation :4.298312 *10**-6 kmol/s\n", "\n" ] } ], "prompt_number": 11 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.2" ] }, { "cell_type": "code", "collapsed": false, "input": [ " \n", "# Variable Declaration \n", "v=0.30; #velocity of parallelair in m/s\n", "t=300; #temperature of air in kelvin\n", "p=10.0**5/760; #pressure of air in pascal\n", "Dab=5.9*10**-4; #diffusivity of naphthalene in in air in m**2/s \n", "pa1=0.2*10**5/760; #pressure of air at 1 in pascal\n", "pa2=0; #pressure of air at 2 in pascal\n", "d=1.15; #density of air in kg/m**3\n", "u=0.0185*10**-3; #viscosity of air in Newton*s/m**2\n", "D=1.; #length in m\n", "a=1.; #area of plate in m**2\n", "\n", "# Calculation \n", "Nsc=u/(d*Dab); #schmidt no. calculation\n", "Nre=(D*v*d)/u; #reynolds no. calculation\n", " #flow is turbulent \n", "f=0.072*(Nre)**-.25; #friction factor using \"chilton colburn\" analogy\n", "k_c=(f*v)/(2*(Nsc)**.667); #mass transfer coefficient\n", "NA=k_c*(pa1-pa2)/(8314*300); #mass flux calc.\n", "sub=NA*a; #rate of sublimation in kmol/m**2*s\n", "\n", "# Result\n", "print \"\\nrate of sublimation :%f *10**-7 kmol/s\\n\"%(sub/10**-7)\n", "#End" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "rate of sublimation :1.077674 *10**-7 kmol/s\n", "\n" ] } ], "prompt_number": 12 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.3 " ] }, { "cell_type": "code", "collapsed": false, "input": [ " \n", "\n", "# a is CO2 and b is water\n", "p=2.; #total pressure at 1 in atm \n", "pa1=0.2*10**5; #pressure of CO2 at pt 1 in atm\n", "pa2=0; #pressure of CO2 at pt 2 is 0 since air is pure\n", "ya1=0.1; #mole fraction of CO2 at 1 is 0.2/2\n", "ya2=0; #mole fraction of CO2 at 2 is 0 since air is pure\n", "yb1=0.9; #mole fraction of water at 1 is (1-0.1)\n", "yb2=1.0; #mole fraction of water at 2 is 1.0 since total pressure has to be constant.\n", "k_y1=6.78*10**-5; #mass transfer coefficient in kmol/m**2*s*molefraction\n", "import math\n", "\n", "# Calculation \n", "yb_ln=(yb2-yb1)/(math.log(yb2/yb1)); #log mean is represented by yb_ln\n", "\n", "k_y=k_y1/yb_ln; \n", "\n", "# Result\n", "print \"\\nvalue of mass transfer coefficient k_y is:%f *10**-5 kmol/m**2*s*(molefractin)\"%(k_y/10.0**-5)\n", "k_g=k_y/p; #mass ttransfer coefficient in lmol/m**2*s*atm\n", "print \"\\nvalue mass transfer coefficient k_g is:%f *10**-5 kmol/m**2*s*(atm)\"%(k_g/10**-5)\n", "\n", "NA=k_y*(ya1-ya2); #mass flux in kmol/m**2*s\n", "print \"\\nvalue of rate of mass transfer :%f *10**-6 kmol/m**2*s\"%(NA/10.0**-6)\n", "#end" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "value of mass transfer coefficient k_y is:7.143443 *10**-5 kmol/m**2*s*(molefractin)\n", "\n", "value mass transfer coefficient k_g is:3.571721 *10**-5 kmol/m**2*s*(atm)\n", "\n", "value of rate of mass transfer :7.143443 *10**-6 kmol/m**2*s\n" ] } ], "prompt_number": 4 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.4" ] }, { "cell_type": "code", "collapsed": false, "input": [ " \n", "NA=7.5*10**-7; #mass flux in gmol/cm**2*s\n", "Dab=1.7*10**-5; #diffusivity if SO2 in water in cm**2/s\n", "c=1./18.02; #concentration is density/molecular weight in gmol/cm**2*s\n", "#SO2 is absorbed from air into water\n", "\n", "xa1=0.0025; #liquid phase mole fraction at 1\n", "xa2=0.0003; #liquid phase mole fraction at 2\n", " #NA=kc(Ca1-Ca2)=Dab*(Ca1-Ca2)/d\n", "\n", "# Calculation \n", "k_c=NA/(c*(xa1-xa2)); #k_c=Dab/d=NA/c(xa1-xa2)\n", "\n", "# Result \n", "print \"\\nmass transfer coefficient k_c is:%f cm/s\"%k_c\n", "\n", "d=Dab/k_c;\n", "print \"\\nfilm thickness d is :%f cm\"%d\n", "#end" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "mass transfer coefficient k_c is:0.006143 cm/s\n", "\n", "film thickness d is :0.002767 cm\n" ] } ], "prompt_number": 5 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.5 " ] }, { "cell_type": "code", "collapsed": false, "input": [ "\n", "Kg=2.72*10**-4; #overall gas phase mass transfer coefficient in kmol/m**2*S*atm\n", "r_gas=0.85*(1/Kg); #given that gas phase resisitance is 0.85 times overall resistance\n", "kg=1.0/r_gas; \n", "m=9.35*10**-3; #henry's law constant in atm*m**3/kmol\n", "kl=m/(1./Kg-1/kg); #liquid phase mass transfer coefficient in m/s\n", "print \"\\nthe value of liquid film coefficient kl : %f*10**-5 m/s\"%(kl/10**-5)\n", "print \"\\nthe value of gas film coefficient kg : %f*10**-5 m/s\"%(kg/10**-5);\n", "p=1.; #overall pressure in atm\n", "\n", " #NA=Kg(pag-pa*)=kg(pag-pai)=kl(Cai-Cal)\n", "# Calculation \n", "Yag=0.1; #molefraction of ammonia\n", "Cal=6.42*10**-2; #liquid phase concentration \n", "Pag=Yag*p; #pressure of ammonia\n", " \n", "#Pai=m*C_ai;\n", "#NA=kg(pag-pai)=kl(Cai-Cal)\n", " \n", "#Cai=poly([0],'Cai'); #calc. of conc. in gas phase\n", "x = 1.6588481 #x=roots((Pag-m*Cai)*(kg/kl)-(Cai-Cal));\n", "\n", "# Result \n", "print \"\\nthe value of interphase conc.cai :%f kmol/m**3\"%x\n", "Pai=m*x;\n", "print \"\\nthe value of interphase pressure pai is:%f atm\"%Pai\n", "#end" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "the value of liquid film coefficient kl : 1.695467*10**-5 m/s\n", "\n", "the value of gas film coefficient kg : 32.000000*10**-5 m/s\n", "\n", "the value of interphase conc.cai :1.658848 kmol/m**3\n", "\n", "the value of interphase pressure pai is:0.015510 atm\n" ] } ], "prompt_number": 13 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.6 " ] }, { "cell_type": "code", "collapsed": false, "input": [ " \n", "m=0.3672;\n", "t=.9;\n", " #Pai and Cai indicates interfacial pressure and conc.\n", " #Pal and Cal indicates bulk pressure and conc.\n", "Yag=0.15; #molefraction of ammonia\n", "Cal=0.147; #liquid phase concentration in kmol/m**3\n", "p=1; #overall pressure\n", "\n", "# Calculation \n", "Pag=Yag*p; #pressure of ammonia\n", "\n", " #Pai=m*C_ai;\n", " #kg/kl=(Cai-Cal)/(Pag-Pai);\n", " \n", "#Cai=poly([0],'Cai'); #calc. of conc. in gas phase\n", "x = 0.211954 #x=roots((Pag-m*Cai)*(t)-(Cai-Cal));\n", "\n", "# Result\n", "print \"\\nthe value of conc. of ammonia cai is :%f kmol/m**3\"%x\n", "Pai=m*x;\n", "print \"\\nthe value of interphase pressure Pai is :%f atm\"%Pai" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "the value of conc. of ammonia cai is :0.211954 kmol/m**3\n", "\n", "the value of interphase pressure Pai is :0.077830 atm\n" ] } ], "prompt_number": 14 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.7" ] }, { "cell_type": "code", "collapsed": false, "input": [ " \n", "# Variable Declaration \n", "D=.1;\n", "l=3; # l is length of bubble in cm\n", "a=3.14*D*l; # area in cm**2\n", "Ca_o=0.0001; #pure conc. of gas in g*mol/cc*atm\n", "Ca=0;\n", "NA=.482*10**-5; # molar rate of absorption in g*moles/s\n", " #Pa_o and Ca_o indicates pure pressure and conc.\n", "# Calculation \n", "kl=NA/(a*(Ca_o-Ca)); #mass transfer coefficient acc. to higbie's penetration theory\n", "Q=4; #volumetric flow rate in cc/s\n", "A=3.14*.1*.1/4; #area of flow\n", "v=Q/A; #velocity of flow in cm/s\n", "\n", "#timt t=bubble length/linear velocity;\n", "t=l/v;\n", "DAB=(kl**2)*3.14*t/4; #diffusivity in cm**2/s\n", "D_new=0.09; #revised diameter reduced to.09\n", "a_new=3.14*l*D_new; #revised area\n", "A_new=3.14*0.09*0.09/4; #revised flow area\n", "v_new=Q/A_new; #revised velocity\n", "\n", "# Result \n", "print \"\\nthe value of diffusivity of gas DAB is :%f cm/s\"%(DAB/10**-5)\n", "\n", "t_new=l/v_new; #revised time\n", "kl_new=2*(DAB/(3.14*0.0047))**0.5; #revised mass transfer coefficient \n", "NA_new=kl_new*a_new*(Ca_o-Ca); #revised molar rate absorption in g*moles/s\n", "print \"\\nthe value of NA_new is :%f*10**-6 kmol/m**3\"%(NA_new/10**-6)\n", "#end" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\n", "the value of diffusivity of gas DAB is :1.210021 cm/s\n", "\n", "the value of NA_new is :4.855188*10**-6 kmol/m**3\n" ] } ], "prompt_number": 8 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.8" ] }, { "cell_type": "code", "collapsed": false, "input": [ " \n", "# Variable Declaration \n", "Kg=7.36*10**-10;\n", "p=1.013*10**5;\n", "Ky=Kg*p;\n", "#resistance in gas phase is 0.45 of total resistance & .55 in liquid phase\n", "#(resistance in gas phase)r_gas=1/ky and (resistance in liq phase)r_liq=m'/kx\n", "r_gas=0.45*(1./Ky);\n", "ky=1./r_gas;\n", "r_liq=0.55*(1./Ky);\n", "print \"film based liq phase mass transfer coeff.ky is :%f \"%ky\n", "\n", "# Calculation\n", "m1=86.45;\n", "kx=m1/r_liq;\n", "yag=.1;\n", "xal=(.4/64)/((99.6/18)+(.4/64));\n", "print \"\\n film based gas phase mass transfer coeff.ky is :%f \"%kx\n", "#slope of the line gives -kx/ky=-70.61\n", "m2=m1; # since equilibrium line a straigth line m'=m''\n", "Kx=1/(1/kx+(1/(m2*ky))); #overall liquid phase mass transfer coefficient\n", "print \"\\n overall liq phase mass transfer coefficient Kx is :%f \"%Kx\n", "# equillibrium relation is given under\n", "p = [0.2,0.3,0.5,0.7];\n", "a = [29,46,83,119];\n", "i=0;\n", "x = [0,0,0,0]\n", "y = [0,0,0,0]\n", " #looping for calcullating mole fraction\n", "while (i<4):\n", " x[i]= (p[i]/64.)/(p[i]/64.+100/18);\n", " y[i]= a[i]/760.; #mole fraction plotted on y-axis\n", " i=i+1; \n", " #mole fraction plotted on x-axis\n", "%matplotlib inline\n", "from matplotlib.pyplot import *\n", "\n", "# Result\n", "plot(x,y);\n", "title(\"Fig.3.17,Example 8\");\n", "xlabel(\"X-- Concentration of SO2 in liquid phase, X(10**4)(molefraction)\");\n", "ylabel(\"Y-- Concentration of SO2 in gas phase, Y(molefraction)\");\n", "show()\n", " #from the graph we get these values\n", "yao=.083; #corresponding to the value of xao=0.001128\n", "xao=.00132; #corresponding to the value of yag=.1\n", "yai=.0925; #corresponding to the perpendicular dropped from the pt(.001128,0.1) \n", "xai=.00123;\n", " \n", " # flux based on overall coefficient\n", "NAo_gas=Ky*(yag-yao);\n", "NAo_liq=Kx*(xao-xal);\n", "print \"overall gas phase mass transfer flux -NAo_gas is :%f*10**-6 kmol/m**2*s \"%(NAo_gas/10**-6)\n", "print \"overall liq phase mass transfer flux -NAo_liq is :%f*10**-6 kmol/m**2*s \"%(NAo_liq/10**-6);\n", "\n", " # flux based on film coefficient \n", "NAf_gas=ky*(yag-yai);\n", "NAf_liq=kx*(xai-xal);\n", "print \"film based gas phase mass transfer flux-NAf_gas is :%f *10**-6 kmol/m**2*s\"%(NAf_gas/10**-6);\n", "print \"film based liq phase mass transfer flux-NAf_liq is :%f *10**-6 kmol/m**2*s\"%(NAf_liq/10**-6);\n", "#end" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "film based liq phase mass transfer coeff.ky is :0.000166 \n", "\n", " film based gas phase mass transfer coeff.ky is :0.011719 \n", "\n", " overall liq phase mass transfer coefficient Kx is :0.006445 \n", "Populating the interactive namespace from numpy and matplotlib" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "\n" ] }, { "output_type": "stream", "stream": "stderr", "text": [ "WARNING: pylab import has clobbered these variables: ['f']\n", "`%pylab --no-import-all` prevents importing * from pylab and numpy\n" ] }, { "metadata": {}, "output_type": "display_data", "png": "iVBORw0KGgoAAAANSUhEUgAAAZYAAAEgCAYAAACXa1X+AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nOMXCwcHBwTGv/Aec+J/DRRI5KQAAAABJRU5ErkJggg==\n", "text": [ "" ] }, { "output_type": "stream", "stream": "stdout", "text": [ "overall gas phase mass transfer flux -NAo_gas is :1.267466*10**-6 kmol/m**2*s \n", "overall liq phase mass transfer flux -NAo_liq is :1.235953*10**-6 kmol/m**2*s \n", "film based gas phase mass transfer flux-NAf_gas is :1.242613 *10**-6 kmol/m**2*s\n", "film based liq phase mass transfer flux-NAf_liq is :1.192479 *10**-6 kmol/m**2*s\n" ] } ], "prompt_number": 9 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Example 3.9" ] }, { "cell_type": "code", "collapsed": false, "input": [ " \n", "# Variable Declaration \n", "Cas=1.521*10**-7;\n", "v=1525; #velocity in m/s\n", "D=0.0516; #diffusivity in cm**2/s\n", "d=1.25*10**-3; #density of air in g/cm**3\n", "u=1.786*10**-4; #viscosity of air in n*s/m**2\n", "Dia=2.54; #diameter in cm\n", "\n", "# Calculation \n", "nre=(Dia*v*d)/(u); #calc. of reynolds no.\n", "cf=2*0.036*(nre)**(-0.25); #friction factor\n", "nsc=(u)/(d*D); #calc of schmidt no.\n", "kc=(cf*v)/(2*(nsc)**(2./3)); #cf/2=kc/uo*(sc)**2/3\n", "\n", "#rate of mass transfer=(cross sectional area)*(air velocity)*dc =(3.14*d**2/4)*v*dc -----1 eqn\n", " \n", "#flux for mass transfer from the surface=kc*(Cas-C)\n", "# rate of mass transfer=(flux)*mass transfer\n", "# =kc*(Cas-C)*3.14*dx*D------2 eqn\n", "# solving ----1 & -----2 we get\n", "# \n", "# (3.14*d**2/4)*v*dc=kc*(Cas-C)*3.14*dx*d;\n", "# dc/(Cas-C)=(kc*3.14*d*v)/(3.14*d**2/4)*dx\n", "# solving this we get\n", "# ln[(Cas-C)/(Cas-C_in)]=(kc*4*x)/(d*v)\n", "import math\n", "x=183; #upper limit of x\n", "C_in=0; #C=C_in=0;\n", "t=(kc*4*x)/(Dia*v); #variable to take out the exponential\n", "z=math.e**t;\n", "C_final=Cas-(z*(Cas-C_in)); #value of c_final in g*mol/cc;\n", "\n", "# Result\n", "print \"\\t conc. of acid at outlet :%f *10**-8 g*mol/cc\\n\"%(abs(C_final/10**-8))\n", "rate=(3.14*Dia**2/4)*v*(C_final-C_in);\n", "print \"\\trate of mass transfer :%f *10**-4 g*mol/s\\n\"%(abs(rate/10**-4));\n", "#End" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\t conc. of acid at outlet :7.709387 *10**-8 g*mol/cc\n", "\n", "\trate of mass transfer :5.954246 *10**-4 g*mol/s\n", "\n" ] } ], "prompt_number": 10 } ], "metadata": {} } ] }