1 files changed, 0 insertions, 865 deletions

diff --git a/Electrical_Circuit_Theory_And_Technology/chapter_17-checkpoint_3.ipynb b/Electrical_Circuit_Theory_And_Technology/chapter_17-checkpoint_3.ipynb
deleted file mode 100755
index 81f680ae..00000000
--- a/Electrical_Circuit_Theory_And_Technology/chapter_17-checkpoint_3.ipynb
+++ /dev/null
@@ -1,865 +0,0 @@
-{

- "metadata": {

-  "name": "",

-  "signature": "sha256:ca1c7401f018e12f4456a542a7349262c450bbcce53eee5003079be7be1331af"

- },

- "nbformat": 3,

- "nbformat_minor": 0,

- "worksheets": [

-  {

-   "cells": [

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h1>Chapter 17: D.c. transients</h1>"

-     ]

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 1, page no. 262</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#from pylab import *\n",

-      "%pylab inline\n",

-      "#initializing  the  variables:\n",

-      "C  =  15E-6;#  in  Farads\n",

-      "R  =  47000;#  in  ohms\n",

-      "V  =  120;#  in  Volts\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  R*C\n",

-      "t1  =  tou\n",

-      "Vctou  =  V*(1-math.e**(-1*t1/tou))\n",

-      "Vct  =  V/2\n",

-      "t0  =  -1*tou*math.log(1  -  Vct/V)\n",

-      "t=[]\n",

-      "Vc=[]\n",

-      "I  =  V/R\n",

-      "for h in range(50):\n",

-      "    t.append((h-1)/10)\n",

-      "    k=(h-1)/10\n",

-      "    Vc.append(V*(1 - math.e**(-1*k/tou)))\n",

-      "fig  = plt.figure()\n",

-      "ax = fig.add_subplot(1, 1, 1)\n",

-      "ax.plot(t,Vc,'-')\n",

-      "#plot(t,Vc,'-')\n",

-      "xlabel('time(sec)')\n",

-      "ylabel('Volts(V)')\n",

-      "show()\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)the  capacitor  voltage  at  a  time  equal  to  one  time  constant  =  \",round(Vctou,2),\"  V\"\n",

-      "print  \"\\n  (b)the  time  for  the  capacitor  voltage  to  reach  one  half  of  its  steady  state  value  =  \",round(t0,5),\" secs\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "Populating the interactive namespace from numpy and matplotlib\n"

-       ]

-      },

-      {

-       "metadata": {},

-       "output_type": "display_data",

-       "png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEPCAYAAACtCNj2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nD8/iLwbt6hd+AAAAAElFTkSuQmCC\n",

-       "text": [

-        "<matplotlib.figure.Figure at 0x34660b8>"

-       ]

-      },

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)the  capacitor  voltage  at  a  time  equal  to  one  time  constant  =   75.85   V\n",

-        "\n",

-        "  (b)the  time  for  the  capacitor  voltage  to  reach  one  half  of  its  steady  state  value  =   0.48867  secs\n"

-       ]

-      }

-     ],

-     "prompt_number": 1

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 2, page no. 263</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#from pylab import *\n",

-      "%pylab inline\n",

-      "#initializing  the  variables:\n",

-      "C  =  4E-6;#  in  Farads\n",

-      "R  =  220000;#  in  ohms\n",

-      "V  =  24;#  in  Volts\n",

-      "t1  =  1.5;#  in  secs\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  R*C\n",

-      "I  =  V/R\n",

-      "\n",

-      "t=[]\n",

-      "Vc=[]\n",

-      "for h in range(50):\n",

-      "    t.append((h-1)/10)\n",

-      "    k=(h-1)/10\n",

-      "    Vc.append(V*math.e**(-1*k/tou))\n",

-      "#plt.figsize(10,8)\n",

-      "fig  = plt.figure()\n",

-      "#canvas = fc(fig)\n",

-      "ax = fig.add_subplot(1, 1, 1)\n",

-      "ax.plot(t,Vc,'-')\n",

-      "#plot(t,Vc,'-')\n",

-      "xlabel('time(sec)')\n",

-      "ylabel('P.D across Capacitor(V)')\n",

-      "show()\n",

-      "\n",

-      "t=[]\n",

-      "VR=[]\n",

-      "for h in range(50):\n",

-      "    t.append((h-1)/10)\n",

-      "    k=(h-1)/10\n",

-      "    VR.append(V*(1 - math.e**(-1*k/tou)))\n",

-      "fig  = plt.figure()\n",

-      "#canvas = fc(fig)\n",

-      "ax = fig.add_subplot(1, 1, 1)\n",

-      "ax.plot(t,VR,'-')\n",

-      "#plot(t,VR,'-*')\n",

-      "xlabel('time(sec)')\n",

-      "ylabel('P.D across Resistor(V)')\n",

-      "show()\n",

-      "\n",

-      "t=[]\n",

-      "i=[]\n",

-      "for h in range(50):\n",

-      "    t.append((h-1)/10)\n",

-      "    k=(h-1)/10\n",

-      "    i.append(I*math.e**(-1*k/tou))\n",

-      "fig  = plt.figure()\n",

-      "#canvas = fc(fig)\n",

-      "ax = fig.add_subplot(1, 1, 1)\n",

-      "ax.plot(t,i,'-')\n",

-      "#plot(t,i,'*-')\n",

-      "xlabel('time(sec)')\n",

-      "ylabel('current(A)')\n",

-      "show()\n",

-      "\n",

-      "Vct1  =  V*math.e**(-1*t1/tou)\n",

-      "VRt1  =  V*math.e**(-1*t1/tou)\n",

-      "it1   =  I*math.e**(-1*t1/tou)\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  the  value  of  capacitor  voltage  is  \",round(Vct1,1),\"  V,  resistor  voltage  is  \",round(VRt1,1),\"  V,\"\n",

-      "print  \"current  is  \",round(0.02,2),\"  mA  at  one  and  a  half  seconds  after  discharge  has  started.\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "Populating the interactive namespace from numpy and matplotlib\n"

-       ]

-      },

-      {

-       "metadata": {},

-       "output_type": "display_data",

-       "png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEPCAYAAACukxSbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nR/4/BVHYi+QDH9kAAAAASUVORK5CYII=\n",

-       "text": [

-        "<matplotlib.figure.Figure at 0x77c6e10>"

-       ]

-      },

-      {

-       "metadata": {},

-       "output_type": "display_data",

-       "png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAEPCAYAAACqZsSmAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nD/p/wQuHfYdHfM4AAAAASUVORK5CYII=\n",

-       "text": [

-        "<matplotlib.figure.Figure at 0x7b9e4a8>"

-       ]

-      },

-      {

-       "metadata": {},

-       "output_type": "display_data",

-       "png": "iVBORw0KGgoAAAANSUhEUgAAAZoAAAEPCAYAAAB7rQKTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nqer/AUdcZmZ6XUFsAAAAAElFTkSuQmCC\n",

-       "text": [

-        "<matplotlib.figure.Figure at 0x7bac898>"

-       ]

-      },

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  the  value  of  capacitor  voltage  is   4.4   V,  resistor  voltage  is   4.4   V,\n",

-        "current  is   0.02   mA  at  one  and  a  half  seconds  after  discharge  has  started.\n"

-       ]

-      }

-     ],

-     "prompt_number": 8

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 3, page no. 265</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "C  =  20E-6;#  in  Farads\n",

-      "R  =  50000;#  in  ohms\n",

-      "V  =  20;#  in  Volts\n",

-      "t1  =  1;#  in  secs\n",

-      "t2  =  2;#  in  secs\n",

-      "VRt  =  15;#  in  Volts\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  R*C\n",

-      "I  =  V/R\n",

-      "Vct1  =  V*(1-math.e**(-1*t2/tou))\n",

-      "t3  =  -1*tou*math.log(VRt/V)\n",

-      "it1  =  I*math.e**(-1*t1/tou)\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)initial  value  of  the  current  flowing  is  \",round(I*1000,1),\"mA\"\n",

-      "print  \"\\n  (b)time  constant  of  the  circuit  \",round(tou,2),\"  Sec\"\n",

-      "print  \"\\n  (c)the  value  of  the  current  one  second  after  connection,  \",round((it1/1E-3),3),\"  mA\"\n",

-      "print  \"\\n  (d)the  value  of  the  capacitor  voltage  two  seconds  after  connection  \",round(Vct1,1),\"  V\"\n",

-      "print  \"\\n  (e)the  time  after  connection  when  the  resistor  voltage  is  15  V  is  \",round(t3,3),\"  sec\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)initial  value  of  the  current  flowing  is   0.4 mA\n",

-        "\n",

-        "  (b)time  constant  of  the  circuit   1.0   Sec\n",

-        "\n",

-        "  (c)the  value  of  the  current  one  second  after  connection,   0.147   mA\n",

-        "\n",

-        "  (d)the  value  of  the  capacitor  voltage  two  seconds  after  connection   17.3   V\n",

-        "\n",

-        "  (e)the  time  after  connection  when  the  resistor  voltage  is  15  V  is   0.288   sec\n"

-       ]

-      }

-     ],

-     "prompt_number": 9

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 17.4, page no. 266</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "C  =  0.5E-6;#  in  Farads\n",

-      "V  =  10;#  in  Volts\n",

-      "tou  =  0.012;#  in  secs\n",

-      "t1  =  0.007;#  in  secs\n",

-      "\n",

-      "#calculation:\n",

-      "R  =  tou/C\n",

-      "Vc  =  V*(1-math.e**(-1*t1/tou))\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)value  of  the  resistor  is  \",R,\"  ohm\"\n",

-      "print  \"\\n  (b)capacitor  voltage  is  \",round(Vc,2),\"  V\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)value  of  the  resistor  is   24000.0   ohm\n",

-        "\n",

-        "  (b)capacitor  voltage  is   4.42   V\n"

-       ]

-      }

-     ],

-     "prompt_number": 10

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 5, page no. 267</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "R  =  50000;#  in  ohms\n",

-      "V  =  100;#  in  Volts\n",

-      "Vc1  =  20;#  in  Volts\n",

-      "tou  =  0.8;#  in  secs\n",

-      "t1  =  0.5;#  in  secs\n",

-      "t2  =  1;#  in  secs\n",

-      "\n",

-      "#calculation:\n",

-      "C  =  tou/R\n",

-      "t  =  -1*tou*math.log(Vc1/V)\n",

-      "I  =  V/R\n",

-      "it1  =  I*math.e**(-1*t1/tou)\n",

-      "Vc  =  V*math.e**(-1*t2/tou)\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)the  value  of  the  capacitor  is  \",round((C/1E-6),2),\"uF\"\n",

-      "print  \"\\n  (b)the  time  for  the  capacitor  voltage  to  fall  to  20  V  is  \",round(t,2),\"  sec\"\n",

-      "print  \"\\n  (c)the  current  flowing  when  the  capacitor  has  been  discharging  for  0.5  s  is  \",round(it1*1000,2),\"mA\"\n",

-      "print  \"\\n  (d)voltage  drop  across  resistor  when  the  capacitor  has  been  discharging  for  one  second  is  \",round(Vc,1),\"  V\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)the  value  of  the  capacitor  is   16.0 uF\n",

-        "\n",

-        "  (b)the  time  for  the  capacitor  voltage  to  fall  to  20  V  is   1.29   sec\n",

-        "\n",

-        "  (c)the  current  flowing  when  the  capacitor  has  been  discharging  for  0.5  s  is   1.07 mA\n",

-        "\n",

-        "  (d)voltage  drop  across  resistor  when  the  capacitor  has  been  discharging  for  one  second  is   28.7   V\n"

-       ]

-      }

-     ],

-     "prompt_number": 11

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 6 page no. 268</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "C  =  0.1E-6;#  in  Farads\n",

-      "R  =  4000;#  in  ohms\n",

-      "V  =  200;#  in  Volts\n",

-      "Vc1  =  2;#  in  Volts\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  R*C\n",

-      "I  =  V/R\n",

-      "t  =  -1*tou*math.log(Vc1/V)\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \" \\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)  initial  discharge  current  is  \",round(I,2),\"  A\"\n",

-      "print  \"\\n  (b)Time  constant  tou  is  \",round(tou,5),\"  sec\"\n",

-      "print  \"\\n  (c)min.  time  required  for voltage  across capacitor  to  fall  to  less  than  2  V  is  \",round(t*1000,0),\"  msec\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        " \n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)  initial  discharge  current  is   0.05   A\n",

-        "\n",

-        "  (b)Time  constant  tou  is   0.0004   sec\n",

-        "\n",

-        "  (c)min.  time  required  for voltage  across capacitor  to  fall  to  less  than  2  V  is   2.0   msec\n"

-       ]

-      }

-     ],

-     "prompt_number": 12

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 7, page no. 270</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "from pylab import *\n",

-      "#initializing  the  variables:\n",

-      "L  =  0.1;#  in  Henry\n",

-      "R  =  20;#  in  ohms\n",

-      "V  =  60;#  in  Volts\n",

-      "i2  =  1.5;#  in  Amperes\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  L/R\n",

-      "t1  =  2*tou\n",

-      "\n",

-      "t=[]\n",

-      "i=[]\n",

-      "I  =  V/R\n",

-      "for h in range(250):\n",

-      "    t.append((h-1)/10000)\n",

-      "    k=(h-1)/10000\n",

-      "    i.append(I*(1  -  math.e**(-1*k/tou)))\n",

-      "plot(t,i,'-')\n",

-      "xlabel('time(sec)')\n",

-      "ylabel('current(A)')\n",

-      "show()\n",

-      "i1  =  I*(1  -  math.e**(-1*t1/tou))\n",

-      "t2  =  -1*tou*math.log(1  -  i2/I)\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \" \\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)  the  value  of  current  flowing  at  a  time  equal  to  two  time  constants  is  \",round(i1,2),\"  A\"\n",

-      "print  \"\\n  (b)the  time  for  the  current  to  grow  to  1.5  A  is  \",round(t2,5),\"  sec\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "metadata": {},

-       "output_type": "display_data",

-       "png": "iVBORw0KGgoAAAANSUhEUgAAAZQAAAEPCAYAAABlZDIgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUYpOSazjAAAAAElFTkSuQmCC\n",

-       "text": [

-        "<matplotlib.figure.Figure at 0x7b9d748>"

-       ]

-      },

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        " \n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)  the  value  of  current  flowing  at  a  time  equal  to  two  time  constants  is   2.59   A\n",

-        "\n",

-        "  (b)the  time  for  the  current  to  grow  to  1.5  A  is   0.00347   sec\n"

-       ]

-      }

-     ],

-     "prompt_number": 13

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 8, page no. 271</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "L  =  0.04;#  in  Henry\n",

-      "R  =  10;#  in  ohms\n",

-      "V  =  120;#  in  Volts\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  L/R\n",

-      "t1  =  tou\n",

-      "I  =  V/R\n",

-      "i1  =  I*(1  -  math.e**(-1*t1/tou))\n",

-      "i2  =  0.01*I\n",

-      "t2  =  -1*tou*(-5)\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)  the  final  value  of  current  is  \",round(I,2),\"  A\"\n",

-      "print  \"\\n  (b)time  constant  of  the  circuit  is  \",round(tou*1000,2),\"msec\"\n",

-      "print  \"\\n  (c)  value  of  current  after  a  time  equal  to  the  time  constant  is  \",round(i1,2),\"  A\"\n",

-      "print  \"\\n  (d)expected  time  for  current  to  rise  to  within  0.01  times  of  its  final  value  is  \",round(t2*1000,2),\"msec\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)  the  final  value  of  current  is   12.0   A\n",

-        "\n",

-        "  (b)time  constant  of  the  circuit  is   4.0 msec\n",

-        "\n",

-        "  (c)  value  of  current  after  a  time  equal  to  the  time  constant  is   7.59   A\n",

-        "\n",

-        "  (d)expected  time  for  current  to  rise  to  within  0.01  times  of  its  final  value  is   20.0 msec\n"

-       ]

-      }

-     ],

-     "prompt_number": 14

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 9, page no. 271</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "L  =  3;#  in  Henry\n",

-      "R  =  15;#  in  ohms\n",

-      "V  =  120;#  in  Volts\n",

-      "t1  =  0.1;#  in  secs\n",

-      "t3  =  0.3;#  in  secs\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  L/R\n",

-      "I  =  V/R\n",

-      "i2  =  0.85*I;#  in  amperes\n",

-      "VL  =  V*math.e**(-1*t1/tou)\n",

-      "t2  =  -1*tou*math.log(1  -  (i2/I))\n",

-      "i3  =  I*(1  -  math.e**(-1*t3/tou))\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Results  \\n\\n\"\n",

-      "print  \"\\n  (a)  steady  state  value  of  current  is  \",round(I,2),\"  A\"\n",

-      "print  \"\\n  (b)time  constant  of  the  circuit  is  \",round(tou,2),\"  sec\"\n",

-      "print  \"\\n  (c)value  of  the  induced  e.m.f.  after  0.1  s  is  \",round(VL,2),\"  V\"\n",

-      "print  \"\\n  (d)  time  for  the  current  to  rise  to  0.85  times  of  its  final  values  is  \",round(t2,2),\"  A\"\n",

-      "print  \"\\n  (e)value  of  the  current  after  0.3  s  is  \",round(i3,2),\"  A\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Results  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)  steady  state  value  of  current  is   8.0   A\n",

-        "\n",

-        "  (b)time  constant  of  the  circuit  is   0.2   sec\n",

-        "\n",

-        "  (c)value  of  the  induced  e.m.f.  after  0.1  s  is   72.78   V\n",

-        "\n",

-        "  (d)  time  for  the  current  to  rise  to  0.85  times  of  its  final  values  is   0.38   A\n",

-        "\n",

-        "  (e)value  of  the  current  after  0.3  s  is   6.21   A\n"

-       ]

-      }

-     ],

-     "prompt_number": 15

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 10, page no. 273</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "from pylab import *\n",

-      "#initializing  the  variables:\n",

-      "R  =  15;#  in  ohms\n",

-      "V  =  110;#  in  Volts\n",

-      "tou  =  2;#  in  secs\n",

-      "t1  = 3;#  in  secs\n",

-      "i2  = 5;#  in  amperes\n",

-      "\n",

-      "#calculation:\n",

-      "L  =  tou*R\n",

-      "I  =  V/R\n",

-      "\n",

-      "t=[]\n",

-      "i=[]\n",

-      "for h in range(100):\n",

-      "    t.append((h-1)/10)\n",

-      "    k=(h-1)/10\n",

-      "    i.append(I*math.e**(-1*k/tou))\n",

-      "plot(t,i,'-')\n",

-      "xlabel('time(sec)')\n",

-      "ylabel('current(A)')\n",

-      "show()\n",

-      "i1  =  I*(math.e**(-1*t1/tou))\n",

-      "t2  =  -1*tou*log((i2/I))\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \" \\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)the  current  flowing  in  the  winding  3  s  after  being  shorted-out  is  \",round(i1,2),\"  A\"\n",

-      "print  \"\\n  (b)the  time  for  the  current  to  decay  to  5  A  is  \",round(t2,2),\"  sec\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "metadata": {},

-       "output_type": "display_data",

-       "png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEPCAYAAABMTw/iAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/T/TLOQZYjmougAAAABJRU5ErkJggg==\n",

-       "text": [

-        "<matplotlib.figure.Figure at 0x77abf28>"

-       ]

-      },

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        " \n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)the  current  flowing  in  the  winding  3  s  after  being  shorted-out  is   1.64   A\n",

-        "\n",

-        "  (b)the  time  for  the  current  to  decay  to  5  A  is   0.77   sec\n"

-       ]

-      }

-     ],

-     "prompt_number": 16

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 11, page no. 273</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "L  =  6;#  in  Henry\n",

-      "r  =  10;#  in  ohms\n",

-      "V  =  120;#  in  Volts\n",

-      "tou  =  0.3;#  in  secs\n",

-      "t1  =  1;#  in  secs\n",

-      "\n",

-      "#calculation:\n",

-      "R  =  (L/tou)  -  r\n",

-      "Rt  =  R  +  r\n",

-      "I  =  V/Rt\n",

-      "i2  =  0.1*I\n",

-      "i1  =  I*(math.e**(-1*t1/tou))\n",

-      "t2  =  -1*tou*math.log((i2/I))\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"  \\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  (a)  resistance  of  the  coil  is  \",round(R,2),\"  ohm\"\n",

-      "print  \"\\n  (b)  current  flowing  in  circuit  one  second  after  the  shorting  link  has  been  placed  is  \",round(i1,2),\"  A\"\n",

-      "print  \"\\n  (c)the  time  for  the  current  to  decay  to  0.1  times  of  initial  value  is  \",round(t2,2),\"  sec\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "  \n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  (a)  resistance  of  the  coil  is   10.0   ohm\n",

-        "\n",

-        "  (b)  current  flowing  in  circuit  one  second  after  the  shorting  link  has  been  placed  is   0.21   A\n",

-        "\n",

-        "  (c)the  time  for  the  current  to  decay  to  0.1  times  of  initial  value  is   0.69   sec\n"

-       ]

-      }

-     ],

-     "prompt_number": 17

-    },

-    {

-     "cell_type": "markdown",

-     "metadata": {},

-     "source": [

-      "<h3>Example 12, page no. 274</h3>"

-     ]

-    },

-    {

-     "cell_type": "code",

-     "collapsed": false,

-     "input": [

-      "\n",

-      "from __future__ import division\n",

-      "import math\n",

-      "#initializing  the  variables:\n",

-      "L  =  0.2;#  in  Henry\n",

-      "R  =  1000;#  in  ohms\n",

-      "V  =  24;#  in  Volts\n",

-      "t1  =  1*L/R;#  in  secs\n",

-      "t2  =  2*L/R;#  in  secs\n",

-      "t3  =  3*L/R;#  in  secs\n",

-      "\n",

-      "#calculation:\n",

-      "tou  =  L/R\n",

-      "I  =  V/R\n",

-      "i1  =  I*(1  -  math.e**(-1*t1/tou))\n",

-      "VL  =  V*(math.e**(-1*t2/tou))\n",

-      "VR  =  V*(1  -  math.e**(-1*t3/tou))\n",

-      "\n",

-      "\n",

-      "#Results\n",

-      "print  \"\\n\\n  Result  \\n\\n\"\n",

-      "print  \"\\n  time  constant  of  circuit  is  \",round(tou*1000,6),\"msec, and steady-state  value  of current  is  \",round(I*1000,2),\"mA\"\n",

-      "print  \"\\n  (a)  urrent  flowing  in  the  circuit  at  a  time  equal  to  one  time  constant  is  \",round(i1*1000,2),\"mA\"\n",

-      "print  \"\\n  (b)  voltage  drop  across  the  inductor  at  a  time  equal  to  two  time  constants  is  \",round(VL,3),\"  V\"\n",

-      "print  \"\\n  (c)the  voltage  drop  across  the  resistor  after  a  time  equal  to  three  time  constants  is  \",round(VR,2),\"  V\""

-     ],

-     "language": "python",

-     "metadata": {},

-     "outputs": [

-      {

-       "output_type": "stream",

-       "stream": "stdout",

-       "text": [

-        "\n",

-        "\n",

-        "  Result  \n",

-        "\n",

-        "\n",

-        "\n",

-        "  time  constant  of  circuit  is   0.2 msec, and steady-state  value  of current  is   24.0 mA\n",

-        "\n",

-        "  (a)  urrent  flowing  in  the  circuit  at  a  time  equal  to  one  time  constant  is   15.17 mA\n",

-        "\n",

-        "  (b)  voltage  drop  across  the  inductor  at  a  time  equal  to  two  time  constants  is   3.248   V\n",

-        "\n",

-        "  (c)the  voltage  drop  across  the  resistor  after  a  time  equal  to  three  time  constants  is   22.81   V\n"

-       ]

-      }

-     ],

-     "prompt_number": 18

-    }

-   ],

-   "metadata": {}

-  }

- ]

-}
\ No newline at end of file