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  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Chapter 6 : pumping of liquids\n"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "example 6.1 page no : 115"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "\n",
      "import math \n",
      "from numpy import *\n",
      "\n",
      "# Initialization of Variable\n",
      "atp = 100.2*1000.\n",
      "g = 9.81\n",
      "rho_w = 996.\n",
      "rho_toluene = 867.\n",
      "vap_pre_toluene = 4.535*1000\n",
      "viscosity_toluene = 5.26/10000\n",
      "\n",
      "#calculation\n",
      "m = (atp-vap_pre_toluene)/rho_toluene/g\n",
      "print \"Max. height of toluene supported by atm. pressure (in m): %.4f\"%m\n",
      "\n",
      "#part(1)\n",
      "hopw = 0.650           #head of pump in terms of water\n",
      "hopt = hopw*rho_w/rho_toluene           #head of pump in terms of toluene\n",
      "Q = 1.8*10**-3                          #flow in m**3/s\n",
      "d = 2.3*10**-2                          #diameter of pipe\n",
      "pi = 3.14127\n",
      "\n",
      "#u = 4*Q/pi/d**2\n",
      "#substituting this for reynolds no.\n",
      "Re = 4*Q*rho_toluene/pi/d/viscosity_toluene         #reynolds no.\n",
      "print \"reynolds no : %.4f\"%Re\n",
      "phi = 0.0396*Re**-0.25\n",
      "\n",
      "\n",
      "#since both LHS and RHS are function of x(max. ht. ab. toluene) \n",
      "#we define a new variable to solve the eqn\n",
      "#y = (atp/rho_toluene/g)-(vap_pre_toluene/rho_toluene/g)-(4*phi*16*Q**2*x/pi**2/d**5/g)-hopt\n",
      "#y = x \n",
      "#these are two equations\n",
      "\n",
      "b = array([0,((atp/rho_toluene/g)-(vap_pre_toluene/rho_toluene/g)-hopt)])\n",
      "A = array([[1, -1],[1, 4*phi*16*Q**2/pi**2/d**5/g]])\n",
      "x = linalg.solve(A ,b)\n",
      "print \"the maximum height above toulene in the tank the pump can be \\\n",
      "located without risk while flow rate is 1.80dm**3/s (in m): %.4f\"%x[0]\n",
      "\n",
      "#solution of part(2)\n",
      "l = 9.          #length \n",
      "u = math.sqrt(((atp/rho_toluene/g)-(vap_pre_toluene/rho_toluene/g)-hopt-l)*d*g/4/phi/l)     #fluid velocity in pipes\n",
      "Q = pi*d**2*u/4\n",
      "print \"Maximum delivery rate if pump is located 9m above toluene tank(in m**3/s) %.4f\"%Q\n",
      "\n",
      "#solution of part(3)\n",
      "#clubing d together we get\n",
      "Q = 1.8/1000.\n",
      "a = (atp/rho_toluene/g)-(vap_pre_toluene/rho_toluene/g)-hopt-l\n",
      "b = a*pi**2*g/4./9./16./Q**2/0.0396/(4*Q*rho_toluene/pi/viscosity_toluene)**-0.25\n",
      "d = (1./b)**(1./4.75)\n",
      "print \"minimum smooth diameter of suction pipe which will have flow \\\n",
      "rate as (1.8 dm**3/s) for pump kept at 9 m high (in m):\",d\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Max. height of toluene supported by atm. pressure (in m): 11.2477\n",
        "reynolds no : 164260.3512\n",
        "the maximum height above toulene in the tank the pump can be located without risk while flow rate is 1.80dm**3/s (in m): 6.3463\n",
        "Maximum delivery rate if pump is located 9m above toluene tank(in m**3/s) 0.0009\n",
        "minimum smooth diameter of suction pipe which will have flow rate as (1.8 dm**3/s) for pump kept at 9 m high (in m): 0.0306728431855\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "example 6.2 pageno : 118"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "\n",
      "import math \n",
      "# Initialization of Variable\n",
      "Q1 = 24.8/1000          #flow in pump 1\n",
      "d1 = 11.8/100           #diameter of impeller 1\n",
      "H1 = 14.7               #head of pump 1\n",
      "N1 = 1450.              #frequency of motor 1\n",
      "Q2 = 48/1000.           #flow in pump 2\n",
      "\n",
      "#calculation\n",
      "H2 = 1.15*H1            #head of pump 2\n",
      "specific_speed = N1*Q1**0.5/H1**0.75\n",
      "N2 = specific_speed*H2**0.75/Q2**0.5        #frequency of motor 2\n",
      "print \"frequency of motor 2 in rpm %.4f\"%N2 \n",
      "d2 = math.sqrt(N2**2*H1/H2/N1**2/d1**2)\n",
      "print  \"diametr of impeller 2 (in m) %.4f\"%(1/d2 )\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "frequency of motor 2 in rpm 1157.4350\n",
        "diametr of impeller 2 (in m) 0.1585\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "example 6.3 page no : 120"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "\n",
      "from matplotlib.pyplot import *\n",
      "import math \n",
      "%matplotlib inline\n",
      "\n",
      "# Initialization of Variable\n",
      "Q = [0, 0.01, 0.02, 0.03 ,0.04, 0.05]           #discharge\n",
      "effi_hyd = [65.4 ,71, 71.9, 67.7, 57.5, 39.2]\n",
      "effi_over = [0 ,36.1, 56.0, 61.0, 54.1, 37.0]\n",
      "H_sys = [0 ,0, 0, 0, 0, 0]\n",
      "d = 0.114           #diameter of pipe\n",
      "d_o = 0.096         #diameter of impeller\n",
      "h = 8.75            #elevation\n",
      "g = 9.81            #acc. of gravity\n",
      "rho = 999.          #denisity of water\n",
      "l = 60.             #length of pipe\n",
      "theta = 0.611       #angle in radians\n",
      "B = 0.0125          #width of blades\n",
      "pi = 3.1412\n",
      "mu = 1.109/1000     #viscosity of water\n",
      "omega = 2*pi*1750/60.\n",
      "H_theor = []\n",
      "# calculation\n",
      "for i in range(6):\n",
      "    if i == 0:\n",
      "        H_sys[i] = h\n",
      "    else:\n",
      "        H_sys[i] = h+8.*Q[i]**2./pi**2/d**4/g*(1+8*l*0.0396/d*(4*rho*Q[i]/pi/d/mu)**-0.25)\n",
      "    H_theor.append(omega**2*d_o**2/g-omega*Q[i]/2/pi/g/B/math.tan(theta))\n",
      "\n",
      "#H_theor = omega**2*d_o**2/g-omega*Q/2/pi/g/B/math.tan(theta)\n",
      "#print (H_sys\"head of system (in m)\")\n",
      "#print (H_theor)\n",
      "H_eff = [0,0,0,0,0,0]\n",
      "for i in range(6):\n",
      "    H_eff[i] = effi_hyd[i]*H_theor[i]/100.\n",
      "\n",
      "#print (H_eff)\n",
      "plot(Q,effi_hyd, 'r--d')\n",
      "plot(Q,effi_over, 'g')\n",
      "plot(Q,H_eff,'k')\n",
      "plot(Q,H_theor)\n",
      "plot(Q,H_sys ,'c-')\n",
      "title('system characteritics')\n",
      "ylabel('Head(m)or Efficiency(%)')\n",
      "xlabel('volumetric flow rate(m**3/s)')\n",
      "show()\n",
      "\n",
      "#calculation of power\n",
      "#at intersecting point using datatrip b/w H_sys &H_eff\n",
      "Q = 0.0336\n",
      "effi_over = 59.9\n",
      "H_eff = 13.10\n",
      "P = H_eff*rho*g*Q/effi_over/10\n",
      "print \"Power required to pump fluid at this rate(in KW): %.4f\"%P \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', 'pi', 'new_figure_manager']\n",
        "`%pylab --no-import-all` prevents importing * from pylab and numpy\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
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7gVUvPH06oKkJDB4MHDsGvPeeXGsl0lVri4ExhoyMDPHzjIwMCMqds52ov//d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\nw+PNmzdo3bp1jeFhYWEBTU31ue61Oqp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hbeS6VgQjce8rIrW6okY0VkikQmq1XmrEVm1M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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x258a6d0>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Power required to pump fluid at this rate(in KW): 7.2014\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "example 6.4 pageno : 123"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "import math \n",
      "from matplotlib.pyplot import *\n",
      "\n",
      "# Initialization of Variable\n",
      "#each is increased by five units to make each compatible for graph plotting\n",
      "Q = [0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.1]      #flow rate\n",
      "HeffA = [20.63 ,19.99, 17.80, 14.46, 10.33, 5.71, 0, 0, 0, 0, 0 ]                 #Heff of pump A\n",
      "HeffB = [18 ,17, 14.95, 11.90, 8.10, 3.90, 0, 0, 0, 0, 0]                         #Heff of pump B\n",
      "alpha = 1.\n",
      "h = 10.4\n",
      "d = 0.14\n",
      "l = 98.\n",
      "pi = 3.1412\n",
      "g = 9.81\n",
      "rho = 999.\n",
      "mu = 0.001109\n",
      "H_sys = [0,0,0,0,0,0,0,0,0,0,0]\n",
      "for i in range(11):\n",
      "    if i == 0:\n",
      "        H_sys[i] = h\n",
      "    else:\n",
      "        H_sys[i] = h+8*Q[i]**2/pi**2/d**4/g*(1+8*l*0.0396/d*(4*rho*Q[i]/pi/d/mu)**-0.25)\n",
      "\n",
      "#H_sys is head of the system\n",
      "print  \"the head of system in terms of height of water : \",H_sys\n",
      "plot(Q,H_sys,'r--d')\n",
      "plot(Q,HeffA ,'-c')\n",
      "plot(Q,HeffB)\n",
      "show()\n",
      "\n",
      "#at intersecting point using datatrip b/w H_sys &H_effA\n",
      "print \"the flow rate at which H_sys takes over HeffA \",0.03339\n",
      "\n",
      "\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "the head of system in terms of height of water :  [10.4, 10.703503558535079, 11.434551925145852, 12.522017190713953, 13.934570851357016, 15.652293146483034, 17.66081196342499, 19.949010875049055, 22.507899154909985, 25.329974605787854, 28.4088306047139]\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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MtAVTp6qTqr163X0akzHuq1OHzZ06MfHECfZdv27+AIUQlmfMQHxqaqoSGhpa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\nhBAORhK7EEI4mP8HHfNwDjcyutAAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x3203e10>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "the flow rate at which H_sys takes over HeffA  0.03339\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "example 6.5 pageno : 126"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "\n",
      "import math\n",
      "from numpy import *\n",
      "\n",
      "# Initialization of Variable\n",
      "rho = 1000.\n",
      "dc = .15\n",
      "l = 7.8\n",
      "g = 9.81\n",
      "pi = 3.1428\n",
      "atp = 105.4*1000\n",
      "vap_pre = 10.85*1000\n",
      "sl = .22\n",
      "dp = 0.045\n",
      "h = 4.6\n",
      "\n",
      "#(\"x(t) = sl/2*cos(2*pi*N*t)\"  \"the function of print lcement\")\n",
      "#\"since we have to maximize the acceleration double derivate the terms\")\n",
      "#since double derivation have the term cos(kt) \n",
      "#finding it maxima\n",
      "t = linspace(0,5,100)\n",
      "k = 1.\n",
      "\n",
      "def  maximacheckerforcosine():\n",
      "    h = 0.00001\n",
      "    a = 0.00\n",
      "    for i in range(1,401): \n",
      "        if (math.cos(a+h)-math.cos(a-h))/2*h == 0 and math.cos(i-1)>0:\n",
      "            break\n",
      "        else:\n",
      "            a = 0.01+a\n",
      "    m = i-1\n",
      "    v = math.cos(i-1)\n",
      "    return m,v\n",
      "\n",
      "a, b =  maximacheckerforcosine()\n",
      "\n",
      "print \"time t when the acceleration will be maximum(s)\",a\n",
      "\n",
      "#double derivative will result in a square of value of N\n",
      "#lets consider its coefficient all will be devoid of N**2 \n",
      "k = sl/2*(2*pi)**2                      #accn max of piston\n",
      "kp = k*1./4*pi*dc**2/1.*4/pi/dp**2      #accn coeff. ofsuction pipe\n",
      "f = 1./4*pi*dp**2*l*rho*kp              #force exerted by piston\n",
      "p = f/1.*4./pi/dp**2                    #pressure exerted by piston\n",
      "\n",
      "#calculation\n",
      "o = atp-h*rho*g-vap_pre\n",
      "#constant term of quadratic eqn\n",
      "y = poly1d([-p, 0,o],False)\n",
      "a = roots(y)\n",
      "print \"Maximum frequency of oscillation if cavitation o be avoided(in Hz) %.4f\"%abs(a[0])\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "time t when the acceleration will be maximum(s) 0\n",
        "Maximum frequency of oscillation if cavitation o be avoided(in Hz) 0.3622\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "example 6.6 pageno : 128"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "\n",
      "import math \n",
      "\n",
      "# Initialization of Variable\n",
      "rhos = 1830.            #density of acid\n",
      "atp = 104.2*1000        #atmospheric pressure\n",
      "temp = 11.+273          #temp in kelvin\n",
      "M = 28.8/1000           #molar mass of air\n",
      "R = 8.314               #universal gas constant\n",
      "g = 9.81                #acceleration of gravity\n",
      "pi = 3.14\n",
      "d = 2.45                #diameter of tank\n",
      "l = 10.5                #length of tank\n",
      "h_s = 1.65              #height of surface of acid from below\n",
      "effi = 0.93             #efficiency\n",
      "\n",
      "#calculation\n",
      "mliq = pi*d**2*l*rhos/4\n",
      "h_atm = atp/rhos/g      #height conversion of atp\n",
      "h_r = 4.3-1.65          #height difference\n",
      "mair = g*h_r*mliq*M/(effi*R*temp*math.log(h_atm/(h_atm+h_s)))       #mass of air\n",
      "print \"mass of air required to lift the sulphuric acid tank %.4f\"%mair\n",
      "print \"The negative sign indicates air is expanding & work done is magnitude of value in kg:\"\n",
      "m = abs(mair/mliq)\n",
      "print  \"The mass of air required for per kilo of acid transferred: %.4f\"%m\n",
      "\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "mass of air required to lift the sulphuric acid tank -123.3851\n",
        "The negative sign indicates air is expanding & work done is magnitude of value in kg:\n",
        "The mass of air required for per kilo of acid transferred: 0.0014\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}