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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Chapter16-Soil-Bearing Capacity for Shallow Foundations"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Ex1-pg587"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#determine the gross allowable load per unit area (qall) that the foundation can carry.\n",
      "import math\n",
      "c=20.\n",
      "## from table 16.1\n",
      "Nc=17.69\n",
      "Nq=7.44\n",
      "Ng=3.64\n",
      "\n",
      "Df=3.\n",
      "G=110.\n",
      "q=G*Df\n",
      "\n",
      "C=200.\n",
      "B=4.\n",
      "\n",
      "Qu= C*Nc+q*Nq+G*B*Ng/2.\n",
      "\n",
      "Fs=3.\n",
      "Qall=Qu/Fs\n",
      "print'%s %.1f %s'%('Qa = ',Qall,' lb/ft^2')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Qa =  2264.7  lb/ft^2\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Ex2-pg588"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "#determine the size of the footing\u2014that is, the size of B.\n",
      "G=18.15\n",
      "qa=30000.*9.81/1000.\n",
      "\n",
      "Nc=57.75\n",
      "Nq=41.44\n",
      "Ng=45.41\n",
      "C=0.\n",
      "q=G*1.\n",
      "B=1.\n",
      "(1.3*C*Nc+q*Nq+0.4*G*B*Ng)*B**2/3. == qa\n",
      "B= math.sqrt(294.3/(250.7+109.9))\n",
      "print'%s %.1f %s'%(' B = ',B,' m')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " B =  0.9  m\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Ex3-pg595"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "# Determine the safe gross load (factor of safety of 3) that the footing can carry\n",
      "B=1.2\n",
      "L=1.2\n",
      "c=32.\n",
      "C=0.\n",
      "Df=1.\n",
      "G=16.\n",
      "Nq=23.18\n",
      "Ng=22.02\n",
      "Nc=1.\n",
      "Lqs=1.+0.1*B*(math.tan(61./57.3)**2.)/L\n",
      "Lgs=Lqs\n",
      "Lqd=1.+0.1*Df*math.tan(61./57.3)/B\n",
      "Lgd=Lqd\n",
      "Lcs=1.\n",
      "Lcd=1.\n",
      "Gs=19.5\n",
      "q=0.5*G+0.5*(Gs-9.81)\n",
      "Qu= C*Lcs*Lcd*Nc+q*Lqs*Lqd*Nq+(Gs-9.81)*Lgs*Lgd*B*Ng/2.\n",
      "Qa=Qu/3.\n",
      "Q=Qa*B**2.\n",
      "print'%s %.1f %s'%('the gross load = ',Q,' kN')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "the gross load =  311.6  kN\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Ex4-pg601"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "#Determine the magnitude of the gross ultimate load applied eccentrically for bearing capacity failure in soil.\n",
      "e=0.1\n",
      "B=1.\n",
      "X=B-2.*e\n",
      "Y=1.5\n",
      "B1=0.8\n",
      "L1=1.5\n",
      "c=30.\n",
      "Df=1.\n",
      "Nq=18.4\n",
      "Ng=15.668\n",
      "q=1.*18.\n",
      "G=18.\n",
      "Lqs=1.+e*(B1/L1)*math.tan(60./57.3)**2.\n",
      "Lgs=Lqs\n",
      "Lqd=1.+e*(Df/B1)*math.tan(60./57.3)\n",
      "Lgd=Lqd\n",
      "qu=q*Lqs*Lqd*Nq+Lgs*Lgd*G*B1*Ng/2.\n",
      "Qu=qu*B1*L1\n",
      "print'%s %.1f %s'%('The magnitude of the gross ultimate load =',Qu,' kN')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The magnitude of the gross ultimate load = 751.8  kN\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Ex5-pg601"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#determine the gross ultimate load per unit length that the foundation can carry.\n",
      "import math\n",
      "B=1.5\n",
      "Df=0.75\n",
      "e=0.1*B\n",
      "G=17.5\n",
      "c=30.\n",
      "C=0.\n",
      "q=G*Df\n",
      "Nq=18.4\n",
      "Ng=15.668\n",
      "Lqd=1.+0.1*(Df/B)*math.tan(60./57.3)\n",
      "Lgd=Lqd\n",
      "Quc=q*Nq*Lqd+Lgd*B*Ng/2.\n",
      "k=0.8\n",
      "a=1.754\n",
      "Qua=Quc*(1.-a*(e/B)**k)\n",
      "print'%s %.1f %s'%('The gross ultimate load per unit length = ',Qua,' kN')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The gross ultimate load per unit length =  198.7  kN\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Ex6-pg606"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import math\n",
      "#Estimate the ultimate bearing capacity of a circular footing with a diameter of 1.5 m. The soil is sandy.\n",
      "Qup=280.\n",
      "Bp=0.7 ## in m\n",
      "Bf=1.5\n",
      "Quf=Qup*Bf/Bp\n",
      "print'%s %.1f %s'%('The ultimate bearing capacity = ',Quf,' kN/m^2')\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The ultimate bearing capacity =  600.0  kN/m^2\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Ex7-pg606"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#calculate the value of Cv\n",
      "import math\n",
      "#Determine the size of a square column foundation that should carry a load of 2500 kN with a maximum settlement of 25 mm.\n",
      "a=2500.\n",
      "##doing for the first values only\n",
      "Bf=4.\n",
      "Bp=0.305\n",
      "q=a/Bf**2.\n",
      "Sep=4.\n",
      "Sef=Sep*(2.*Bf/(Bf+Bp))**2\n",
      "print'%s %.1f %s'%('Sef = ',Sef,' mm')\n",
      "import math\n",
      "%matplotlib inline\n",
      "import warnings\n",
      "warnings.filterwarnings('ignore')\n",
      "import numpy\n",
      "from math import tan\n",
      "import matplotlib\n",
      "from matplotlib import pyplot\n",
      "#given\n",
      "t=numpy.array([.02,.1,.25,.5,1,2.,4.,8.,16.,30.,60.,120.,240.,480.,960.,1440.])\n",
      "gauge=numpy.array([3975.,4082.,4102.,4128.,4166.,4224.,4298.,4420.,4572.,4737.,4923.,5080.,5207.,5283.,5334.,5364.])\n",
      "Hdr=2.24\n",
      "t50=19.\n",
      "#calculations\n",
      "Cv=.197*(Hdr/2)**2 /t50/60.\n",
      "leng=len(t)\n",
      "logt=numpy.zeros(leng)\n",
      "for i in range(0,leng):\n",
      "\tlogt[i]=math.log(t[i])\n",
      "\n",
      "#results\n",
      "print'%s %.4f %s'%('The value of Cv (cm^2/sec) = ',Cv,'')\n",
      "pyplot.plot(logt,gauge)\n",
      "pyplot.xlabel('Time(min) - log scale')\n",
      "pyplot.ylabel('Dial reading (cm)')\n",
      "pyplot.title('Graph of dial reading vs time')\n",
      "pyplot.show()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Sef =  13.8  mm\n",
        "The value of Cv (cm^2/sec) =  0.0002 \n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
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ajHffTaOyO3WC2293omhJThZm1ia8/npa5nTzzeG66zzPU0tzsjCzVm/uXNhlF/jGNzzP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\nmQhcK+kiUjVTH2BGRISkdyU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       "text": [
        "<matplotlib.figure.Figure at 0x54c9290>"
       ]
      }
     ],
     "prompt_number": 2
    }
   ],
   "metadata": {}
  }
 ]
}