{ "metadata": { "name": "" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Chapter 9: Cams" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Example 5, Page 300" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%matplotlib inline\n", "import math\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "#Variable declaration\n", "alpha=55*math.pi/180\n", "N=1200#rpm\n", "lift=.5#in\n", "rn=.125#in ; noseradius\n", "rmin=1.125#in ; minimum radius\n", "\n", "#Calculations&Results\n", "OQ=rmin+lift-rn\n", "OP=(OQ**2-1)/(2*(1-OQ*math.cos(alpha)))#from triangle opq fig 201(a)\n", "PQ=OP+rmin-rn\n", "phi=math.asin(OQ*math.sin(alpha)/PQ)\n", "x1=np.linspace(0,phi)\n", "x2=np.linspace(phi,alpha)\n", "y1=4.477*(1-np.cos(x1))#from 9.6\n", "y2=1.5*np.cos(alpha-x2)-1#from 9.9\n", "v1=math.pi*N*4.477*np.sin(x1)/(30*12)#from 9.7\n", "v2=15.71*np.sin(alpha-x2)#from 9.10\n", "f1=(math.pi*N/30)**2*(4.477/12)*np.cos(x1)#from 9.8\n", "f2=-1974*np.cos(alpha-x2)#from 9.11\n", "a=np.linspace(0,phi)\n", "b=np.linspace(phi,alpha)\n", "p=np.linspace(0,phi)\n", "q=np.linspace(phi,alpha)\n", "plt.subplot(3,1,3)\n", "plt.subplot(3,1,1)\n", "plt.plot(x1,y1,x2,y2)\n", "plt.tick_params(axis='y', which='both', labelleft='off', labelright='on')\n", "plt.xlabel(\"angle\")\n", "plt.ylabel(\"displacement\")\n", "plt.subplot(3,1,2)\n", "plt.plot(a,v1,b,v2)\n", "plt.tick_params(axis='y', which='both', labelleft='off', labelright='on')\n", "plt.ylabel(\"velocity\")\n", "plt.subplot(3,1,3)\n", "plt.plot(p,f1,q,f2)\n", "plt.tick_params(axis='y', which='both', labelleft='off', labelright='on')\n", "plt.xlabel(\"angle\")\n", "plt.ylabel(\"acceleration\")\n", "plt.show()" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "display_data", "png": 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55Zfs2LEDgLCwMKZPn06DBrVP+DKn27AHXUlpCZuPbuaHIz+wP3c/w92HM9lzMoNdB9PI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\n088rxj0752w7+7Tdj3f3nnv79e+x9aBb6nZ5jNy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"text": [ "" ] } ], "prompt_number": 4 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Example 7, Page 309" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import math\n", "\n", "#Variable declaration\n", "N=600#rpm\n", "BC=3#in\n", "rmin=1.125#in\n", "rf=39/8#in\n", "OP=rf-rmin\n", "OM1=0.79#in;given\n", "NZ1=2.66#in\n", "\n", "#Calculations\n", "w=N*math.pi/30\n", "vb=w*OM1\n", "Vang=vb/BC\n", "at=w**2*NZ1\n", "fBC=at/BC\n", "OM2=.52#in\n", "NZ2=3.24#in\n", "af=w*OM2/BC\n", "angf=w**2*NZ2/BC\n", "\n", "#Results\n", "print \"When theta = 25 degrees\\nangular velocity = %.1f rad/s\\nangular acceleration = %.f rad/s^2\"\\\n", " \"\\nWhen theta = 45 degrees\\nangular velocity = %.1f rad/s\\nangular acceleration = %.f rad/s^2\"%(Vang,fBC,af,angf)" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "When theta = 25 degrees\n", "angular velocity = 16.5 rad/s\n", "angular acceleration = 3500 rad/s^2\n", "When theta = 45 degrees\n", "angular velocity = 10.9 rad/s\n", "angular acceleration = 4264 rad/s^2\n" ] } ], "prompt_number": 3 } ], "metadata": {} } ] }