summaryrefslogtreecommitdiff
path: root/Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb
diff options
context:
space:
mode:
authorTrupti Kini2016-11-14 23:30:28 +0600
committerTrupti Kini2016-11-14 23:30:28 +0600
commita752afee497bb5a66577ba24d6d2a138a31cfdc9 (patch)
tree2d087b6428d3e212f9b12d8929ab4efda652765d /Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb
parent01b313afadc09f56176ecb22db02289591e05af5 (diff)
downloadPython-Textbook-Companions-a752afee497bb5a66577ba24d6d2a138a31cfdc9.tar.gz
Python-Textbook-Companions-a752afee497bb5a66577ba24d6d2a138a31cfdc9.tar.bz2
Python-Textbook-Companions-a752afee497bb5a66577ba24d6d2a138a31cfdc9.zip
Added(A)/Deleted(D) following books
A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_10_Sgd9FNt.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_2.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_3.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_4.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_5.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_6.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_7.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/chapter_9.ipynb A Strength_Of_Materials_by_S_S_Bhavikatti/screenshots/BMD_IXQhYHC.JPG A Strength_Of_Materials_by_S_S_Bhavikatti/screenshots/S_F_D_1_0Q7t8pV.JPG A Strength_Of_Materials_by_S_S_Bhavikatti/screenshots/s.JPG
Diffstat (limited to 'Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb')
-rw-r--r--Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb1531
1 files changed, 1531 insertions, 0 deletions
diff --git a/Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb b/Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb
new file mode 100644
index 00000000..69c4471a
--- /dev/null
+++ b/Strength_Of_Materials_by_S_S_Bhavikatti/chapter_8.ipynb
@@ -0,0 +1,1531 @@
+{
+ "metadata": {
+ "name": "chapter 8.ipynb"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Chapter No.8:Thin And Thick Cyclinders And Spheres"
+ ]
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.1,Page No.322"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "L=3000 #mm #Length\n",
+ "d1=1000 #mm #Internal diameter\n",
+ "t=15 #mm #Thickness\n",
+ "P=1.5 #N/mm**2 #Fluid Pressure\n",
+ "E=2*10**5 #n/mm**2 #Modulus of elasticity\n",
+ "mu=0.3 #Poissoin's ratio\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Hoop stress\n",
+ "f1=P*d1*(2*t)**-1 #N/mm**2\n",
+ "\n",
+ "#Longitudinal Stress\n",
+ "f2=P*d1*(4*t)**-1 #N/mm**2\n",
+ "\n",
+ "#Max shear stress\n",
+ "q_max=(f1-f2)*2**-1 #N/mm**2\n",
+ "\n",
+ "#Diametrical Strain\n",
+ "#Let e1=dell_d*d**-1 .....................(1)\n",
+ "e1=(f1-mu*f2)*E**-1 \n",
+ "\n",
+ "#Sub values in equation 1 and further simplifying we get\n",
+ "dell_d=e1*d1 #mm\n",
+ "\n",
+ "#Longitudinal strain\n",
+ "#e2=dell_L*L**-1 ......................(2)\n",
+ "e2=(f2-mu*f1)*E**-1 \n",
+ "\n",
+ "#Sub values in equation 2 and further simplifying we get\n",
+ "dell_L=e2*L #mm\n",
+ "\n",
+ "#Change in Volume \n",
+ "#Let Z=dell_V*V**-1 ................(3)\n",
+ "Z=2*e1+e2\n",
+ "\n",
+ "#Sub values in equation 3 and further simplifying we get\n",
+ "dell_V=Z*pi*4**-1*d1**2*L\n",
+ "\n",
+ "#Result\n",
+ "print\"Max Intensity of shear stress\",round(q_max,2),\"N/mm**2\"\n",
+ "print\"Change in the Dimensions of the shell is:dell_d\",round(dell_d,2),\"mm\"\n",
+ "print\" :dell_L\",round(dell_L,2),\"mm\"\n",
+ "print\" :dell_V\",round(dell_V,2),\"mm**3\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Max Intensity of shear stress 12.5 N/mm**2\n",
+ "Change in the Dimensions of the shell is:dell_d 0.21 mm\n",
+ " :dell_L 0.15 mm\n",
+ " :dell_V 1119192.38 mm**3\n"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.2,Page No.323"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "L=2000 #mm #Length\n",
+ "d=200 #mm # diameter\n",
+ "t=10 #mm #Thickness\n",
+ "dell_V=25000 #mm**3 #Additional volume\n",
+ "E=2*10**5 #n/mm**2 #Modulus of elasticity\n",
+ "mu=0.3 #Poissoin's ratio\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Let p be the pressure developed\n",
+ "\n",
+ "#Circumferential Stress\n",
+ "\n",
+ "#f1=p*d*(2*t)**-1 #N/mm**2\n",
+ "#After sub values and further simplifying\n",
+ "#f1=10*p\n",
+ "\n",
+ "#f1=p*d*(4*t)**-1 #N/mm**2\n",
+ "#After sub values and further simplifying\n",
+ "#f1=5*p\n",
+ "\n",
+ "#Diameterical strain = Circumferential stress\n",
+ "#Let X=dell_d*d**-1 ................................(1)\n",
+ "#X=e1=(f1-mu*f2)*E**-1 \n",
+ "#After sub values and further simplifying\n",
+ "#e1=8.5*p*E**-1\n",
+ "\n",
+ "#Longitudinal strain\n",
+ "#Let Y=dell_L*L**-1 ......................................(2)\n",
+ "#Y=e2=(f2-mu*f1)*E**-1 \n",
+ "#After sub values and further simplifying\n",
+ "#e2=2*p*E**-1\n",
+ "\n",
+ "#Volumetric strain\n",
+ "#Let X=dell_V*V**-1 \n",
+ "#X=2*e1+e2\n",
+ "#After sub values and further simplifying\n",
+ "#X=19*p*E**-1\n",
+ "#After further simplifying we get\n",
+ "p=dell_V*(pi*4**-1*d**2*L)**-1*E*19**-1 #N/mm**2\n",
+ "\n",
+ "#Hoop Stress\n",
+ "f1=p*d*(2*t)**-1\n",
+ "\n",
+ "X=e1=8.5*p*E**-1\n",
+ "#Sub value of X in equation 1 we get\n",
+ "dell_d=8.5*p*E**-1*d\n",
+ "\n",
+ "Y=e2=2*p*E**-1\n",
+ "#Sub value of Y in equation 2 we get\n",
+ "dell_L=2*p*E**-1*L\n",
+ "\n",
+ "#Result\n",
+ "print\"Pressure Developed is\",round(p,2),\"N/mm**2\"\n",
+ "print\"Hoop stress Developed is\",round(f1,2),\"N/mm**2\"\n",
+ "print\"Change in diameter is\",round(dell_d,2),\"mm\"\n",
+ "print\"Change in Length is\",round(dell_L,2),\"mm\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Pressure Developed is 4.19 N/mm**2\n",
+ "Hoop stress Developed is 41.88 N/mm**2\n",
+ "Change in diameter is 0.04 mm\n",
+ "Change in Length is 0.08 mm\n"
+ ]
+ }
+ ],
+ "prompt_number": 2
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.3,Page No.324"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d=750 #mm #Diameter of water supply pipes\n",
+ "h=50*10**3 #mm #Water head\n",
+ "sigma=20 #N/mm**2 #Permissible stress\n",
+ "rho=9810*10**-9 #N/mm**3\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Pressure of water\n",
+ "P=rho*h #N/mm**2\n",
+ "\n",
+ "#Stress\n",
+ "#sigma=p*d*(2*t)**-1\n",
+ "#After further simplifying\n",
+ "t=P*d*(2*sigma)**-1 #mm \n",
+ "\n",
+ "#Result\n",
+ "print\"Thickness of seamless pipe is\",round(t,3),\"mm\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Thickness of seamless pipe is 9.197 mm\n"
+ ]
+ }
+ ],
+ "prompt_number": 3
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.4,Page No.326"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d=2500 #mm #Diameter of riveted boiler\n",
+ "P=1 #N/mm**2 #Pressure\n",
+ "rho1=0.7 #Percent efficiency\n",
+ "rho2=0.4 #Circumferential joints\n",
+ "sigma=150 #N/mm**2 #Permissible stress\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Equating Bursting force to longitudinal joint strength ,we get\n",
+ "#p*d*L=rho1*2*t*L*sigma\n",
+ "#After rearranging and further simplifying we get\n",
+ "t=P*d*(2*sigma*rho1)**-1 #mm\n",
+ "\n",
+ "#Considering Longitudinal force\n",
+ "#pi*d**2*4**-1*P=rho2*pi*d*t*sigma\n",
+ "#After rearranging and further simplifying we get\n",
+ "t2=P*d*(4*sigma*rho2)**-1\n",
+ "\n",
+ "#Result\n",
+ "print\"Thickness of plate required is\",round(t,2),\"mm\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Thickness of plate required is 11.9 mm\n"
+ ]
+ }
+ ],
+ "prompt_number": 4
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.5,Page No.326"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "#Boiler Dimensions\n",
+ "t=16 #mm #Thickness\n",
+ "p=2 #N/mm**2 #internal pressure\n",
+ "f=150 #N/mm**2 #Permissible stress\n",
+ "rho1=0.75 #Longitudinal joints\n",
+ "rho2=0.45 #circumferential joints\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Equating Bursting force to longitudinal joint strength ,we get\n",
+ "d1=rho1*2*t*f*p**-1 #mm\n",
+ "\n",
+ "#Considering circumferential strength \n",
+ "d2=4*rho2*t*f*p**-1 #mm\n",
+ "\n",
+ "#Result\n",
+ "print\"Largest diameter of Boiler is\",round(d1,2),\"mm\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Largest diameter of Boiler is 1800.0 mm\n"
+ ]
+ }
+ ],
+ "prompt_number": 5
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.6,Page No.329"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d=250 #mm #Diameter iron pipe\n",
+ "t=10 #mm #Thickness\n",
+ "d2=6 #mm #Diameter of steel\n",
+ "p=80 #N/mm**2 #stress\n",
+ "P=3 #N/mm**2 #Pressure\n",
+ "E_c=1*10**5 #N/mm**2\n",
+ "mu=0.3 #poissoin's ratio\n",
+ "E_s=2*10**5 #N/mm**2\n",
+ "n=1 #No.of wires\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "L=6 #mm #Length of cyclinder\n",
+ "\n",
+ "#Force Exerted by steel wire at diameterical section\n",
+ "F=p*2*pi*d2**2*1*4**-1 #N\n",
+ "\n",
+ "#Initial stress in cyclinder\n",
+ "f_c=F*(2*t*d2)**-1 #N/mm**2\n",
+ "\n",
+ "#LEt due to fluid pressure alone stresses developed in steel wire be F_w and in cyclinder f1 and f2\n",
+ "f2=P*d*(4*t)**-1 #N/mm**2\n",
+ "\n",
+ "#Considering the equilibrium of half the cyclinder, 6mm long we get\n",
+ "#F_w*2*pi*4**-1*d2**2*n+f1*2*t*d2=P*d*d2\n",
+ "#After further simplifying we get\n",
+ "#F_w+2.122*f1=79.58 . ......................................(1)\n",
+ "\n",
+ "#Equating strain in wire to circumferential strain in cyclinder \n",
+ "#F_w=(f1-mu*f2)*E_s*E_c**-1 #N/mm**2\n",
+ "#After further simplifying we get\n",
+ "#F_w=2*f1-11.25 ....................................(2)\n",
+ "\n",
+ "#Sub in equation in1 we get\n",
+ "f1=(79.58+11.25)*(4.122)**-1 #N/mm**2\n",
+ "F_w=2*f1-11.25 #N/mm**2\n",
+ "\n",
+ "#Final stresses\n",
+ "#1) In steel Wire\n",
+ "sigma=F_w+p #N/mm**2\n",
+ "\n",
+ "#2) In Cyclinder\n",
+ "sigma2=f1-f_c\n",
+ "\n",
+ "#Result\n",
+ "print\"Final Stresses developed in:cyclinder is\",round(sigma,2),\"N/mm**2\"\n",
+ "print\" :Steel is\",round(sigma2,2),\"N/mm**2\" "
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Final Stresses developed in:cyclinder is 112.82 N/mm**2\n",
+ " :Steel is -15.66 N/mm**2\n"
+ ]
+ }
+ ],
+ "prompt_number": 6
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.7,Page No.332"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d=750 #mm #Diameter of shell\n",
+ "t=8 #mm #THickness\n",
+ "p=2.5 #N/mm**2\n",
+ "E=2*10**5 #N/mm**2\n",
+ "mu=0.25 #Poissoin's ratio\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Hoop stress\n",
+ "f1=f2=p*d*(4*t)**-1 #N/mm**2\n",
+ "\n",
+ "#Change in Diameter\n",
+ "dell_d=d*p*d*(1-mu)*(4*t*E)**-1 #mm\n",
+ "\n",
+ "#Change in Volume\n",
+ "dell_V=3*p*d*(1-mu)*(4*t*E)**-1*pi*6**-1*d**3\n",
+ "\n",
+ "#Answer for Change in diameter is incorrect in book\n",
+ "\n",
+ "#Result\n",
+ "print\"Stress introduced is\",round(f1,2),\"N/mm**2\"\n",
+ "print\"Change in Diameter is\",round(dell_d,2),\"N/mm**2\"\n",
+ "print\"Change in Volume is\",round(dell_V,2),\"mm**3\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Stress introduced is 58.59 N/mm**2\n",
+ "Change in Diameter is 0.16 N/mm**2\n",
+ "Change in Volume is 145608.33 mm**3\n"
+ ]
+ }
+ ],
+ "prompt_number": 7
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.8,Page No.333"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d=600 #mm #Diameter of sherical shell\n",
+ "t=10 #mm #Thickness\n",
+ "f=80 #N/mm**2 #Permissible stress\n",
+ "rho=0.75 #Efficiency joint\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Max Pressure\n",
+ "p=f*4*t*rho*d**-1 #N/mm**2\n",
+ "\n",
+ "#Result\n",
+ "print\"Max Pressure is\",round(p,2),\"N/mm**2\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Max Pressure is 4.0 N/mm**2\n"
+ ]
+ }
+ ],
+ "prompt_number": 8
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.9,Page No.333"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "L=1000 #mm #Length of shell\n",
+ "d=200 #mm #Diameter\n",
+ "t=6 #mm #Thickness\n",
+ "p=1.5 #N/mm**2 #Internal Pressure\n",
+ "E=2*10**5 #N/mm**2\n",
+ "mu=0.25 #Poissoin's Ratio\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Change in Volume of sphere\n",
+ "dell_V_s=3*p*d*(1-mu)*(4*t*E)**-1*pi*6**-1*d**3\n",
+ "\n",
+ "#Hoop stress\n",
+ "f1=p*d*(2*t)**-1 #N/mm**2\n",
+ "\n",
+ "#Longitudinal stress\n",
+ "f2=p*d*(4*t)**-1 #N/mm**2\n",
+ "\n",
+ "#Principal strain\n",
+ "e1=(f1-mu*f2)*E**-1\n",
+ "e2=(f2-mu*f1)*E**-1\n",
+ "\n",
+ "V_c=1000 #mm**3\n",
+ "\n",
+ "#Change in Volume of cyclinder\n",
+ "dell_V_c=(2*e1+e2)*pi*4**-1*d**2*L\n",
+ "\n",
+ "#Total Change in Diameter\n",
+ "dell_V=dell_V_s+dell_V_c #mm**3\n",
+ "\n",
+ "#Result\n",
+ "print\"Change in Volume is\",round(dell_V,2),\"mm**3\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Change in Volume is 8443.03 mm**3\n"
+ ]
+ }
+ ],
+ "prompt_number": 9
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.10,Page No.337"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "%matplotlib inline\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d1=400 #mm #Internal Diameter\n",
+ "t=100 #mm #Thickness\n",
+ "p=80 #N/mm**2 #Fluid pressure\n",
+ "\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Internal Radius\n",
+ "r1=d1*2**-1 #mm\n",
+ "\n",
+ "#Outer Radius\n",
+ "r_o=r1+t #mm\n",
+ "\n",
+ "p1=80 #N/mm**2\n",
+ "p2=0\n",
+ "\n",
+ "#Now From Lame's Euation\n",
+ "#p_x=b*(x**2)**-1-a\n",
+ "#at x=200 #mm \n",
+ "p_x=80 #N/mm**2\n",
+ "#80=b*(200**2)**-1-a ..........................(1)\n",
+ "\n",
+ "#at x=300 #mm\n",
+ "#p_x2=0\n",
+ "#0=b*(300**2)**-1-a ...........................(2)\n",
+ "\n",
+ "#Sub equation 2 from 1\n",
+ "#80=b*(200**2)**-1-b*(300**2)**-1\n",
+ "#After Further simplifying we get\n",
+ "b=(50000)**-1*(200**2*300**2*80)\n",
+ "\n",
+ "#From equation 2 we get\n",
+ "a=b*(300**2)**-1\n",
+ "\n",
+ "#Variation of radial pressure p_x;\n",
+ "#p_x=b*(x**2)**-1-a\n",
+ "#After sub values and further simplifying we get\n",
+ "\n",
+ "#Radial pressure Variation\n",
+ "#At \n",
+ "x=200 #mm\n",
+ "p_x=b*(x**2)**-1-a #N/mm**2\n",
+ "\n",
+ "#At\n",
+ "x2=250 #mm\n",
+ "p_x2=b*(x2**2)**-1-a #N/mm**2\n",
+ "\n",
+ "#At \n",
+ "x3=300 #mm\n",
+ "p_x3=b*(x3**2)**-1-a #N/mm**2\n",
+ "\n",
+ "\n",
+ "#Hoop stress Distribution\n",
+ "#Variation of F_x\n",
+ "\n",
+ "#At \n",
+ "x=200 #mm\n",
+ "F_x=b*(x**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#At\n",
+ "x2=250 #mm\n",
+ "F_x2=b*(x2**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#At\n",
+ "x3=300 #mm\n",
+ "F_x3=b*(x3**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#Result\n",
+ "print\"Max Hoop stress is\",round(F_x,2),\"N/mm**2\"\n",
+ "print\"Min Hoop stress is\",round(F_x3,2),\"N/mm**2\"\n",
+ "print\"Plot of Hoop stress\"\n",
+ "\n",
+ "#Plotting Variation of hoop stress\n",
+ "\n",
+ "X1=[x,x2,x3]\n",
+ "Y1=[p_x,p_x2,p_x3]\n",
+ "Y2=[-F_x,-F_x2,-F_x3]\n",
+ "Z1=[0,0,0]\n",
+ "plt.plot(X1,Y1,X1,Y2,X1,Z1)\n",
+ "plt.xlabel(\"Length x in mm\")\n",
+ "plt.ylabel(\"Radial Stress Distribution & Hoop Stress Distribution in N/mm**2\")\n",
+ "plt.show()\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Max Hoop stress is 208.0 N/mm**2\n",
+ "Min Hoop stress is 128.0 N/mm**2\n",
+ "Plot of Hoop stress\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": "iVBORw0KGgoAAAANSUhEUgAAAZIAAAFRCAYAAABe/ivgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRERkEiYSIiIyCRMJERGZhImEiIhM8v8BOmQpuVllnG0AAAAASUVORK5CYII=\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x4e17390>"
+ ]
+ }
+ ],
+ "prompt_number": 10
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.11,Page No.338"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "%matplotlib inline\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d_o=300 #mm #Outside diameter \n",
+ "d2=200 #mm #Internal Diameter\n",
+ "p=14 #N/mm**2 #internal Fluid pressure\n",
+ "t=50 #mm #Thickness\n",
+ "r_o=150 #mm #Outside Diameter\n",
+ "r2=100 #mm #Internal Diameter\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#From Lame's Equation\n",
+ "#p_x=b*(x**2)**-1-a #N/mm**2 ...................(1)\n",
+ "#F_x=b*(x**2)**-1+a #N/mm**2 ...................(2)\n",
+ "\n",
+ "#At \n",
+ "x=r2=100 #mm\n",
+ "p_x=14 #N/mm**2\n",
+ "\n",
+ "#Sub value of p_x in equation 1 we get\n",
+ "#14=(100)**-1*b-a ............................(3)\n",
+ "\n",
+ "#At\n",
+ "x2=r_o=150 #mm\n",
+ "p_x2=0 #N/mm**2\n",
+ "\n",
+ "#Sub value in equation 1 we get\n",
+ "#0=b*(150**2)**-1-a ......................(4)\n",
+ "\n",
+ "#From Equations 3 and 4 we get\n",
+ "#14=b*(100**2)**-1-b*(100**2)**-1\n",
+ "#After sub values and further simplifying we get\n",
+ "b=14*100**2*150**2*(150**2-100**2)**-1\n",
+ "\n",
+ "#From equation 4 we get\n",
+ "a=b*(150**2)**-1\n",
+ "\n",
+ "#Hoop Stress\n",
+ "#F_x=b*(x**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#At \n",
+ "x=100 #mm\n",
+ "F_x=b*(x**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#At\n",
+ "x2=125 #mm\n",
+ "F_x2=b*(x2**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#At\n",
+ "x3=150 #mm\n",
+ "F_x3=b*(x3**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#If thin Cyclindrical shell theory is used,hoop stress is uniform and is given by\n",
+ "F=p*d2*(2*t)**-1 #N/mm**2\n",
+ "\n",
+ "#Percentage error in estimating max hoop tension\n",
+ "E=(F_x-F)*F_x**-1*100 #%\n",
+ "\n",
+ "#Result\n",
+ "print\"Max Hoop Stress Developed in the cross-section is\",round(F,2),\"N/mm**2\"\n",
+ "print\"Plot of Variation of hoop stress\"\n",
+ "\n",
+ "#Plotting Variation of hoop stress\n",
+ "\n",
+ "X1=[x,x2,x3]\n",
+ "Y1=[F_x,F_x2,F_x3]\n",
+ "Z1=[0,0,0]\n",
+ "plt.plot(X1,Y1,X1,Z1)\n",
+ "plt.xlabel(\"Length x in mm\")\n",
+ "plt.ylabel(\"Radial Stress Distribution & Hoop Stress Distribution in N/mm**2\")\n",
+ "plt.show()\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Max Hoop Stress Developed in the cross-section is 28.0 N/mm**2\n",
+ "Plot of Variation of hoop stress\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAFRCAYAAAB0TtpPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x563ec90>"
+ ]
+ }
+ ],
+ "prompt_number": 11
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.12,Page No.339"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d_o=300 #mm #Outside diameter \n",
+ "d2=200 #mm #Internal Diameter\n",
+ "p=12 #N/mm**2 #internal Fluid pressure\n",
+ "F_max=16 #N/mm**2 #Tensile stress\n",
+ "r_o=150 #mm #Outside Diameter\n",
+ "r2=100 #mm #Internal Diameter\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Let p_o be the External Pressure applied.\n",
+ "#From LLame's theorem\n",
+ "#p_x=b*(x**2)**-1-a ..............(1)\n",
+ "#F_x=b*(x**2)**-1+a ...........................(2)\n",
+ "\n",
+ "#Now At\n",
+ "x=100 #mm\n",
+ "p_x=12 #N/mm**2\n",
+ "#sub in equation 1 we get\n",
+ "#12=b*(100**2)**-1-a . ..................(3)\n",
+ "\n",
+ "#The Max Hoop stress occurs at least value of x where\n",
+ "x=r1=100 #mm\n",
+ "#16=b*(100**2)**-1+a .......................(4)\n",
+ "\n",
+ "#From Equations 1 and 2 we get\n",
+ "#28=b*(100**2)**-1+b*(100**2)**-1\n",
+ "#After furhter Simplifying we get\n",
+ "b=28*100**2*2**-1\n",
+ "\n",
+ "#sub in equation 1 we get\n",
+ "a=-(12-(b*(100**2)**-1))\n",
+ "\n",
+ "#Thus At\n",
+ "x2=150 #mm\n",
+ "p_o=b*(x2**2)**-1-a\n",
+ "\n",
+ "#Result\n",
+ "print\"Minimum External applied is\",round(p_o,2),\"N/mm**2\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Minimum External applied is 4.22 N/mm**2\n"
+ ]
+ }
+ ],
+ "prompt_number": 12
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.13,Page No.340"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d1=160 #mm #Internal Diameter \n",
+ "r1=80 #mm #External Diameter\n",
+ "p1=40 #N/mm**2 #Internal Diameter\n",
+ "P_max=120 #N/mm**2 #Allowable stress\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#From Lame's Equation we have\n",
+ "#p_x=b*(x**2)**-1-a ..........................(1)\n",
+ "#F_x=b*(x**2)**-1+a ...........................(2)\n",
+ "\n",
+ "#At \n",
+ "x=r1=80 #N/mm**2 \n",
+ "#Sub in equation 1 we get\n",
+ "#120=b*(80**2)**-1+a ........................(3)\n",
+ "\n",
+ "#The hoop tension at inner edge is max stress\n",
+ "#Hence\n",
+ "#120=b*(80**2)**-1+a .............................(4)\n",
+ "\n",
+ "#From Equation 3 and 4 we get\n",
+ "b=160*80**2*2**-1 \n",
+ "\n",
+ "#Sub in equation 3 we get\n",
+ "a=-(40-(b*(80**2)**-1))\n",
+ "\n",
+ "#Let External radius be r_o.Since at External Surface is Zero,we get\n",
+ "#0=b*(r_o)**-1-a\n",
+ "#After Further simplifying we get\n",
+ "r_o=(b*a**-1)**0.5\n",
+ "\n",
+ "#Thickness of Cyclinder \n",
+ "t=r_o-r1 #mm\n",
+ "\n",
+ "#Result\n",
+ "print\"Thickness Required is\",round(t,2),\"mm\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Thickness Required is 33.14 mm\n"
+ ]
+ }
+ ],
+ "prompt_number": 13
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.14,Page No.341"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d_o=300 #mm #Outside diameter \n",
+ "d1=180 #mm #Internal Diameter\n",
+ "p=12 #N/mm**2 #internal Fluid pressure\n",
+ "p_o=6 #N/mm**2 #External Pressure\n",
+ "r_o=150 #mm #Outside Diameter\n",
+ "r=90 #mm #Internal Diameter\n",
+ "\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#From Lame's Equation we have\n",
+ "#p_x=b*(x**2)**-1-a ..........................(1)\n",
+ "#F_x=b*(x**2)**-1+a ...........................(2)\n",
+ "\n",
+ "#At \n",
+ "x=r1=90 #N/mm**2 \n",
+ "p=42 #N/mm**2\n",
+ "#Sub in equation 1 we get\n",
+ "#42=b*(90**2)**-1-a ..............................(3)\n",
+ "\n",
+ "#At \n",
+ "x=r_o=150 #mm\n",
+ "p2=6 #N/mm**2\n",
+ "#sub in equation 1 we get\n",
+ "#6=b*(150**2)**-1-a ..............................(4)\n",
+ "\n",
+ "#From equations 3 and 4 weget\n",
+ "#36=b*(90**2)**-1-b2(150**2)**-1\n",
+ "#After further simplifying we get\n",
+ "b=36*90**2*150**2*(150**2-90**2)**-1\n",
+ "\n",
+ "#Sub value of b in equation 4 we get\n",
+ "a=b*(150**2)**-1-p_o\n",
+ "\n",
+ "#At \n",
+ "x=r1=90 #mm\n",
+ "F_x=b*(x**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#At \n",
+ "x2=r_o=150 #mm \n",
+ "F_x2=b*(x2**2)**-1+a #N/mm**2\n",
+ "\n",
+ "#Now if External pressure is doubled i.e p_o2=12 #N/mm**2 We have\n",
+ "p_o2=12 #N/mm**2\n",
+ "#sub in equation 4 we get\n",
+ "#12=b2*(150**2)**-1-a2 ..........................(5)\n",
+ "\n",
+ "#Max Hoop stress is to be 70.5 #N/mm**2,which occurs at x=r1=90 #mm\n",
+ "#Sub in equation 4 we get\n",
+ "#70.5=b*(90**2)**-1+a2 ................................(6)\n",
+ "\n",
+ "#Adding equation 5 and 6\n",
+ "#82.5=b2*(150**2)**-1+b*(90**2)**-1\n",
+ "#After furhter simplifying we get\n",
+ "b2=82.5*150**2*90**2*(150**2+90**2)**-1\n",
+ "\n",
+ "#Sub in equation 5 we get\n",
+ "a2=b2*(150**2)**-1-12 \n",
+ "\n",
+ "#If p_i is the internal pressure required then from Lame's theorem\n",
+ "p_i=b2*(r1**2)**-1-a2\n",
+ "\n",
+ "#Result\n",
+ "print\"Stresses int the material are:F_x\",round(F_x,2),\"N/mm**2\"\n",
+ "print\" :F_x2\",round(F_x2,2),\"N/mm**2\"\n",
+ "print\"Internal Pressure that can be maintained is\",round(p_i,2),\"N/mm**2\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Stresses int the material are:F_x 70.5 N/mm**2\n",
+ " :F_x2 34.5 N/mm**2\n",
+ "Internal Pressure that can be maintained is 50.82 N/mm**2\n"
+ ]
+ }
+ ],
+ "prompt_number": 14
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.15,Page No.344"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "%matplotlib inline\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "r1=200 #mm #Inner Radius\n",
+ "r2=250 #mm #Radius at common surface\n",
+ "r3=300 #mm #Outer radius\n",
+ "p=6 #N/mm**2 #Inital pressure\n",
+ "p2=80 #N/mm**2 #Pressure\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Inner Cyclinder:\n",
+ "\n",
+ "#From Lame's Equation we have\n",
+ "#p_x=b*(x**2)**-1-a ..........................(1)\n",
+ "#F_x=b*(x**2)**-1+a ...........................(2)\n",
+ "\n",
+ "#At \n",
+ "x=r1=200 #mm\n",
+ "p_x=0\n",
+ "#0=b1*(250**2)**-1-a1 .................(3)\n",
+ "\n",
+ "#At x=r2=250 #mm\n",
+ "p_x2=6 #N/mm**2\n",
+ "#6=b1*(250**2)-a1 ...................(4)\n",
+ "\n",
+ "#From Equation 3 and 4 we get\n",
+ "b1=6*200**2*250**2*(200**2-250**2)**-1\n",
+ "\n",
+ "#From equation 3 we get\n",
+ "a1=b1*(200**2)**-1\n",
+ "\n",
+ "F_200=b1*(200**2)**-1+a1\n",
+ "F_250=b1*(250**2)**-1+a1\n",
+ "\n",
+ "#For outer cyclinder \n",
+ "#From Lame's Equation we have\n",
+ "#p_x2=b2*(x**2)**-1-a2 ..........................(5)\n",
+ "#F_x2=b2*(x**2)**-1+a2 ...........................(6)\n",
+ "\n",
+ "\n",
+ "#At \n",
+ "x2=r2=250 #mm\n",
+ "p_x2=6 #N/mm**2\n",
+ "#6=b2*(250**2)**-1-a2 ...........................(7) \n",
+ "\n",
+ "#At\n",
+ "x3=300 #mm\n",
+ "#p_x2=0\n",
+ "#0=b2**2*(300**2)**-1-a2 .................................(8)\n",
+ "\n",
+ "#from equation 7 and 8 we get\n",
+ "b2=6*250**2*300**2*(300**2-250**2)**-1\n",
+ "\n",
+ "#sub in equation 8 we get\n",
+ "a2=b2*(300**2)**-1\n",
+ "\n",
+ "F_250_2=b2*(250**2)**-1+a2\n",
+ "F_300_2=b2*(300**2)**-1+a2\n",
+ "\n",
+ "#When Fluid is admitted\n",
+ "#Let Lame's equation be\n",
+ "#p_x3=b3*(x**2)**-1-a3 ..........................(5)\n",
+ "#F_x3=b3*(x**2)**-1+a3 ...........................(6)\n",
+ "\n",
+ "\n",
+ "#At x=200\n",
+ "p_x3=80 #N/mm**2\n",
+ "#80=b3*(200**2)**-1-a3 ................................(7)\n",
+ "\n",
+ "#At x=300 #mm\n",
+ "#p_x=0\n",
+ "#0=b3*(300**2)**-1-a3 ..............................(8)\n",
+ "\n",
+ "#from Equation 7 and 8 we get\n",
+ "b3=80*200**2*300**2*(300**2-200**2)**-1\n",
+ "\n",
+ "#From Equation 8 we get\n",
+ "a3=b3*(300**2)**-1\n",
+ "\n",
+ "#Hoop stresses \n",
+ "F_200_3=b3*(200**2)**-1+a3 #N/mm**2\n",
+ "F_250_3=b3*(250**2)**-1+a3 #N/mm**2\n",
+ "F_300_3=b3*(300**2)**-1+a3 #N/mm**2\n",
+ "\n",
+ "#Pressure at common surface\n",
+ "p_250=b3*(250**2)**-1-a3 #N/mm**2\n",
+ "\n",
+ "#final stress\n",
+ "f_200=F_200+F_200_3 #N/mm**2\n",
+ "f_250=F_250+F_250_3 #N/mm**2\n",
+ "f_300=F_250_2+F_250_3 #N/mm**2\n",
+ "f_300_2=F_300_2+F_300_3 #N/mm**2\n",
+ "\n",
+ "#Result\n",
+ "print\"final Hoop stress are:f_200\",round(f_200,2),\"N/mm**2\"\n",
+ "print\" :f_250\",round(f_250,2),\"N/mm**2\"\n",
+ "print\" :f_300\",round(f_300,2),\"N/mm**2\"\n",
+ "print\" :f_300_2\",round(f_300_2,2),\"N/mm**2\"\n",
+ "print\"Variation of Hoop stress and Radial stress\"\n",
+ "\n",
+ "#Final stresses\n",
+ "#Variation of hoop stress \n",
+ " \n",
+ "X1=[x,x2,x3,x3]\n",
+ "Y1=[f_200,f_250,f_300,f_300_2]\n",
+ "Z1=[0,0,0,0]\n",
+ "plt.plot(X1,Y1,X1,Z1)\n",
+ "plt.xlabel(\"Length x in mm\")\n",
+ "plt.ylabel(\"Hoop Stress Distribution in N/mm**2\")\n",
+ "plt.show()\n",
+ "\n",
+ "#Due to Fluid\n",
+ "#Variation of hoop stress \n",
+ " \n",
+ "X1=[x,x2,x3]\n",
+ "Y1=[F_200_3,F_250_3,F_300_3]\n",
+ "Z1=[0,0,0]\n",
+ "plt.plot(X1,Y1,X1,Z1)\n",
+ "plt.xlabel(\"Length x in mm\")\n",
+ "plt.ylabel(\"Hoop Stress Distribution in N/mm**2\")\n",
+ "plt.show()\n",
+ "\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "final Hoop stress are:f_200 174.67 N/mm**2\n",
+ " :f_250 128.83 N/mm**2\n",
+ " :f_300 189.43 N/mm**2\n",
+ " :f_300_2 155.27 N/mm**2\n",
+ "Variation of Hoop stress and Radial stress\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEPCAYAAABcA4N7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEenEREFERDoxURARkU7/H21GIMqBrUIbAAAAAElFTkSuQmCC\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x5576590>"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEPCAYAAABcA4N7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x566a330>"
+ ]
+ }
+ ],
+ "prompt_number": 15
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.16,Page No.348"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "do=200 #mm #Inner Diameter\n",
+ "r_o=100 #mm #Inner radius\n",
+ "d1=300 #mm #outer diameter\n",
+ "r1=150 #mm #Outer radius\n",
+ "d2=250 #mm #Junction Diameter\n",
+ "r2=125 #mm #Junction radius\n",
+ "E=2*10**5 #N/mm**2 #Modulus of Elasticity\n",
+ "p=30 #N/mm**2 #radial pressure\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#from Lame's Equation we get\n",
+ "#p_x=b*(x**2)**-1-a ..........................(1)\n",
+ "#F_x=b*(x**2)**-1+a ...........................(2)\n",
+ "\n",
+ "#Then from Boundary condition \n",
+ "#p_x=0 at x=100 #mm\n",
+ "#0=b1*(100**2)**-1-a1 .....................(3)\n",
+ "\n",
+ "#p_x2=30 #N/mm**2 at x2=125 #mm\n",
+ "#30=b1*(125**2)**-1-a1 ................................(4)\n",
+ "\n",
+ "#From equation 3 and 4 we get\n",
+ "b1=30*125**2*100**2*(100**2-125**2)**-1\n",
+ "\n",
+ "#From Equation 3 we get\n",
+ "a1=b1*(100**2)**-1\n",
+ "\n",
+ "#therefore Hoop stress in inner cyclinder at junction\n",
+ "F_2_1=b1*(125**2)**-1+a1 #N/mm**2\n",
+ "\n",
+ "#Outer Cyclinder\n",
+ "#p_x=b*(x**2)**-1-a ..........................(5)\n",
+ "#F_x=b*(x**2)**-1+a ...........................(6)\n",
+ "\n",
+ "#Now at x=125 #mm\n",
+ "#p_x3=30 #N/mm**2\n",
+ "#30=b2*(125**2)**-1-a2 ..................................(7)\n",
+ "\n",
+ "#At x=150 #mm\n",
+ "#p_x4=0\n",
+ "#0=b2*(150**2)**-1-a2 ...................................(8)\n",
+ "\n",
+ "#From equations 7 and 8\n",
+ "b2=30*150**2*125**2*(150**2-125**2)**-1\n",
+ "\n",
+ "#From eqauation 8 we get\n",
+ "a2=b2*(150**2)**-1\n",
+ "\n",
+ "#Hoop stress at junction \n",
+ "F_2_0=b2*(125**2)**-1+a2 #N/mm**2\n",
+ "\n",
+ "rho_r=(F_2_0-F_2_1)*E**-1*r2\n",
+ "\n",
+ "#Result\n",
+ "print\"Shrinkage Allowance is\",round(rho_r,3),\"mm\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Shrinkage Allowance is 0.189 mm\n"
+ ]
+ }
+ ],
+ "prompt_number": 16
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.17,Page No.350"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d_o=500 #mm #Outer Diameter\n",
+ "r_o=250 #mm #Outer Radius\n",
+ "d1=300 #mm #Inner Diameter\n",
+ "r1=150 #mm #Inner Radius\n",
+ "d2=400 #mm #Junction Diameter\n",
+ "E=2*10**5 #N/mm**2 #Modulus ofElasticity\n",
+ "alpha=12*10**-6 #Per degree celsius\n",
+ "dell_d=0.2 #mm\n",
+ "dell_r=0.1 #mm\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#Let p be the radial pressure developed at junction\n",
+ "#Let Lame's Equation for internal cyclinder be\n",
+ "#p_x=b*(x**2)**-1-a ................................(1)\n",
+ "#F_x=b*(x**2)**-1+a ...............................(2)\n",
+ "\n",
+ "#At \n",
+ "x=150 #mm \n",
+ "p_x=0\n",
+ "#Sub in equation 1 we get\n",
+ "#0=b*(150**2)**-1-a .........................(3)\n",
+ "\n",
+ "#At \n",
+ "x2=200 #mm\n",
+ "#p_x2=p\n",
+ "#p=b*(200**2)**-1-a ......................(4)\n",
+ " \n",
+ "#From Equation 3 and 4\n",
+ "#p=b*(200**2)**-1-b(150**2)**-1\n",
+ "#after further simplifying we get\n",
+ "#b=-51428.571*p\n",
+ "\n",
+ "#sub in equation 3 we get\n",
+ "#a1=-2.2857*p\n",
+ "\n",
+ "#therefore hoop stress at junction is\n",
+ "#F_2_1=-21428.571*p*(200**2)**-1-2.2857*p\n",
+ "#after Further simplifying we geet\n",
+ "#F_2_1=3.5714*p\n",
+ "\n",
+ "#Let Lame's Equation for cyclinder be \n",
+ "#p_x=b*(x**2)**-1-a .........................5\n",
+ "#F_x=b*(x**2)**-1+a .............................6\n",
+ "\n",
+ "#At \n",
+ "x=200 #mm\n",
+ "#p_x=p2\n",
+ "#p2=b2*(20**2)**-1-a2 ...................7\n",
+ "\n",
+ "#At\n",
+ "x2=200 #mm\n",
+ "p_x2=0\n",
+ "#0=b2*(250**2)**-1-a2 ....................8\n",
+ "\n",
+ "#from equation 7 and 8 we get\n",
+ "#p2=b2*(200**2)**-1-b2*(250**2)**-1\n",
+ "#After further simplifying we get\n",
+ "#p2=b2*(250**2-200**2)*(200**2*250**2)**-1\n",
+ "#b2=111111.11*p\n",
+ "\n",
+ "#from equation 7\n",
+ "#a2=b2*(250**2)**-1\n",
+ "#further simplifying we get\n",
+ "#a2=1.778*p\n",
+ "\n",
+ "#At the junctionhoop stress in outer cyclinder \n",
+ "#F_2_0=b2*(200**2)**-1+a2\n",
+ "#After further simplifying we get\n",
+ "#F_2_0=4.5556*p\n",
+ "\n",
+ "#Considering circumferential strain,the compatibility condition\n",
+ "#rho_r*r2**-1=1*E**-1*(F_2_1+F_2_0)\n",
+ "#where F_2_1 is compressive and F_2_0 is tensile\n",
+ "#furter simplifying we get\n",
+ "p=0.1*200**-1*2*10**5*(3.5714+4.5556)**-1\n",
+ "\n",
+ "#Let T be the rise in temperature required\n",
+ "#dell_d=d*alpha*T\n",
+ "#After sub values and further simplifying we get\n",
+ "d=250 #mm\n",
+ "T=dell_d*(d*alpha)**-1 #Per degree celsius\n",
+ "\n",
+ "#Result\n",
+ "print\"Radial Pressure Developed at junction\",round(p,2),\"N/mm**2\"\n",
+ "print\"Min Temperatureto outer cyclinder\",round(T,2),\"Per degree Celsius\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Radial Pressure Developed at junction 12.3 N/mm**2\n",
+ "Min Temperatureto outer cyclinder 66.67 Per degree Celsius\n"
+ ]
+ }
+ ],
+ "prompt_number": 17
+ },
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Example 8.8.18,Page No.355"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import numpy as np\n",
+ "%matplotlib inline\n",
+ "\n",
+ "#Initilization of Variables\n",
+ "\n",
+ "d_o=400 #mm #Outer Diameter\n",
+ "r_o=200 #mm #Outer radius\n",
+ "t=50 #mm #Thickness\n",
+ "r1=150 #mm #Internal Radius\n",
+ "p=50 #N/mm**2 #Internal Pressure\n",
+ "\n",
+ "#Calculations\n",
+ "\n",
+ "#The Radial Pressure and hoop stress at any radial distance x are given by\n",
+ "#p_x=b*(x**2)**-1-a ..........................(1)\n",
+ "#F_x=b*(x**2)**-1+a ...........................(2)\n",
+ "\n",
+ "#Now at\n",
+ "x=150 #N/mm**2\n",
+ "p_x1=50 #N/mm**2\n",
+ "#Sub in equation 1 we get\n",
+ "#50=2*b*(150**3)**-1-a ...........................(3)\n",
+ "\n",
+ "#At x=200 #mm\n",
+ "p_x2=0\n",
+ "#0=2*b*(200**2)**-1-a ....................(4)\n",
+ "\n",
+ "#From equation 3 and 4 we get\n",
+ "#50=2*b*(150**3)**-1-2*b*(200**3)**-1\n",
+ "#After further simplifying we get\n",
+ "b=50*150**3*200**3*(200**3-150**3)**-1*2**-1\n",
+ "\n",
+ "#Sub in equation 3 we get\n",
+ "a=b*(200**3)**-1\n",
+ "\n",
+ "#Now At\n",
+ "x=150 #mm\n",
+ "F_x=b*(x**3)**-1+a\n",
+ "\n",
+ "#Now At\n",
+ "x2=160 #mm\n",
+ "F_x2=b*(x2**3)**-1+a\n",
+ "\n",
+ "#Now At\n",
+ "x3=170 #mm\n",
+ "F_x3=b*(x3**3)**-1+a\n",
+ "\n",
+ "#Now At\n",
+ "x4=180 #mm\n",
+ "F_x4=b*(x4**3)**-1+a\n",
+ "\n",
+ "#Now At\n",
+ "x5=190 #mm\n",
+ "F_x5=b*(x5**3)**-1+a\n",
+ "\n",
+ "#Now At\n",
+ "x6=200 #mm\n",
+ "F_x6=b*(x6**3)**-1+a\n",
+ "\n",
+ "#Result\n",
+ "print\"Plot of Variation of hoop stress\"\n",
+ "\n",
+ "#Plotting Variation of hoop stress\n",
+ "\n",
+ "X1=[x,x2,x3,x4,x5,x6]\n",
+ "Y1=[F_x,F_x2,F_x3,F_x4,F_x5,F_x6]\n",
+ "Z1=[0,0,0,0,0,0]\n",
+ "plt.plot(X1,Y1,X1,Z1)\n",
+ "plt.xlabel(\"Length x in mm\")\n",
+ "plt.ylabel(\"Hoop Stress Distribution in N/mm**2\")\n",
+ "plt.show()\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Plot of Variation of hoop stress\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAEPCAYAAABCyrPIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBgIREQEA/h+bezx5xlsz+QAAAABJRU5ErkJggg==\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x58d75b0>"
+ ]
+ }
+ ],
+ "prompt_number": 18
+ }
+ ],
+ "metadata": {}
+ }
+ ]
+} \ No newline at end of file