summaryrefslogtreecommitdiff
path: root/Fluid_Mechanics-Fundamentals_&_Applications/Chapter10_2.ipynb
diff options
context:
space:
mode:
Diffstat (limited to 'Fluid_Mechanics-Fundamentals_&_Applications/Chapter10_2.ipynb')
-rwxr-xr-xFluid_Mechanics-Fundamentals_&_Applications/Chapter10_2.ipynb396
1 files changed, 396 insertions, 0 deletions
diff --git a/Fluid_Mechanics-Fundamentals_&_Applications/Chapter10_2.ipynb b/Fluid_Mechanics-Fundamentals_&_Applications/Chapter10_2.ipynb
new file mode 100755
index 00000000..505f66cb
--- /dev/null
+++ b/Fluid_Mechanics-Fundamentals_&_Applications/Chapter10_2.ipynb
@@ -0,0 +1,396 @@
+{
+ "metadata": {
+ "name": "",
+ "signature": "sha256:e9f209a2bf5415ddf06809cb9961528b86fd396a12cb639b1f2552ce5098ec2f"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Chapter 10:Approximate Solutions of the Navier-Stokes Equation"
+ ]
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 10.10-2, Page No:499"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "\n",
+ "#Variable Decleration\n",
+ "rho_air=0.8588 #Density of the surrounding air by gas law in kg/m^3\n",
+ "u=1.474*10**-5 #Dynamic Viscosity in kg/m.s\n",
+ "rho_particle=1240 #Density of the particle in kg/m^3\n",
+ "D=50*10**-6 #Diameter of the particles in m\n",
+ "g=9.81 #Acceleration due to gravity in m/s^2\n",
+ "\n",
+ "#Calculations\n",
+ "#Applying Newtons Third Law and solving for V we get\n",
+ "V=(D**2/(18*u))*(rho_particle-rho_air)*g #Terminal Velocity of the particle in m/s\n",
+ "\n",
+ "#Verification of Reynolds Number \n",
+ "Re=(rho_air*V*D)/u #Reynolds Number\n",
+ "\n",
+ "#Result\n",
+ "print \"The Terminal Velocity of the particles is\",round(V,3),\"m/s\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The Terminal Velocity of the particles is 0.115 m/s\n"
+ ]
+ }
+ ],
+ "prompt_number": 2
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 10.10-6,Page No:519"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "\n",
+ "#Variable Decleration\n",
+ "V_dot_by_L1=2 #Strength of source in line 1 in m^2/s at (0,-1)m\n",
+ "V_dot_by_L2=-1 #Strength of source in line 2 in m^2/s at (1,-1)m\n",
+ "T=1.5 #Vortex Strength in m^2/s a (1,1) m\n",
+ "r_vortex=1 #distance in m\n",
+ "r_source1=1.414 #Distance in m\n",
+ "r_source2=1 #Distance in m\n",
+ "\n",
+ "#Calculations\n",
+ "V_vortex=T/(2*pi*r_vortex) #Velocity Induced by the Vortex in m/s\n",
+ "V_source1=V_dot_by_L1/(2*pi*r_source1) #Velocity induced by the source1 in m/s\n",
+ "V_source2=V_dot_by_L2/(2*pi*r_source2) #Velocity induced by the source2 in m/s\n",
+ "V=V_vortex+(V_source1/2**0.5)+V_source2+(V_source1/2**0.5) #Vectorial addition of the velocities in m/s\n",
+ "\n",
+ "#Result\n",
+ "print \"The superposed velocity at point (1,0) is\",round(V,3),\"m/s to the right\"\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The superposed velocity at point (1,0) is 0.398 m/s to the right\n"
+ ]
+ }
+ ],
+ "prompt_number": 13
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 10.10-8, Page No:526"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "\n",
+ "#Variable Decleration\n",
+ "V_dot=0.11 #Volumetric flow rate in m^3/s\n",
+ "L=0.35 #Length of flow in m\n",
+ "b=0.02 #m\n",
+ "u_star_max=0.159 #m/s\n",
+ "\n",
+ "#Calculations\n",
+ "V_dot_by_L=-V_dot/L #Strength of the line source in m^2/s\n",
+ "u_max=(-u_star_max*V_dot_by_L)/b #Umax in m/s\n",
+ "\n",
+ "#Result\n",
+ "print \"The strength of the line source is\",round(V_dot_by_L,3),\"m^2/s\"\n",
+ "print \"The maximum velocity is\",round(u_max,2),\"m/s\"\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The strength of the line source is -0.314 m^2/s\n",
+ "The maximum velocity is 2.5 m/s\n"
+ ]
+ }
+ ],
+ "prompt_number": 17
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 10.10-9,Page No:535"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "\n",
+ "#Variable Decleration\n",
+ "V=10 #Velocity of fluid Flow in kh/hr\n",
+ "rho=999.9 #Density of water at 5\u02daC in kg/m^3\n",
+ "v=1.519*10**-6 #Kinematic Viscosity in m^2/s\n",
+ "#Conversion Factors\n",
+ "C1=1000\n",
+ "C2=3600\n",
+ "\n",
+ "#Calculations\n",
+ "Rex=(V*0.5*C1)/(v*C2) #Reynolds Number\n",
+ "\n",
+ "#Result\n",
+ "print \"The Reynolds Number is\",round(Rex)\n",
+ "print \"As a result the boundary layer is Transitional\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The Reynolds Number is 914344.0\n",
+ "As a result the boundary layer is Transitional\n"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 10.10-10,Page No:541"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "\n",
+ "#Variable Decleration\n",
+ "V=32 #Velocity of the fluid in m/s\n",
+ "x=1.1 #Distance in m\n",
+ "v=1.7*10**-5 #Kinematic Viscosity in m^2/s\n",
+ "#Conversion factor\n",
+ "C1=1000 \n",
+ "C2=3600\n",
+ "C3=100\n",
+ "\n",
+ "#Calculations\n",
+ "Rex=(V*x*C1)/(v*C2) #Reynolds Number\n",
+ "delta=4.91*x*C3/Rex**0.5 #Thickness of boundary Layer in cm\n",
+ "\n",
+ "#Result\n",
+ "print \"The Thickness of the boundary Layer is\",round(delta,2),\"cm\""
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The Thickness of the boundary Layer is 0.71 cm\n"
+ ]
+ }
+ ],
+ "prompt_number": 19
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 10.10-11, Page No:546"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "\n",
+ "#Variable decleration\n",
+ "x=0.3 #Length of the tunnel in m\n",
+ "V=4 #Optimised speed in m/s\n",
+ "R=0.15 #Radius of the tunnel in m\n",
+ "v=1.507*10**-5 #Kinematic Viscosity in m^2/s\n",
+ "\n",
+ "#Calculations\n",
+ "Rex=(V*x)/v #Reynolds Number\n",
+ "#Using the diplacement thickness formula\n",
+ "delta_star=(1.72*x)/Rex**0.5 #Displacement Thickness in m\n",
+ "#Applying the Continuity Equation\n",
+ "V_end=(V*R**2)/(R-delta_star)**2 #Velocity at the end in m/s\n",
+ "\n",
+ "#Result\n",
+ "print \"The end velocity should be\",round(V_end,2),\"m/s\"\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The end velocity should be 4.1 m/s\n"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 10.10-12, Page No:550"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "import matplotlib.pyplot as plt\n",
+ "%matplotlib inline\n",
+ "\n",
+ "#NOTE:The Notation has been changed here\n",
+ "\n",
+ "#Decleration of variables\n",
+ "V=10 #Velocity in m/s\n",
+ "x=1.52 #Length in m\n",
+ "v=1.516*10**-5 #Kinematic viscosity in m^2/s\n",
+ "u=[0,0.]\n",
+ "#Calculations\n",
+ "#Part(a)\n",
+ "\n",
+ "length=range(0,1500,20) #Array of length in mm\n",
+ "Re=(V*x)/v #Reynolds Number\n",
+ "y=transpose(length) #Transpose of the length matrix\n",
+ "#Laminar Boundary Layer\n",
+ "d_lam=(4.918*y)/((Re)**0.5)\n",
+ "#Turbulent Boundary Layer\n",
+ "d_tur=(0.16*y)/((Re)**(0.14285))\n",
+ "\n",
+ "#Part(b)\n",
+ "C_lam=0.664/((Re)**0.5) #Local Skin Friction coefficient for laminar boundary layer\n",
+ "C_tur=0.027/((Re)**0.14285) #Local Skin Friction coefficient for turbulent boundary Layer\n",
+ "\n",
+ "#Result\n",
+ "print \"The Reynolds Number is\",round(Re)\n",
+ "print \"The Local skin friction coefficient is\",round(C_lam,4),\"for laminar boundary layer\"\n",
+ "print \"The Local Skin friction coefficient is\",round(C_tur,4),\"for turbulent boundary layer\"\n",
+ "\n",
+ "plt.plot(y,d_tur,y,d_lam)\n",
+ "plt.xlabel('x,mm')\n",
+ "plt.ylabel('delta,mm')\n",
+ "plt.show()"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The Reynolds Number is 1002639.0\n",
+ "The Local skin friction coefficient is 0.0007 for laminar boundary layer\n",
+ "The Local Skin friction coefficient is 0.0038 for turbulent boundary layer\n"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEPCAYAAACp/QjLAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nBxERaeL/AxTcQojqb0i5AAAAAElFTkSuQmCC\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x10b5b5f90>"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Examples 10.10-15,Page No:563"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math\n",
+ "\n",
+ "#Variable Decleration\n",
+ "rho=1.204 #Density of the fluid in kg/m^3\n",
+ "w=0.5 #Width of the test object in m\n",
+ "U=10 #Velocity of the flow in m/s\n",
+ "delta1=0.042 #Boundary Layer thickness at 1 in m\n",
+ "delta2=0.077 #Boundary Layer thickness at 2 in m\n",
+ "\n",
+ "#Calculations\n",
+ "a=(delta2-delta1) \n",
+ "b=w*rho\n",
+ "c=U**2\n",
+ "Fd=(b*c*a*4)/45#Skin friction drag in N\n",
+ "\n",
+ "#Result\n",
+ "print \"The Skin Friction Drag is\",round(Fd,2),\"N\"\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "The Skin Friction Drag is 0.19 N\n"
+ ]
+ }
+ ],
+ "prompt_number": 15
+ }
+ ],
+ "metadata": {}
+ }
+ ]
+} \ No newline at end of file