Week 6 - Data analysis

AIM:

To write a program to create a data visualizer for an engine using File Parsing

OBJECTIVE:

• To display engine performance details
• To display parametric plots for various factors affecting an engines performance, based on the users choice

THEORY:

Equations used:

• Work Done (WD)= Area under the P-V diagram, which is calculated using Simpson's method.
• Power output (P)=`(WD*N*n)/(60*2*1000)`
  
  • `WD`- work done
  • `N`-speed of the engine
  • `n`-no. of cylinders
• Specific Fuel Consumption = `F_c/P`
  
  • `F_c`-Fuel consumption/stroke
  • `P`-Power output

Inputs:

• `N`= 1500
• `n`= 1
• `F_c`= 20

PROGRAM CODE:

# -*- coding: utf-8 -*-
"""
python program to perform data analysis on file and output plot and desired results

-Raaghul V
"""


# Generating plots for 2 random quantities by analysis data using file parsing
import math
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import simps

#Compatability check using try-except block
try:
  open('engine_data.out')
  check=1
except:
  print('File not recognized. Please provide a valid CONVERGE output file')
  check=0
if check==1:

  #Creating empty lists to store data in each respective column from the file
  data=[]
  volume = []
  pressure = []
  
  x1=open('engine_data.out','r') # storing the readable data in a variable

  for i in x1:
        if '#' not in i:
          a1=i.split() #splitting the string w.r.t spaces
          data.append(a1) #adding each line as a nested list
          
          #adding P and V to their respective lists
          volume.append(float(a1[7])) 
          pressure.append(float(a1[1]))

  #Plotting the P-V diagram
  plt.plot(volume, pressure, color = 'orange', linewidth = 3)
  plt.xlabel('Volume(m^3)')
  plt.ylabel("Pressure(MPa)")
  plt.title("P-V Diagram")
  plt.grid()
  plt.savefig("P-V Diagram")
  plt.show()

      
  #Basic performance calculation

  #Input parameters
  
  #Speed
  rpm = 1500
  rps = 1500/60
  s_c= rps/2

  #Fuel consumption/stroke cycle
  f_c= 20
  n = 1 #No of cylinders
  print("\n")
  print("\n")
  print("ENGINE PERFORMANCE DETAILS")
  print("\n")
  #Calculating area under the curve using Simpson's function/rule
  #Area under curve=Work done by the engine
  area = simps(pressure, volume)
  print('1.Area under the curve:',area,'units')
  area = area*pow(10,6)
  print('2.Work Done:',area,'J')
  

  #Calculating Power Output and Specific Fuel Consumption(SFC)
  p_o= n*area*s_c/(1000)
  sfc= (f_c*pow(10,-6)*s_c*3600)/(p_o*1000)
  print('3.Power Ouput:',p_o,'KW')  
  print('4.Specific Fuel Consumption:',sfc,'(kg/hr)/KW')


          
  #Converting columns into rows for ease
  t=np.transpose(data)
  fl=t.astype(np.float)#convert

  #List containing axes labels and units
  labels = ['Crank Angle','Pressure','Maximum Pressure','Minimum Pressure','Mean Temperature','Maximum Temperature','Minimum Temperature','Volume','Mass','Density','Integrated HR','HR Rate','Cp','Cv','Gamma','Kinematic Viscosity','Dynamic Viscosity']
  units = ['(DEG)','(MPa)','(MPa)','(MPa)','(K)','(K)','(K)','(m^3)','(kg)','(kg/m^3)','(J)','(J/time)','(J/kgK)','(J/kgK)','','(m^2/s)','(Ns/m^2)']
  print("\n")
  print("\n")
  #User Interface
  print('__________________________________________________________________________________DATA VISUALIZER FOR AN ENGINE_______________________________________________________________________________')
  print('\n')
  print(' 1.Crank\n 2.Pressure\n 3.Maximum Pressure\n 4.Minimum Pressure\n 5.Mean Temperature\n 6.Maximum Temperature\n 7.Minimum Temperature\n 8.Volume\n 9.Mass\n 10.Density\n 11.Integrated HR\n 12.HR Rate\n 13.Cp\n 14.Cv\n 15.gamma\n 16.Kinematic Viscosity\n 17.Dynamic Viscosity')
  print('\n')
  x0=int(input("Enter the number of plots you want to generate"))
  for i in range(0,x0):
    X=int(input('Enter the key for the component you need on the X-axis:'))
    Y=int(input('Enter the key for the component you need on the Y-axis:'))
    if X>0 and Y>0 and X<18 and Y<18:
      #Plotting graphs based on the user's choice
      plt.plot(fl[X-1],fl[Y-1],linewidth=3,color='RED')
      plt.title(labels[X-1]+ ' VS ' +labels[Y-1])
      plt.xlabel(labels[X-1] + ' ' + units[X-1])
      plt.ylabel(labels[Y-1] + ' ' + units[Y-1],)
      plt.savefig(labels[X-1] + ' vs ' + labels[Y-1] + '.png')
      plt.grid()
      plt.show()
    else:
      print("INVALID OPTION")

  print('__________________________________________________________________________________END__________________________________________________________________________________________')

PROCEDURE

• Import the neccesary modules used for calculations and plotting graphs
• Use a try-except block to check the file compatibilty before proceeding futher.
• Read the file and add all the data to a list, awaiting sorting.
• Sort the data and organize them into systemic lists.
• Plot graphs based on the respective lists.
• A User interface is coded for ease of usage
• The program allows the user to generate any plot of choice by selecting the neccesary factors according to the legend given.

RESULTS:

SS of Output console:

SS of saved images:

Output plots:

CONCLUSION:

Hence, using the Python, we created a data visualizer for an engine with the data recived from a Converge simulation.