Week 6 - Data analysis

Aim:

• To parse the given engine data and write a scrpit to plot the user defined data sets.
• To check the compatibilty of the file.
• Calculate the area under PV diagram, Power and the specific fuel consumption.

Program Logic:

1. At first,the compatibility check of the file is performed using the "try,except" command.
2. Once the compatibility check is performed, the engine data file is opened and the available datasets are extracted and printed.
3. The available datasets has a unique serial number, A user input is asked with respect to the serial numbers of the data to plot the curve.
4. The user input is stored and is used as the serial number of the datasets whose curves are to be plotted. The datsets are stored in seperate lists.
5. The same serial numbers are used to extract the Labels and units of the dataset.
6. The list is then plotted given the desired output.
7. The area under PV diagram is calculated using the "trapz" command.
8. The Power and Specific fuel consumption is then calculated using the concerned formulae.

Program:

# FILE PARSING
#Importing Libraries:
import math
import matplotlib.pyplot as plt 
import numpy as np 

#Intializations:
a = []
b = []
line_ct = []
ct = 1

#Compatibility check:
try:
        f = open('engine_data.out')
        print('File opened successfully')
        f.close()
except FileNotFoundError:
        print('File not recognized. Please provide a valid CONVERGE output file')

#Extracting Available Datasets:
f1 = open('engine_data.out')
print('The datasets avaible are:')
for lineno in f1:
        for i in range(1,18):
                if ct == 3:
                        print([i],lineno.split()[i])
        ct = ct + 1
f1.close()

#Taking User Input:
c = input('Enter the serial number of the Data which is to be plotted in x axis :')
d = input('Enter the serial number of the Data which is to be plotted in y axis :')
c = int(c)
d = int(d)

#Extracting User defined Data:
f2 = open('engine_data.out')
for line in f2:
        if '#' not in line:
                a.append(float(line.split()[c-1]))
                b.append(float(line.split()[d-1]))
f2.close()

#Extracting Data for X and Y Label:
f3 = open('engine_data.out')
ct2 = 1
for line in f3:
        for j in range(1,18):
                if ct2==3: # Extracting Label Data
                        e = str(line.split()[c])
                        f = str(line.split()[d])
                if ct2==4: # Extracting Units
                        g = str(line.split()[c])
                        h = str(line.split()[d])
        ct2 = ct2 + 1
f3.close()

#Creating Labels:
k = e + g
l = f + h

#Calculating Work Done,Power and Specific Fuel Consumption:
p = []
v = []
f4 = open('engine_data.out')
for lines in f4:
        if '#' not in lines:
                p.append(float(lines.split()[1]))
                v.append(float(lines.split()[7]))
f4.close()
RPM = 1500
fps = 20*(10**-6)
Workdone = round((np.trapz(p,v)*1000),3)
Power = round((2*math.pi*RPM*Workdone/60),3)
fph = (fps*RPM*(0.5/60))*3600
SFC = round((fph/Power),4)

print('Workdone :',Workdone,'KJ')
print('Power :',Power,'KW')
print('Specific Fuel Consumption :',SFC,'g/KWH')

#Plotting Data:
plt.plot(a,b)
plt.xlabel(k)
plt.ylabel(l)
plt.show()

Output:

Result:

• A scrpit is written to plot the user defined data sets.
• Compatibilty check is performed.
• Area under PV diagram, Power and the specific fuel consumption are calculated.