Week 6 - Data analysis

Data analysis:- file parsing, and data extraction

Aim:-

write a script code that reads the data from the input file and takes column numbers as the input and plot the respective columns as separate images.

Basic performance calculation:-

• Calculate the area under the P-V diagram.
• Calculate the power output of this engine.
• Calculate its specific fuel consumption.

Given data:

The data file is https://drive.google.com/file/d/1SzKJngJcgJkvhJGGGDYY3JwLoc2o5_lQ/view?usp=sharing

Engine RPM = 1500

Fuel consumption = 20 micro grams per 1 stroke cycle

Procedure:-

1. import required libraries.
2. first, use the try command to open and read the file if a file does not exist except for an error and print "File not recognized. Please provide a valid CONVERGE output file" exit the system.
3. if a file exists read the file line by line using for loop.
4. first 5 lines of code are comments extract parameters from line 3 and their respective units from line4.
5. print serial number, parameters & units side by side.
6. Now ask the user to give serial numbers as x,y parameters as input.
7. Based on given inputs extract respective parameter, units, and their values.
8. plot the respective x,y columns as separate images.
9. Calculate the area under the P-V diagram, power output of this engine, & specific fuel consumption and print the results.

Main Code:-

# DATA ANALYSIS
import math
import numpy as np
import matplotlib.pyplot as plt

# separate the coloumn
data_file = 'engine_data.out'

try:
	file = open(data_file,'r')
except:
	print("File not recognized. Please provide a valid CONVERGE output file")
	sys.exit()

line_count = 1

for line in file:

	if line_count == 3: 
		parameters = line.split()

	if line_count == 4:
		units   = line.split()

	if line_count == 6:
		coloumn = line.split()

	line_count += 1
len_column = len(coloumn)
# print(len(coloumn))

# showing the quantities along with their coloumn number
print("%5s %15s %10s" %("S.No", "Parameter", "(unit)"))
for i in range(len_column):
	# print (i+1,'\t',parameters[i+1],'\t',units[i+1])
	print ("%5d %15s %10s" % (i+1, parameters[i+1], units[i+1]))

# enter the coloumn number for x and y axis
x = int(input('S.No number for x-axis parameter :'))
y = int(input('S.No number for y-axis parameter :'))

# print(x,y)
X_values = []
Y_values = []
P  = []
V  = []

line_count = 1
for line in open(data_file, 'r'):
	# print(line)
	
	if line_count == 3:
		x_parameter = line.split()[x]
		y_parameter = line.split()[y]

	if line_count == 4:
		x_axis = x_parameter + line.split()[x]
		y_axis = y_parameter + line.split()[y]

	if (line_count >= 6 and x <= len_column and y <= len_column):
		coloumn = line.split()
		X_values.append(float(coloumn[x-1]))
		Y_values.append(float(coloumn[y-1]))
		P.append(float(coloumn[1]))
		V.append(float(coloumn[7]))

	line_count += 1

# Ploting
plt.plot(X_values,Y_values)
plt.xlabel(x_axis)
plt.ylabel(y_axis)
plt.title(y_axis + 'vs' + x_axis)
plt.savefig(y_axis + 'vs' + x_axis + '.png')
plt.show()


# Performance calculation
area = np.trapz(P, V)
print('Area under pv diagram :', area, 'Mj')

rpm = 1500
workdone = area * 1e+3        # kj
power_in_kW = 2*math.pi*rpm * workdone/60
print('power output of this engine :', power_in_kW, 'Kw') 

fuel_consumed_per_stroke = 20e-6 
fuel_consumed_per_hour = 20e-6*rpm*60    # kg/hr
sfc = fuel_consumed_per_hour/power_in_kW
print('specific fuel consumption:', sfc, 'kg/kW-h')

Plots:-

Results: