Week 6 - Data analysis

AIM :TO WRITE A PYTHON PROGRAM WHICH READS THE ENGINE OUTPUT PARAMETER DATA FILE AND PERFORM THE REQUIRED OBJECTIVES

The programming language used is Python

2.OBJECTIVE :

1. To read the data from a given data file.
2. To take the file name as an input from the user and check whether the file is present or not.
3. To plot a graph between 2 parameters given by the user as an input.
4. To do basic performance calculation by calculating the area under the P-V diagram, the power output of this engine, and specific fuel consumption.

3.PROBLEM STATEMENT :

Read the data from a given file named 'engine_data.out' using python program, plot a curve between 2 engine parameters (parameters to be given by the user as an input) and perform basic performance calculation by calculating the area under the P-V diagram, the power output of this engine(Assume that RPM is 1500) and specific fuel consumption (engine consumed 20 micrograms of fuel (per 1 stroke cycle))

4.PROCEDURE

To solve the above-given problem statement, the following procedure is followed:

1. Using a python program initially the name of the data file is taken as an input from the user and checked whether the file is present or not if the file is not present then the program is terminated.
2. Then the file is opened and data is read line by line and stored.
3. The name of parameters, their units, and their column number are stored as an array and displayed in form of a table for the user to select the required columns.
4. Then the column no for the independent parameter (x-axis) and dependent parameter (y-axis) is taken from the user and the values of that column are extracted from the data file and further plotted.
5. At the end the values under pressure and volume column are extracted from the data file and the area under the PV diagram is calculated which gives the work done, then multiplying it with speed the value of power output by the engine is calculated, and at the end, the specific fuel consumption is also calculated and displayed. 

Python Code

#DATA ANALYSIS OF ENGINE DATA

#Importing the modules
import numpy as np 
import matplotlib.pyplot as plt 
from scipy.integrate import simps



filename = input("Enter the name of CONVERGE output filename with extension(.out):")

#COMPATIBILITY CHECK

#Checking if the file is a valid CONVERGE output file
try:
	f = open(filename)
	f.close()
except FileNotFoundError:
	print('File not recognized. Please provide a valid CONVERGE output file')
	exit()

#Checking if data is present in the CONVERGE output file
i=0
for line in open(filename):
	if '#' not in line:
		break
	i = i+1

j=0
for line in open(filename):
	j=j+1
	if j>i:
		break

if j==i:
	print('No data present in the CONVERGE output file')
	exit()



#DATA EXTRACTION

i=0
for line in open(filename):
	if i==2:
		c = line.split() #Storing unit of variables in list c
		i=0
		break

	if i==1:
		b=line.split()  #Storing names of variables in list b
		i = i+1

	if 'column' in line.split():
		a = line.split() #Storing column numbers of variables in list a
		i=1


a.remove("column") #Removing column from list a
a.remove("#") #Removing # from list a
a = np.array(a,dtype=np.int) #Converting data to integer
b.remove("#") #Removing # from list b
c.remove("#")  #Removing # from list c
num_col = len(a) #Number of columns/number of variables


#GETTING THE DATA

data_counter = 0 #Initializing number of data points counter variable
data = np.arange(0,num_col)

for line in open(filename):
	if '#' not in line:
		d = line.split() #Storing current data line as in d
		d = np.array(d,dtype=np.float32) #Converting list data to float array
		data = np.vstack([data,d]) #Stacking the float array d in data matrix
		data_counter = data_counter + 1 

data = np.delete(data,0,0) #Deleting the first row used to initialize the array



#DATA VISUALIZER

print('Type -')

for i in a:
	print('{} for {}'.format(i,b[i-1]))


print(' ')
x = input("Do you want a plot between any two variables? (y/n): ")


while(x.lower()=='y'):
	cn1 = input("Enter the clumn number of the variable along X-axis (Refer input map above):")
	cn2 = input("Enter the clumn number of the variable along Y-axis (Refer input map above):")
	cn1 = int(cn1)
	cn2 = int(cn2)
	plt.figure()
	plt.plot(data[:,cn1-1],data[:,cn2-2])
	plt.xlabel('{} {}' .format(b[cn1-1],c[cn1-1]))
	plt.ylabel('{} {}' .format(b[cn2-1],c[cn2-1]))
	plt.title('{} {} vs {} {}' .format(b[cn2-1],c[cn2-1],b[cn1-1],c[cn1-1]))
	z = "n"
	z = input("Do you want to save the plot? (y/n):")
	if(z.lower()=='y'):
		plt.savefig("{}-{}.png".format(b[cn2-1],b[cn1-1]))

	plt.show()
	print(' ')
	x = input("Do you want to plot any other two variables? (y/n):")

print(' ')


x = input("Do you want a single variable plot? (y/n): ")
while(x.lower()=='y'):
	cn = input("Enter the column number of the variable (Refer input map above): ")
	cn = int(cn)
	plt.figure()
	plt.plot(np.arange(0,data_counter),data[:,cn-1])
	plt.xlabel('Data point number')
	plt.ylabel('{} {} '.format(b[cn-1],c[cn-1]))
	z = "n"
	z = input("Do you want to save the plot? (y/n): ")

	if(z.lower()=='y'):
		plt.savefig("{}.png".format(b[cn-1]))

	plt.show()
	print(' ')
	x = input("Do you want any other single variable plot? (y/n): ")
print(' ')



#CALCULATIONS

print('PERFORMANCE OF THE ENGINE')

#Work done
b1 = [i.lower() for i in b]
pressure_column = b1.index('pressure')
volume_column = b1.index('volume')
pressure = data[:,pressure_column]
volume = data[:,volume_column]
A = 0  #Area under the P-V curve
A = simps(pressure,volume,even='first')*np.power(10,6) #Work per cycle(J)

#Power output
rpm = float(input('Enter the rpm of the engine at which data was collected: ')) #Rotation per min
f = float(input('Enter the value of the fuel consumed per cycle (in micrograms): ')) #Fuel consumption per cycle (Microgram)
n = rpm/(2*60) #Number of cycle per second for 4-stroke engine
P = A*n #Power output(W) at speed N (rad/s)

#Specific fuel consumption
f = (f*n*3600)/np.power(10,9) #Fuel consumption (Kg/hr)
sfc = (f*1000)/P  #Specific fuel consumption(Kg/hr.KW)

#Results
print('Area under the P-V curve (i.e. the Work done per cycle) = {} J'.format(A))
print('Power output at {} rpm = {} W'.format(rpm,P))
print('Specific fuel consumption = {} Kg/KW.hr'.format(sfc))

 RESULTS

PLOTS