Data analysis-Engine data file

Aim:

To perform data analysis using python.

Objectives:

1. To visualize the engine data.
2. To check Compatability of file.
3. To Basic performance calculation.

Problem Statement:

Data visualizer

• Your script should take column numbers as the input and plot the respective columns as separate images
• Each file should be saved by the name of the column
• The plot labels should be extracted from the file. If, I request for a plot between column 1 (crank angle) and column 8(volume), then the label information should automatically be extracted and must appear as labels in the plots. THIS SHOULD NOT BE DONE MANUALLY

Compatability check

• You code should exit gracefully, if a non-compatible file is provided as an input. It should say something like "File not recognized. Please provide a valid CONVERGE output file"

Basic performance calculation

• Calculate the area under the P-V diagram. P is in column 2 and V is in column 8.
• Calculate the power output of this engine. Assume that RPM is 1500
• This engine consumed 20 micro grams of fuel (per 1 stroke cycle). Calculate its specific fuel consumption.

Theory:

Data analysis is a process of inspecting, cleansing, transforming and modelling data with the goal of discovering useful information, informing conclusions and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.[1]

Code:

#  Data analysis
# 1.To visualize the engine data.
# 2.To check Compatability of file.
# code by Abhishek Savakar

# importing modules
from matplotlib.pyplot import *

# defining arrays and inputs
line_count = 1
c_num = []
c_name = []
c_units = []
count = 1
t_1 = []
t_2 = []

#  for a plot between column 1 (crank angle) and column 8(volume)
t1 =0
t2 = 7

# to check compatibility of the file
# if any errors in try block the program will not crash
try:
    engine_data = open('engine_data.out', 'r')
    for line in engine_data:
        for i in range(0, 19):
            # i >=2 because there are two extra elements in that row before numbering in the file.
            if i >= 2:
                if count == 2:
                    # appending all column number, count==2 because row 2 has column names
                    c_num.append(int(line.split()[i]))

        for j in range(0, 18):
            # j >=1 because there are one extra elements in that row in the file.
            if j >= 1:
                # appending all names of the column. count==3 because column names are in 3rd row
                if count == 3:
                    c_name.append(line.split()[j])

                # appending all units of column, count==4 because column units are in 4th row
                elif count == 4:
                    c_units.append(line.split()[j])

        # appending all values and avoiding # in file
        if '#' not in line:
            if count >= 6:
                t_1.append(float(line.split()[t1]))
                t_2.append(float(line.split()[t2]))
        count += 1

    # plotting the graph and automatically labelling.
    figure()
    plot(t_1, t_2)
    title('plot of ' + str(c_name[t2]) + ' V/S ' + str(c_name[t1]))

    xlabel(str(c_name[t1]) + str(c_units[t1]))
    ylabel(str(c_name[t2]) + str(c_units[t2]))
    savefig(str(c_name[t2]) + ' vs ' + str(c_name[t1]))

    show()
    # closing the file.
    engine_data.close()

# this block will run only if error occured
# it will show which error has occured..
except Exception as error:
    print(error)

# this block will run if there is no error
else:
    print("NO Errors Occured")

# it always runs no matter what if error occured in try: or not...
# its useful printing or using must commands of program
finally:
    pass

Code output:

Code output when a non-compatible file is provided as an input:

output screen showing No such file or directory: 'engine_data.out'. when the file was not present in the folder containing the code.

when Ran succesfully:

Output screen showing No errors occured.

Output plots:

other sample plots when column number changed.

Basic performance calculation

Code:

#  Data analysis
# 3.To Basic performance calculation.
# code by Abhishek Savakar

# importing modules
from matplotlib.pyplot import *
from scipy.integrate import *

# defining arrays and inputs
line_count = 1
c_num = []
c_name = []
c_units = []
count = 1
t_1 = []
t_2 = []

#  for a plot between column 1 (crank angle) and column 8(volume)
t1 =7
t2 = 1

# to check compatibility of the file
# if any errors in try block the program will not crash
try:
    engine_data = open('engine_data.out', 'r')
    for line in engine_data:
        for i in range(0, 19):
            # i >=2 because there are two extra elements in that row before numbering in the file.
            if i >= 2:
                if count == 2:
                    # appending all column number, count==2 because row 2 has column names
                    c_num.append(int(line.split()[i]))

        for j in range(0, 18):
            # j >=1 because there are one extra elements in that row in the file.
            if j >= 1:
                # appending all names of the column. count==3 because column names are in 3rd row
                if count == 3:
                    c_name.append(line.split()[j])

                # appending all units of column, count==4 because column units are in 4th row
                elif count == 4:
                    c_units.append(line.split()[j])

        # appending all values and avoiding # in file
        if '#' not in line:
            if count >= 6:
                t_1.append(float(line.split()[t1]))
                t_2.append(float(line.split()[t2]))
        count += 1

    # closing the file.
    engine_data.close()

    #To Calculate the area under the P-V diagram
    area=simps(t_2,t_1)*pow(10,6)
    print('Area under pv curve:',area,'Joules')

    # To Calculate the power output of this engine
    # give
    N=1500
    n=1
    s=4
    x=2

    p=n*area*N/(60*1000*x)
    print('The output power of engine:',p,'KW')

    #To Calculate its specific fuel consumption
    #given
    m=20
    #fuel consumption
    fc=N*60*(m*pow(10,-9)/2)
    # specific fuel consumption
    sfc=fc/p
    print('Specific Fuel Consumption:',sfc,'(kg/hr)/KW')


# this block will run only if error occured
# it will show which error has occured..
except Exception as error:
    print(error)

# this block will run if there is no error
else:
    print("NO Errors Occured")

# it always runs no matter what if error occured in try: or not...
# its useful printing or using must commands of program
finally:
    pass

output screen:

Reference:

[1]. https://en.wikipedia.org/wiki/Data_analysis