Week 6 - Data analysis

AIM :

To Write code in PYTHON that can solve data visualization, compatibility check and basic performance calculation.

OBJECTIVE:

1. To perform Data Analysis.

2. Plot a graph between any two Column vectors.

3. Calculate the area under the P-V diagram.

4. Calculate the power output of this engine.

5. Calculate engine specific fuel consumption.

CODE:

import matplotlib.pyplot as plt

import numpy as np

# Initializing empty lists for storing the data

value1 = []

value2 = []

pressure = []

volume = []

label1 = ""

label2 = ""

# Enter the name of the CONVERGE output file

file_name = input("Enter the file name in .out format: ")

# Checking the file name and conditions

if file_name == 'engine_data.out':

with open(file_name, 'r') as file:

lines = file.readlines()

# Extracting labels and units from specific lines

labels = lines[2].split()

units = lines[3].split()

print('List of parameters available for plotting:')

for i, (label, unit) in enumerate(zip(labels[1:], units[1:]), start=0):

print(f"{i}. {label} {unit}")

# User input for parameters for x and y axes

a = int(input("Enter the parameter index for the x-axis: "))

b = int(input("Enter the parameter index for the y-axis: "))

# Reading data and appending to respective lists

for line in lines[5:]: # Start reading from the 6th line

data = line.split()

value1.append(float(data[a]))

value2.append(float(data[b]))

pressure.append(float(data[1]))

volume.append(float(data[7]))

#calculating the area under the P-V diagram using trapz(y,x)

area=np.trapz(pressure,volume)*1000

print('Area under the P-V diagram: ',area,'J')

#calculating the power output of the engine (assuming a RPM of 1500 and 4-stroke)

N = 1500 #engine RPM

n = 2 #no. of revolution per cycle in four stroke engine

power=(area*N)/(n*746)

print('Power: ',power,'HP')

#calculating the engine specific fuel consumption (assuming it consumes 20gm of fuel in one stroke)

fc = 20 #fuel consumed per cycle in micro gram

ffr = (fc*(N/n))/1000000 #fuel flow rate

sfc= ffr/power

print('fuel flow rate: ',ffr,'g/m')

print('Specific Fuel Consumption: ',sfc,'g/hp-m')

# Assigning labels for axes

label1 = labels[a + 1] + f" {units[a + 1]}"

label2 = labels[b + 1] + f" {units[b + 1]}"

# Plotting the data

plt.plot(value1, value2)

plt.xlabel(label1)

plt.ylabel(label2)

plt.title(f"Plot of {label2} vs {label1}")

plt.savefig(f"{label2}vs{label1}.png")

plt.show()

#plotting area under PV

plt.plot(volume,pressure,color='red',label='pv curve')

plt.fill_between(volume, pressure,color='green',label='area under curve')

plt.xlabel("volume")

plt.ylabel("pressure")

plt.legend()

plt.savefig("area under PV curve")

plt.show()

else:

print('File not recognized. Please provide a valid CONVERGE output file')

RESULT:

plotting list and output results for area under the pv curve, power, specific fuel consumption.

Mean_Temp (K) VS Density (kg/m^3)

Pressure (MPa) VS Crank (DEG)

Pressure (MPa) VS Kin_Visc (m^2/s)

Pressure (MPa) VS Volume (m^3)

Volume (m^3) VS Crank (DEG)

Mean_Temp (K) VS Crank (DEG)

C_v (J/kg-K) VS Crank (DEG)

C_p (J/kg-K) VS Crank (DEG)

Area under PV curve

RESULT :

Hence the data analysis using the large no. of data points and the visualization graph is shown according to the user inputs.