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main_pxfoil.py
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main_pxfoil.py
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import numpy
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import pyxfoil as pxf
from pyxfoil import set_xfoilexe, set_workdir
from pathlib import Path
import json
set_workdir("results")
set_xfoilexe("E:/Downloads/Airfoil-Optimization-master/Airfoil-Optimization-master/xfoil/xfoil.exe")
def average_value(x_values, y_values):
"""
Calculates the average value as area under curve (AUC) divided by domain length.
Args:
x_values: A list of x values representing the independent variable.
y_values: A list of y values representing the dependent variable.
Returns:
The average value (AUC / domain length).
"""
dx = (x_values[-1] - x_values[0])/len(x_values)
area = dx*0.5*(y_values[0] + y_values[-1] + np.sum(y_values[1:-1])*2)
average_value = area / (x_values[-1] - x_values[0])
return average_value
filenames = []
cl = []
cd = []
cm = []
clcd=[]
res = [1e5, 3e5, 5e5]
for file in Path('airfoilsdb').glob("*"):
try:
airfoil = pxf.Xfoil('airfoil')
path='airfoilsdb/'+file.name
cll = []
cdd = []
cmm =[]
clocd = []
airfoil.points_from_dat(path)
airfoil.set_ppar(180)
for re in res:
polar = airfoil.run_polar(0, 10, 2, mach=0.1, re=re)
cll.append(polar.cl)
cdd.append(polar.cd)
cmm.append(polar.cm)
clocd.append(polar.clocd)
cl.append(cll)
cd.append(cdd)
cm.append(cmm)
clcd.append(clocd)
filenames.append(file.name)
except:
print('errorr:'+file.name)
print(cl)
print(cd)
print(filenames)
dict = {'filenames': filenames, 'cl': cl, 'cd': cd, 'cm': cm, 'clcd': clcd}
print(dict)
df = pd.DataFrame(dict)
df['cl'] = df['cl'].apply(json.dumps)
df['cd'] = df['cd'].apply(json.dumps)
df['cm'] = df['cm'].apply(json.dumps)
df['clcd'] = df['clcd'].apply(json.dumps)
df.to_csv('data.csv')