def coefficient_LLT(AC, velocity, AOA):
Au_P = [0.1828, 0.1179, 0.2079, 0.0850, 0.1874]
Al_P = Au_P
deltaz = 0
# Determine children shape coeffcients
AC_u = list(data.values[i, 0:4])
Au_C, Al_C, c_C, spar_thicknesses = calculate_dependent_shape_coefficients(
AC_u, psi_spars, Au_P, Al_P, deltaz, c_P, morphing=morphing_direction)
# Calculate aerodynamics for that airfoil
airfoil = 'optimal'
x = create_x(1., distribution='linear')
y = CST(x, 1., [deltaz / 2., deltaz / 2.], Al=Al_C, Au=Au_C)
# Create file for Xfoil to read coordinates
xf.create_input(x, y['u'], y['l'], airfoil, different_x_upper_lower=False)
Data = xf.find_coefficients(airfoil,
AOA,
Reynolds=Reynolds(10000, velocity, c_C),
iteration=100,
NACA=False)
deviation = 0.001
while Data['CL'] is None:
Data_aft = xf.find_coefficients(airfoil,
AOA * deviation,
Reynolds=Reynolds(
10000, velocity, c_C),
iteration=100,
NACA=False)
Data_fwd = xf.find_coefficients(airfoil,
AOA * (1 - deviation),
Reynolds=Reynolds(
10000, velocity, c_C),
iteration=100,
NACA=False)
try:
for key in Data:
Data[key] = (Data_aft[key] + Data_fwd[key]) / 2.
except:
deviation += deviation
alpha_L_0 = xf.find_alpha_L_0(airfoil,
Reynolds=0,
iteration=100,
NACA=False)
coefficients = LLT_calculator(alpha_L_0,
Data['CD'],
N=100,
b=span,
taper=1.,
chord_root=chord_root,
alpha_root=AOA,
V=velocity)
lift = coefficients['C_L']
drag = coefficients['C_D']
return lift, drag
import numpy as np
import matplotlib.pyplot as plt
import aeropy.xfoil_module as xf
from aeropy.CST.module_2D import *
from aeropy.aero_module import Reynolds
from aeropy.geometry.airfoil import CST, create_x
# Au = [0.23993240191629417, 0.34468227138908186, 0.18125405377549103,
# 0.35371349126072665, 0.2440815012119143, 0.25724974995738387]
# Al = [0.18889012559339036, -0.24686758992053115, 0.077569769493868401,
# -0.547827192265256, -0.0047342206759065641, -0.23994805474814629]
Au = [0.172802, 0.167353, 0.130747, 0.172053, 0.112797, 0.168891]
Al = Au
# c_avian = 0.36 #m
# deltaz = 0.0093943568219451313*c_avian
c_avian = 1.
deltaz = 0
airfoil = 'avian'
x = create_x(1., distribution='linear')
y = CST(x, 1., [deltaz / 2., deltaz / 2.], Au=Au, Al=Al)
# Create file for Xfoil to read coordinates
xf.create_input(x, y['u'], y['l'], airfoil, different_x_upper_lower=False)
print('Reynolds: ', Reynolds(10000, 30, c_avian))
Data = xf.find_coefficients(airfoil,
0.,
Reynolds=Reynolds(10000, 30, c_avian),
iteration=100,
NACA=False)
print(Data)
import matplotlib.pyplot as plt
import numpy as np
from aeropy.geometry.airfoil import create_x, CST
plt.figure()
A = [1., 2., 1.]
deltaz = 0.2
x = create_x(1, distribution='polar')
for i in range(len(A)):
A_i = [0, 0, 0]
A_i[i] = A[i]
y = CST(x, 1., deltaz, A_i)
plt.plot(x, y, '--')
y = CST(x, 1., deltaz, A)
plt.plot(x, y, 'k')
plt.axis('equal')
plt.grid()
plt.xlim([0, 1])
plt.xlabel('$\psi$', fontsize=14)
plt.ylabel(r'$\xi$', fontsize=14)
plt.show()
plt.figure()
A = [1.]
N1 = [.5, 1., .5]
N2 = [1., 1., .5]
deltaz = 0.0
x = create_x(1, distribution='polar')
for i in range(len(N1)):
N1_i = N1[i]
def aerodynamic_performance(AC, psi_spars, Au_P, Al_P, c_P, deltaz, alpha, H,
V):
morphing_direction = 'forwards'
air_data = air_properties(H, unit='feet')
density = air_data['Density']
dyn_pressure = .5 * density * V**2
# Generate dependent shape coefficients
# try:
Au_C, Al_C, c_C, spar_thicknesses = calculate_dependent_shape_coefficients(
AC, psi_spars, Au_P, Al_P, deltaz, c_P, morphing=morphing_direction)
# print 'Reynolds: ', Reynolds(H, V, c_C)
# Generate aifoil file
airfoil = 'test'
x = create_x(1., distribution='linear', n=300)
y = CST(x, 1., [deltaz / 2., deltaz / 2.], Au=Au_C, Al=Al_C)
# Get strain data
strains, av_strain = calculate_strains(Au_P, Al_P, c_P, Au_C, Al_C, c_C,
deltaz, psi_spars, spar_thicknesses)
intersections = intersect_curves(x, y['l'], x, y['u'])
print(intersections, intersections[0][1:])
if len(intersections[0][1:]) == 0:
# print y
create_input(x, y['u'], y['l'], airfoil, different_x_upper_lower=False)
# Get aerodynamic data
print(airfoil, alpha, Reynolds(H, V, c_C))
Data = find_coefficients(airfoil,
alpha,
Reynolds=Reynolds(H, V, c_C),
iteration=200,
NACA=False,
delete=True,
PANE=True,
GDES=True)
# plot_airfoil(AC, psi_spars, c_P, deltaz, Au_P, Al_P, image = 'save', iteration=counter, dir = airfoil+'_dir')
# filtering data (for now I only care about negative strains
str_output = {
'CL': Data['CL'],
'CD': Data['CD'],
'CM': Data['CM'],
'av_strain': av_strain,
'Au_C': Au_C,
'Al_C': Al_C,
'spars': psi_spars
}
if Data['CM'] == None:
str_output['lift'] = None
str_output['drag'] = None
str_output['moment'] = None
else:
str_output['lift'] = Data['CL'] / dyn_pressure / c_C,
str_output['drag'] = Data['CD'] / dyn_pressure / c_C,
str_output['moment'] = Data['CM'] / dyn_pressure / c_C
for i in range(len(strains)):
str_output['strain_' + str(i)] = strains[i]
# Writing to a text file
# f_worker = open(str(airfoil) + '.txt', 'wb')
# for i in range(len(key_list)):
# if i != len(key_list)-1:
# if key_list[i][:1] == 'Au':
# f_worker.write('%f\t' % str_output[key_list[i][:1]+'_C'][int(key_list[i][-1])])
# else:
# else:
# if key_list[i][:1] == 'Au':
# f_worker.write('%f\n' % str_output[key_list[i][:1]+'_C'][int(key_list[i][-1])])
else:
str_output = {
'CL': 1000,
'CD': None,
'CM': None,
'av_strain': av_strain,
'spars': psi_spars,
'Au_C': Au_C,
'Al_C': Al_C,
'lift': None,
'drag': None,
'moment': None
}
for i in range(len(strains)):
str_output['strain_' + str(i)] = strains[i]
# except:
# str_output = {'CL':None, 'CD':None, 'CM':None, 'av_strain':None,
# 'Au_C':[None]*len(AC), 'Al_C': [None]*len(AC),
# 'lift': None, 'drag': None, 'moment':None,
# 'strains':[None]*(len(AC)-1), 'spars':psi_spars}
return str_output
def aircraft_range_LLT(AC, velocity, AOA):
def to_integrate(weight):
# velocity = 0.514444*108 # m/s (113 KTAS)
span = 10.9728
RPM = 1800
a = 0.3089 # (lb/hr)/BTU
b = 0.008 * RPM + 19.607 # lb/hr
lbhr_to_kgs = 0.000125998
BHP_to_watt = 745.7
eta = 0.85
thrust = weight / lift_to_drag
power_SI = thrust * velocity / eta
power_BHP = power_SI / BHP_to_watt
mass_flow = (a * power_BHP + b)
mass_flow_SI = mass_flow * lbhr_to_kgs
SFC = mass_flow_SI / thrust
dR = velocity / g / SFC * lift_to_drag / weight
return dR * 0.001 #*0.0005399
Au_P = [0.1828, 0.1179, 0.2079, 0.0850, 0.1874]
Al_P = Au_P
deltaz = 0
# Determine children shape coeffcients
AC_u = list(data.values[i, 0:4])
Au_C, Al_C, c_C, spar_thicknesses = calculate_dependent_shape_coefficients(
AC_u, psi_spars, Au_P, Al_P, deltaz, c_P, morphing=morphing_direction)
# Calculate aerodynamics for that airfoil
airfoil = 'optimal'
x = create_x(1., distribution='linear')
y = CST(x, 1., [deltaz / 2., deltaz / 2.], Al=Al_C, Au=Au_C)
# Create file for Xfoil to read coordinates
xf.create_input(x, y['u'], y['l'], airfoil, different_x_upper_lower=False)
Data = xf.find_coefficients(airfoil,
AOA,
Reynolds=Reynolds(10000, velocity, c_C),
iteration=100,
NACA=False)
deviation = 0.001
while Data['CL'] is None:
Data_aft = xf.find_coefficients(airfoil,
AOA * deviation,
Reynolds=Reynolds(
10000, velocity, c_C),
iteration=100,
NACA=False)
Data_fwd = xf.find_coefficients(airfoil,
AOA * (1 - deviation),
Reynolds=Reynolds(
10000, velocity, c_C),
iteration=100,
NACA=False)
try:
for key in Data:
Data[key] = (Data_aft[key] + Data_fwd[key]) / 2.
except:
deviation += deviation
alpha_L_0 = xf.find_alpha_L_0(airfoil,
Reynolds=0,
iteration=100,
NACA=False)
coefficients = LLT_calculator(alpha_L_0,
Data['CD'],
N=100,
b=span,
taper=1.,
chord_root=chord_root,
alpha_root=AOA,
V=velocity)
lift_to_drag = coefficients['C_L'] / coefficients['C_D']
g = 9.81 # kg/ms
fuel = 56 * 6.01 * 0.4535 * g
initial_weight = 1111 * g
final_weight = initial_weight - fuel
return scipy.integrate.quad(to_integrate, final_weight, initial_weight)[0]