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propeller.py
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import numpy as np
from AirfoilData import get_aifoildata
import time
import matplotlib.pyplot as plt
import pickle
start_time = time.time()
# Global Inputs
g=9.81
rho = 1.225
dyn_viscosity = 1.789e-5
kin_viscosity = dyn_viscosity/rho
a = 340
B=2
foil = 'e395.DAT'
foilpath = foil.replace(" ", "_")
def design(D, T_hv, V):
#print(T_hv)
nr_sect = 100
D_hub = D/5.75
mach_tip = 0.6
zeta_acc = 0.001
V_displ=20
zeta = V_displ/V
zeta_prev = 0
Re = np.full(nr_sect, 100000)
R = D/2
omega = a*mach_tip/R
v_ratio = V/(omega*R)
T_c = 2 * T_hv / (rho * V**2 * np.pi * R**2)
r = np.linspace(D_hub/2, D/2, nr_sect)
xi = r/R
while abs(zeta_prev/zeta - 1) >= zeta_acc:
phi_tip = np.arctan2(v_ratio*(1+zeta/2), 1)
#print(phi_tip)
f = (B/2)*(1-xi)/np.sin(phi_tip)
F = (2/np.pi)*np.arccos(np.exp(-f))
#F=np.array([1]*nr_sect)
phi = np.arctan2(np.tan(phi_tip), xi)
#print(phi)
x = omega * r / V
G = F * x * np.cos(phi) * np.sin(phi)
re_angs = np.insert(np.expand_dims(Re, axis=1), 1, np.zeros((1, nr_sect)), axis=1)
re_angs[-1, 0] = 100000
data = get_aifoildata(foil, re_angs, ('AlphaClCd', 'ClCdmaxCl', 'ClCdmax'))
alpha, cl, cdcl = np.radians(data[:, 0]), data[:, 1], 1/data[:, 2]
#print(cl)
Wc = 4 * np.pi * v_ratio * G * V * R * zeta / (cl * B)
#print(Wc)
Re = Wc / kin_viscosity
#print(Re)
param1 = 1 - cdcl * np.tan(phi)
param2 = 1 + cdcl / np.tan(phi)
ax_interf = zeta / 2 * (np.cos(phi))**2 * param1
rot_interf = zeta / (2 * x) * np.cos(phi) * np.sin(phi) * param2
#print(ax_interf)
W = V * (1 + ax_interf) / np.sin(phi)
c = Wc / W
beta = phi + alpha
i1 = 4 * xi * G * param1
i2 = v_ratio * i1 / (2 * xi) * param2 * np.sin(phi) * np.cos(phi)
j1 = 4 * xi * G * param2
j2 = j1 / 2 * param1 * (np.cos(phi))**2
I1 = np.trapz(i1, x=xi)
I2 = np.trapz(i2, x=xi)
J1 = np.trapz(j1, x=xi)
J2 = np.trapz(j2, x=xi)
zeta_prev = zeta
zeta = I1/(2*I2)-np.sqrt((I1/(2*I2))**2-T_c/I2)
#print(zeta)
P_c = J1*zeta + J2*zeta**2
P=P_c*rho*V**3*np.pi*R**2/2
cl_mean=np.mean(cl)
#print(P)
#prop_efficiency = T_c / P_c
#print('Final Design:\nr;', r,'\nbetas;', beta, '\nChords;', c, '\nEfficiency;', prop_efficiency)
#plt.plot(r, r**2*np.sqrt(F))
#plt.plot(r, rot_interf)
#plt.show()
#print(c)
#print(beta)
return r, c, beta, phi, Re, omega, P, cl_mean
def powers(D, T_hv, lst, wind_lst):
r, c, beta, phi_hv, Re_hv, omega_hv, P_hv, cl_mean = design(D, T_hv, 0.001)
powers = [r, c, beta, cl_mean, P_hv]
#print(P_hv)
nr_sect=np.size(r)
R=r[-1]
xi=r/R
sigma=B*c/(2*np.pi*r)
with open('AirfoilData/' + foilpath + '/cl_func.pkl', 'rb') as file:
cl_func = pickle.load(file)
with open('AirfoilData/' + foilpath + '/cd_func.pkl', 'rb') as file:
cd_func = pickle.load(file)
winds=[0]
winds.extend(wind_lst)
wind_lst=winds
for point in lst:
var_lst=[]
for wind_speed in wind_lst:
if len(point)==2:
T_conv, V_n = point
V_disc=wind_speed
elif len(point)==3:
T_conv, V_n, V_disc = point
theta=np.arctan2(V_n, V_disc)
V_n+=wind_speed*np.sin(theta)
V_disc += wind_speed * np.cos(theta)
T = 0
omega=omega_hv
phi=phi_hv+0.05
Re = Re_hv
while np.abs((T_conv-T)/T_conv)>0.001:
a_prev = np.full(1, nr_sect)
a = np.zeros(nr_sect)
while not np.max(np.abs((a - a_prev) / a_prev)) < 0.0005:
f=B/2*(1-xi)/np.sin(np.arctan2(xi*np.tan(phi),1))
F=2/np.pi*np.arccos(np.exp(-f))
alpha=beta-phi
points=[]
for j in range(nr_sect):
points.append([np.log10(Re[j]), np.degrees(alpha[j])])
C_l=cl_func(points)
C_d = cd_func(points)
epsilon=C_d/C_l
#epsilon=np.zeros(nr_sect)
C_y = C_l*(np.cos(phi) - epsilon*np.sin(phi))
C_x = C_l*(np.sin(phi)+epsilon*np.cos(phi))
K = C_y/(4*np.sin(phi)**2)
K_prime = C_x/(4*np.sin(phi)*np.cos(phi))
a_prev=a
a = sigma*K/(F-sigma*K)
a_prime = sigma*K_prime/(F+sigma*K_prime)
a[-1]=a[-2]
a_prime[-1]=a_prime[-2]
#i_lst.append(i)
#a_lst.append(a[0])
W=V_n*(1+a)/np.sin(phi)
Re=W*c/kin_viscosity
Re[-1] = 100000
delta_phi=np.arctan2(V_n*(1+a), omega*r*(1-a_prime))-phi
phi+=delta_phi/200
C_T_prime = np.pi ** 3 / 4 * sigma * C_y * xi ** 3 * F ** 2 / ((F + sigma * K_prime) * np.cos(phi)) ** 2
C_P_prime = C_T_prime * np.pi * xi * C_x / C_y
C_T_prime[-1] = C_T_prime[-2]
C_P_prime[-1] = C_P_prime[-2]
#plt.plot(xi, C_l)
#plt.title(f'baseline, omega={omega}')
#plt.show()
C_T = np.trapz(C_T_prime, x=xi)
C_P = np.trapz(C_P_prime, x=xi)
#print(4 / np.pi ** 3 * C_P * rho * omega ** 3 * R ** 5)
#print()
phi_eq=phi
Re_eq=Re
a_prime_eq=a_prime
n_psi=11
T=0
P=0
blade_drag=0
for psi in np.linspace(0, 180, n_psi):
psi=np.radians(psi)
V_t=V_disc*np.cos(psi)
phi=phi_eq
Re=Re_eq
a_prev=np.full(1, nr_sect)
a=np.zeros(nr_sect)
while not np.max(np.abs((a-a_prev)/a_prev))<0.0005:
f = B / 2 * (1 - xi) / np.sin(np.arctan2(xi * np.tan(phi), 1))
F = 2 / np.pi * np.arccos(np.exp(-f))
alpha = beta - phi
points = []
for j in range(nr_sect):
points.append([np.log10(Re[j]), np.degrees(alpha[j])])
C_l = cl_func(points)
C_d = cd_func(points)
epsilon = C_d / C_l
#epsilon=np.zeros(nr_sect)
C_y = C_l * (np.cos(phi) - epsilon * np.sin(phi))
C_x = C_l * (np.sin(phi) + epsilon * np.cos(phi))
K = C_y / (4 * np.sin(phi) ** 2)
K_prime = C_x / (4 * np.sin(phi) * np.cos(phi))
a_prev=a
a = sigma * K / (F - sigma * K)
a_prime = sigma * K_prime / (F + sigma * K_prime)
a[-1] = a[-2]
a_prime[-1] = a_prime[-2]
#i_lst.append(i)
#a_lst.append(a[0])
W = np.sqrt((V_n*(1+a))**2+(omega*r*(1-a_prime)+V_t)**2)
Re = W*c/kin_viscosity
Re[-1] = 100000
delta_phi = np.arctan2(V_n * (1 + a), omega * r * (1 - a_prime)+V_t) - phi
phi += delta_phi / 200
#print(psi)
#print(phi)
C_T_prime = np.pi**3/4*sigma*C_y*xi**3*W**2/(omega*r)**2
C_P_prime = C_T_prime*np.pi*xi*C_x/C_y
C_T_prime[-1] = C_T_prime[-2]
C_P_prime[-1] = C_P_prime[-2]
H_prime=0.5*rho*W**2*B*c*C_x
#plt.plot(xi, a_prime)
C_T=np.trapz(C_T_prime, x=xi)
C_P=np.trapz(C_P_prime, x=xi)
H=np.trapz(H_prime, x=r)
T+= 4 / np.pi ** 2 * C_T * rho * omega ** 2 * R ** 4/n_psi
P+=4/np.pi**3*C_P*rho*omega**3*R**5/n_psi
blade_drag+=H*np.cos(psi)/n_psi
#print(4/np.pi**3*C_P*rho*omega**3*R**5)
#print(W)
#plt.plot(xi, phi)
#plt.title(f'psi={psi}')
#plt.show()
#print(C_P_prime)
#print(f'P: {P}')
#print(f'T: {T}')
#print(f'blade_drag: {blade_drag}')
#print()
#plt.title(f'omega={omega}, psi={psi}')
#plt.show()
#print(P)
#print(T)
#print()
omega*=np.sqrt(T_conv/T)
var_lst.append([P, blade_drag, omega])
powers.append(var_lst)
return powers
#print(powers(D=2, T_hv=583, lst=[[600.2130211835558, 4.941286552985221, 29.687954154618136], [360.9971821340844, 7.697425215730051, 29.062173380815263], [592.4494820678754, 5], [350.5568701406026,5]], wind_lst=[1, -1]))
#print(design(2, 600, 0.001))