class CruiseOptimizer(object):
"""Optimizer for cursie mach number and altitude."""
def __init__(self, ac):
super(CruiseOptimizer, self).__init__()
self.ac = ac
self.aircraft = prop.aircraft(ac)
self.thrust = Thrust(ac)
self.fuelflow = FuelFlow(ac)
self.drag = Drag(ac)
# parameters to be optimized:
# Mach number, altitude
self.x0 = np.array([0.3, 25000 * aero.ft])
self.normfactor = calc_normfactor(self.x0)
self.bounds = None
self.update_bounds()
def update_bounds(self, **kwargs):
machmin = kwargs.get('machmin', 0.5)
machmax = kwargs.get('machmax', self.aircraft['limits']['MMO'])
hmin = kwargs.get('hmin', 25000 * aero.ft)
hmax = kwargs.get('hmax', self.aircraft['limits']['ceiling'])
self.bounds = np.array([[machmin, machmax], [hmin, hmax]
]) * self.normfactor.reshape(2, -1)
def func_fuel(self, x, mass):
mach, h = denormalize(x, self.normfactor)
va = aero.mach2tas(mach, h)
ff = self.fuelflow.enroute(mass, va / aero.kts, h / aero.ft)
ff_m = ff / (va + 1e-3) * 1000
# print("%.03f" % mach, "%d" % (h/aero.ft), "%.05f" % ff_m)
return ff_m
def func_time(self, x, mass):
mach, h = denormalize(x, self.normfactor)
va = aero.mach2tas(mach, h)
va_inv = 1 / (va + 1e-4) * 1000
# print("%.03f" % mach, "%d" % (h/aero.ft), "%.02f" % va)
return va_inv
def func_cons_lift(self, x, mass):
mach, h = denormalize(x, self.normfactor)
va = aero.mach2tas(mach, h)
Tmax = self.thrust.cruise(va / aero.kts, h / aero.ft)
qS = 0.5 * aero.density(h) * va**2 * self.aircraft['wing']['area']
cd0 = self.drag.polar['clean']['cd0']
k = self.drag.polar['clean']['k']
mach_crit = self.drag.polar['mach_crit']
if mach > mach_crit:
cd0 += 20 * (mach - mach_crit)**4
dL2 = qS**2 * (1 / k * (Tmax /
(qS + 1e-3) - cd0)) - (mass * aero.g0)**2
return dL2
def func_cons_thrust(self, x, mass):
mach, h = denormalize(x, self.normfactor)
va = aero.mach2tas(mach, h)
D = self.drag.clean(mass, va / aero.kts, h / aero.ft)
Tmax = self.thrust.cruise(va / aero.kts, h / aero.ft)
dT = Tmax - D
return dT
def optimize(self, goal, mass):
if goal == 'fuel':
func = self.func_fuel
elif goal == 'time':
func = self.func_time
else:
raise RuntimeError('Optimization goal [%s] not avaiable.' % goal)
x0 = self.x0 * self.normfactor
res = minimize(
func,
x0,
args=(mass, ),
bounds=self.bounds,
jac=lambda x, m: Jacobian(lambda x: func(x, m))(x),
options={'maxiter': 200},
constraints=(
{
'type':
'ineq',
'args': (mass, ),
'fun':
lambda x, m: self.func_cons_thrust(x, m),
'jac':
lambda x, m: Jacobian(lambda x: self.func_cons_thrust(
x, m))(x)
},
{
'type':
'ineq',
'args': (mass, ),
'fun':
lambda x, m: self.func_cons_lift(x, m),
'jac':
lambda x, m: Jacobian(lambda x: self.func_cons_lift(x, m))
(x)
},
))
return res
thrust = Thrust(ac='A320', eng='CFM56-5B4')
print('-'*70)
T = thrust.takeoff(tas=100, alt=0)
print("thrust.takeoff(tas=100, alt=0)")
print(T)
print('-'*70)
T = thrust.climb(tas=200, alt=20000, roc=1000)
print("thrust.climb(tas=200, alt=20000, roc=1000)")
print(T)
print('-'*70)
T = thrust.cruise(tas=230, alt=32000)
print("thrust.cruise(tas=230, alt=32000)")
print(T)
print('-'*70)
T = thrust.climb(tas=[200], alt=[20000], roc=[1000])
print("thrust.climb(tas=[200], alt=[20000], roc=[1000])")
print(T)
print('-'*70)
def plot():
# Thrust = Thrust('A320', 'CFM56-5B4')
thrust = Thrust('A320', 'V2500-A1')
fig = plt.figure(figsize=(10,8))