def test_add_existing_design_parameter_as_input_parameter(self):
p = Phase(ode_class=_A,
transcription=GaussLobatto(num_segments=14,
order=3,
compressed=True))
p.add_design_parameter('theta')
with self.assertRaises(ValueError) as e:
p.add_input_parameter('theta')
expected = 'theta has already been added as a design parameter.'
self.assertEqual(str(e.exception), expected)
def test_invalid_input_parameter_name(self):
p = Phase('gauss-lobatto',
ode_class=BrachistochroneODE,
num_segments=8,
transcription_order=3)
with self.assertRaises(ValueError) as e:
p.add_input_parameter('foo')
expected = 'foo is not a controllable parameter in the ODE system.'
self.assertEqual(str(e.exception), expected)
def test_add_existing_input_parameter_as_input_parameter(self):
p = Phase('gauss-lobatto',
ode_class=BrachistochroneODE,
num_segments=8,
transcription_order=3)
p.add_input_parameter('theta')
with self.assertRaises(ValueError) as e:
p.add_input_parameter('theta')
expected = 'theta has already been added as an input parameter.'
self.assertEqual(str(e.exception), expected)
def test_gauss_lobatto(self):
p = Problem(model=Group())
phase = Phase(ode_class=MyODE,
ode_init_kwargs={'n_traj': n_traj},
transcription=GaussLobatto(num_segments=25,
order=3,
compressed=True))
p.model.add_subsystem('phase0', phase)
phase.add_input_parameter('alpha', val=np.ones((n_traj, 2)), units='m')
try:
p.setup()
except Exception as e:
self.fail('Exception encountered in setup:\n' + str(e))
def brachistochrone_min_time(transcription='gauss-lobatto',
num_segments=8,
transcription_order=3,
run_driver=True,
compressed=True,
optimizer='SLSQP'):
p = Problem(model=Group())
# if optimizer == 'SNOPT':
p.driver = pyOptSparseDriver()
p.driver.options['optimizer'] = optimizer
p.driver.options['dynamic_simul_derivs'] = True
if transcription == 'gauss-lobatto':
t = GaussLobatto(num_segments=num_segments,
order=transcription_order,
compressed=compressed)
elif transcription == 'radau-ps':
t = Radau(num_segments=num_segments,
order=transcription_order,
compressed=compressed)
elif transcription == 'runge-kutta':
t = RungeKutta(num_segments=num_segments,
order=transcription_order,
compressed=compressed)
phase = Phase(ode_class=BrachistochroneODE, transcription=t)
p.model.add_subsystem('phase0', phase)
phase.set_time_options(fix_initial=True, duration_bounds=(.5, 10))
phase.set_state_options('x',
fix_initial=True,
fix_final=False,
solve_segments=False)
phase.set_state_options('y',
fix_initial=True,
fix_final=False,
solve_segments=False)
phase.set_state_options('v',
fix_initial=True,
fix_final=False,
solve_segments=False)
phase.add_control('theta',
continuity=True,
rate_continuity=True,
units='deg',
lower=0.01,
upper=179.9)
phase.add_input_parameter('g', units='m/s**2', val=9.80665)
phase.add_boundary_constraint('x', loc='final', equals=10)
phase.add_boundary_constraint('y', loc='final', equals=5)
# Minimize time at the end of the phase
phase.add_objective('time_phase', loc='final', scaler=10)
p.model.linear_solver = DirectSolver()
p.setup(check=True)
p['phase0.t_initial'] = 0.0
p['phase0.t_duration'] = 2.0
p['phase0.states:x'] = phase.interpolate(ys=[0, 10], nodes='state_input')
p['phase0.states:y'] = phase.interpolate(ys=[10, 5], nodes='state_input')
p['phase0.states:v'] = phase.interpolate(ys=[0, 9.9], nodes='state_input')
p['phase0.controls:theta'] = phase.interpolate(ys=[5, 100],
nodes='control_input')
p['phase0.input_parameters:g'] = 9.80665
p.run_model()
if run_driver:
p.run_driver()
# Plot results
if SHOW_PLOTS:
exp_out = phase.simulate()
fig, ax = plt.subplots()
fig.suptitle('Brachistochrone Solution')
x_imp = p.get_val('phase0.timeseries.states:x')
y_imp = p.get_val('phase0.timeseries.states:y')
x_exp = exp_out.get_val('phase0.timeseries.states:x')
y_exp = exp_out.get_val('phase0.timeseries.states:y')
ax.plot(x_imp, y_imp, 'ro', label='implicit')
ax.plot(x_exp, y_exp, 'b-', label='explicit')
ax.set_xlabel('x (m)')
ax.set_ylabel('y (m)')
ax.grid(True)
ax.legend(loc='upper right')
fig, ax = plt.subplots()
fig.suptitle('Brachistochrone Solution')
x_imp = p.get_val('phase0.timeseries.time_phase')
y_imp = p.get_val('phase0.timeseries.controls:theta')
x_exp = exp_out.get_val('phase0.timeseries.time_phase')
y_exp = exp_out.get_val('phase0.timeseries.controls:theta')
ax.plot(x_imp, y_imp, 'ro', label='implicit')
ax.plot(x_exp, y_exp, 'b-', label='explicit')
ax.set_xlabel('time (s)')
ax.set_ylabel('theta (rad)')
ax.grid(True)
ax.legend(loc='lower right')
plt.show()
return p
def ex_aircraft_steady_flight(optimizer='SLSQP',
transcription='gauss-lobatto'):
p = Problem(model=Group())
p.driver = pyOptSparseDriver()
p.driver.options['optimizer'] = optimizer
p.driver.options['dynamic_simul_derivs'] = True
if optimizer == 'SNOPT':
p.driver.opt_settings['Major iterations limit'] = 1000
p.driver.opt_settings['Major feasibility tolerance'] = 1.0E-6
p.driver.opt_settings['Major optimality tolerance'] = 1.0E-6
p.driver.opt_settings["Linesearch tolerance"] = 0.10
p.driver.opt_settings['iSumm'] = 6
num_seg = 15
seg_ends, _ = lgl(num_seg + 1)
phase = Phase(transcription,
ode_class=AircraftODE,
num_segments=num_seg,
segment_ends=seg_ends,
transcription_order=5,
compressed=False)
# Pass Reference Area from an external source
assumptions = p.model.add_subsystem('assumptions', IndepVarComp())
assumptions.add_output('S', val=427.8, units='m**2')
assumptions.add_output('mass_empty', val=1.0, units='kg')
assumptions.add_output('mass_payload', val=1.0, units='kg')
p.model.add_subsystem('phase0', phase)
phase.set_time_options(initial_bounds=(0, 0),
duration_bounds=(300, 10000),
duration_ref=3600)
phase.set_state_options('range',
units='NM',
fix_initial=True,
fix_final=False,
scaler=0.001,
defect_scaler=1.0E-2)
phase.set_state_options('mass_fuel',
units='lbm',
fix_initial=True,
fix_final=True,
upper=1.5E5,
lower=0.0,
scaler=1.0E-5,
defect_scaler=1.0E-1)
phase.add_control('alt',
units='kft',
opt=True,
lower=0.0,
upper=50.0,
rate_param='climb_rate',
rate_continuity=True,
rate_continuity_scaler=1.0,
rate2_continuity=True,
rate2_continuity_scaler=1.0,
ref=1.0,
fix_initial=True,
fix_final=True)
phase.add_control('mach', units=None, opt=False)
phase.add_input_parameter('S', units='m**2')
phase.add_input_parameter('mass_empty', units='kg')
phase.add_input_parameter('mass_payload', units='kg')
phase.add_path_constraint('propulsion.tau', lower=0.01, upper=1.0)
phase.add_path_constraint('alt_rate',
units='ft/min',
lower=-3000,
upper=3000,
ref=3000)
p.model.connect('assumptions.S', 'phase0.input_parameters:S')
p.model.connect('assumptions.mass_empty',
'phase0.input_parameters:mass_empty')
p.model.connect('assumptions.mass_payload',
'phase0.input_parameters:mass_payload')
phase.add_objective('range', loc='final', ref=-1.0)
p.model.linear_solver = DirectSolver(assemble_jac=True)
p.setup()
p['phase0.t_initial'] = 0.0
p['phase0.t_duration'] = 3600.0
p['phase0.states:range'] = phase.interpolate(ys=(0, 1000.0),
nodes='state_input')
p['phase0.states:mass_fuel'] = phase.interpolate(ys=(30000, 0),
nodes='state_input')
p['phase0.controls:mach'][:] = 0.8
p['phase0.controls:alt'][:] = 10.0
p['assumptions.S'] = 427.8
p['assumptions.mass_empty'] = 0.15E6
p['assumptions.mass_payload'] = 84.02869 * 400
p.run_driver()
exp_out = phase.simulate(
times=np.linspace(0, p['phase0.t_duration'], 500),
record=True,
record_file='test_ex_aircraft_steady_flight_rec.db')
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('alt', nodes='all'), 'ro')
plt.plot(exp_out.get_values('time'), exp_out.get_values('alt'), 'b-')
plt.suptitle('altitude vs time')
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('alt_rate', nodes='all', units='ft/min'), 'ro')
plt.plot(exp_out.get_values('time'),
exp_out.get_values('alt_rate', units='ft/min'), 'b-')
plt.suptitle('altitude rate vs time')
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('mass_fuel', nodes='all'), 'ro')
plt.plot(exp_out.get_values('time'), exp_out.get_values('mass_fuel'), 'b-')
plt.suptitle('fuel mass vs time')
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('propulsion.dXdt:mass_fuel', nodes='all'), 'ro')
plt.plot(exp_out.get_values('time'),
exp_out.get_values('propulsion.dXdt:mass_fuel'), 'b-')
plt.suptitle('fuel mass flow rate vs time')
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('mach', nodes='all'), 'ro')
plt.plot(exp_out.get_values('time'), exp_out.get_values('mach'), 'b-')
plt.suptitle('mach vs time')
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('mach_rate', nodes='all'), 'ro')
plt.plot(exp_out.get_values('time'), exp_out.get_values('mach_rate'), 'b-')
plt.suptitle('mach rate vs time')
print('time')
print(phase.get_values('time', nodes='all').T)
print('alt')
print(phase.get_values('alt', nodes='all').T)
print('alt_rate')
print(phase.get_values('alt_rate', nodes='all').T)
print('alt_rate2')
print(phase.get_values('alt_rate2', nodes='all').T)
print('range')
print(phase.get_values('range', nodes='all').T)
print('flight path angle')
print(phase.get_values('gam_comp.gam').T)
print('true airspeed')
print(phase.get_values('tas_comp.TAS', units='m/s').T)
print('coef of lift')
print(phase.get_values('aero.CL').T)
print('coef of drag')
print(phase.get_values('aero.CD').T)
print('atmos density')
print(phase.get_values('atmos.rho').T)
print('alpha')
print(phase.get_values('flight_equilibrium.alpha', units='rad').T)
print('coef of thrust')
print(phase.get_values('flight_equilibrium.CT').T)
print('fuel flow rate')
print(phase.get_values('propulsion.dXdt:mass_fuel').T)
print('max_thrust')
print(phase.get_values('propulsion.max_thrust', units='N').T)
print('tau')
print(phase.get_values('propulsion.tau').T)
print('dynamic pressure')
print(phase.get_values('q_comp.q', units='Pa').T)
print('S')
print(phase.get_values('S', units='m**2').T)
plt.show()
return p
def test_dynamic_input_params(self):
prob = Problem(model=Group())
traj = prob.model.add_subsystem('traj', Trajectory())
# First phase: normal operation.
# NOTE: using RK4 integration here
P_DEMAND = 2.0
phase0 = Phase(ode_class=BatteryODE, transcription=RungeKutta(num_segments=200))
phase0.set_time_options(fix_initial=True, fix_duration=True)
phase0.set_state_options('state_of_charge', fix_initial=True, fix_final=False)
phase0.add_timeseries_output('battery.V_oc', output_name='V_oc', units='V')
phase0.add_timeseries_output('battery.V_pack', output_name='V_pack', units='V')
phase0.add_timeseries_output('pwr_balance.I_Li', output_name='I_Li', units='A')
phase0.add_input_parameter('P_demand', val=P_DEMAND, units='W')
traj.add_phase('phase0', phase0)
# Second phase: normal operation.
transcription = Radau(num_segments=5, order=5, compressed=True)
phase1 = Phase(ode_class=BatteryODE, transcription=transcription)
phase1.set_time_options(fix_initial=False, fix_duration=True)
phase1.set_state_options('state_of_charge', fix_initial=False, fix_final=False, solve_segments=True)
phase1.add_timeseries_output('battery.V_oc', output_name='V_oc', units='V')
phase1.add_timeseries_output('battery.V_pack', output_name='V_pack', units='V')
phase1.add_timeseries_output('pwr_balance.I_Li', output_name='I_Li', units='A')
phase1.add_input_parameter('P_demand', val=P_DEMAND, units='W')
traj.add_phase('phase1', phase1)
# Second phase, but with battery failure.
phase1_bfail = Phase(ode_class=BatteryODE, ode_init_kwargs={'num_battery': 2},
transcription=transcription)
phase1_bfail.set_time_options(fix_initial=False, fix_duration=True)
phase1_bfail.set_state_options('state_of_charge', fix_initial=False, fix_final=False, solve_segments=True)
phase1_bfail.add_timeseries_output('battery.V_oc', output_name='V_oc', units='V')
phase1_bfail.add_timeseries_output('battery.V_pack', output_name='V_pack', units='V')
phase1_bfail.add_timeseries_output('pwr_balance.I_Li', output_name='I_Li', units='A')
phase1_bfail.add_input_parameter('P_demand', val=P_DEMAND, units='W')
traj.add_phase('phase1_bfail', phase1_bfail)
# Second phase, but with motor failure.
phase1_mfail = Phase(ode_class=BatteryODE, ode_init_kwargs={'num_motor': 2},
transcription=transcription)
phase1_mfail.set_time_options(fix_initial=False, fix_duration=True)
phase1_mfail.set_state_options('state_of_charge', fix_initial=False, fix_final=False, solve_segments=True)
phase1_mfail.add_timeseries_output('battery.V_oc', output_name='V_oc', units='V')
phase1_mfail.add_timeseries_output('battery.V_pack', output_name='V_pack', units='V')
phase1_mfail.add_timeseries_output('pwr_balance.I_Li', output_name='I_Li', units='A')
phase1_mfail.add_input_parameter('P_demand', val=P_DEMAND, units='W')
traj.add_phase('phase1_mfail', phase1_mfail)
traj.link_phases(phases=['phase0', 'phase1'], vars=['state_of_charge', 'time'], connected=True)
traj.link_phases(phases=['phase0', 'phase1_bfail'], vars=['state_of_charge', 'time'], connected=True)
traj.link_phases(phases=['phase0', 'phase1_mfail'], vars=['state_of_charge', 'time'], connected=True)
# prob.model.linear_solver = DirectSolver(assemble_jac=True)
prob.setup()
prob.final_setup()
prob['traj.phases.phase0.time_extents.t_initial'] = 0
prob['traj.phases.phase0.time_extents.t_duration'] = 1.0*3600
# prob['traj.phases.phase1.time_extents.t_initial'] = 1.0*3600
prob['traj.phases.phase1.time_extents.t_duration'] = 1.0*3600
# prob['traj.phases.phase1_bfail.time_extents.t_initial'] = 1.0*3600
prob['traj.phases.phase1_bfail.time_extents.t_duration'] = 1.0*3600
# prob['traj.phases.phase1_mfail.time_extents.t_initial'] = 1.0*3600
prob['traj.phases.phase1_mfail.time_extents.t_duration'] = 1.0*3600
prob.set_solver_print(level=0)
prob.run_model()
plot = True
if plot:
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
t0 = prob['traj.phase0.timeseries.time']
t1 = prob['traj.phase1.timeseries.time']
t1b = prob['traj.phase1_bfail.timeseries.time']
t1m = prob['traj.phase1_mfail.timeseries.time']
soc0 = prob['traj.phase0.timeseries.states:state_of_charge']
soc1 = prob['traj.phase1.timeseries.states:state_of_charge']
soc1b = prob['traj.phase1_bfail.timeseries.states:state_of_charge']
soc1m = prob['traj.phase1_mfail.timeseries.states:state_of_charge']
plt.subplot(2, 2, 1)
plt.plot(t0, soc0, 'b')
plt.plot(t1, soc1, 'b')
plt.plot(t1b, soc1b, 'r')
plt.plot(t1m, soc1m, 'c')
plt.xlabel('Time (hour)')
plt.ylabel('State of Charge (percent)')
V_oc0 = prob['traj.phase0.timeseries.V_oc']
V_oc1 = prob['traj.phase1.timeseries.V_oc']
V_oc1b = prob['traj.phase1_bfail.timeseries.V_oc']
V_oc1m = prob['traj.phase1_mfail.timeseries.V_oc']
plt.subplot(2, 2, 2)
plt.plot(t0, V_oc0, 'b')
plt.plot(t1, V_oc1, 'b')
plt.plot(t1b, V_oc1b, 'r')
plt.plot(t1m, V_oc1m, 'c')
plt.xlabel('Time (hour)')
plt.ylabel('Open Circuit Voltage (V)')
V_pack0 = prob['traj.phase0.timeseries.V_pack']
V_pack1 = prob['traj.phase1.timeseries.V_pack']
V_pack1b = prob['traj.phase1_bfail.timeseries.V_pack']
V_pack1m = prob['traj.phase1_mfail.timeseries.V_pack']
plt.subplot(2, 2, 3)
plt.plot(t0, V_pack0, 'b')
plt.plot(t1, V_pack1, 'b')
plt.plot(t1b, V_pack1b, 'r')
plt.plot(t1m, V_pack1m, 'c')
plt.xlabel('Time (hour)')
plt.ylabel('Terminal Voltage (V)')
I_Li0 = prob['traj.phase0.timeseries.I_Li']
I_Li1 = prob['traj.phase1.timeseries.I_Li']
I_Li1b = prob['traj.phase1_bfail.timeseries.I_Li']
I_Li1m = prob['traj.phase1_mfail.timeseries.I_Li']
plt.subplot(2, 2, 4)
plt.plot(t0, I_Li0, 'b')
plt.plot(t1, I_Li1, 'b')
plt.plot(t1b, I_Li1b, 'r')
plt.plot(t1m, I_Li1m, 'c')
plt.xlabel('Time (hour)')
plt.ylabel('Line Current (A)')
plt.show()
def test_cruise_results_gl(self):
p = Problem(model=Group())
if optimizer == 'SNOPT':
p.driver = pyOptSparseDriver()
p.driver.options['optimizer'] = optimizer
p.driver.options['dynamic_simul_derivs'] = True
p.driver.opt_settings['Major iterations limit'] = 100
p.driver.opt_settings['Major step limit'] = 0.05
p.driver.opt_settings['Major feasibility tolerance'] = 1.0E-6
p.driver.opt_settings['Major optimality tolerance'] = 1.0E-6
p.driver.opt_settings["Linesearch tolerance"] = 0.10
p.driver.opt_settings['iSumm'] = 6
p.driver.opt_settings['Verify level'] = 3
else:
p.driver = ScipyOptimizeDriver()
p.driver.options['dynamic_simul_derivs'] = True
transcription = GaussLobatto(num_segments=1,
order=13,
compressed=False)
phase = Phase(ode_class=AircraftODE, transcription=transcription)
p.model.add_subsystem('phase0', phase)
# Pass Reference Area from an external source
assumptions = p.model.add_subsystem('assumptions', IndepVarComp())
assumptions.add_output('S', val=427.8, units='m**2')
assumptions.add_output('mass_empty', val=1.0, units='kg')
assumptions.add_output('mass_payload', val=1.0, units='kg')
phase.set_time_options(initial_bounds=(0, 0),
duration_bounds=(3600, 3600),
duration_ref=3600)
phase.set_state_options('range',
units='km',
fix_initial=True,
fix_final=False,
scaler=0.01,
defect_scaler=0.01)
phase.set_state_options('mass_fuel',
fix_final=True,
upper=20000.0,
lower=0.0,
scaler=1.0E-4,
defect_scaler=1.0E-2)
phase.set_state_options('alt', units='km', fix_initial=True)
phase.add_control('mach', units=None, opt=False)
phase.add_control('climb_rate', units='m/s', opt=False)
phase.add_input_parameter('S', units='m**2')
phase.add_input_parameter('mass_empty', units='kg')
phase.add_input_parameter('mass_payload', units='kg')
phase.add_path_constraint('propulsion.tau',
lower=0.01,
upper=1.0,
shape=(1, ))
phase.add_timeseries_output('tas_comp.TAS', units='m/s')
p.model.connect('assumptions.S', 'phase0.input_parameters:S')
p.model.connect('assumptions.mass_empty',
'phase0.input_parameters:mass_empty')
p.model.connect('assumptions.mass_payload',
'phase0.input_parameters:mass_payload')
phase.add_objective('time', loc='final', ref=3600)
p.model.linear_solver = DirectSolver()
p.setup()
p['phase0.t_initial'] = 0.0
p['phase0.t_duration'] = 1.515132 * 3600.0
p['phase0.states:range'] = phase.interpolate(ys=(0, 1296.4),
nodes='state_input')
p['phase0.states:mass_fuel'] = phase.interpolate(ys=(12236.594555, 0),
nodes='state_input')
p['phase0.states:alt'] = 5.0
p['phase0.controls:mach'] = 0.8
p['phase0.controls:climb_rate'] = 0.0
p['assumptions.S'] = 427.8
p['assumptions.mass_empty'] = 0.15E6
p['assumptions.mass_payload'] = 84.02869 * 400
p.run_driver()
time = p.get_val('phase0.timeseries.time')
tas = p.get_val('phase0.timeseries.TAS', units='km/s')
range = p.get_val('phase0.timeseries.states:range')
assert_rel_error(self, range, tas * time, tolerance=1.0E-4)
theta = thetas[i]
theta2 = np.random.uniform(np.pi - np.pi / 6, np.pi + np.pi / 6)
r = 4000.
if i % 3 == 0:
theta2 = theta - np.pi / 4
start_x = center_x + r * np.cos(theta)
start_y = center_y + r * np.sin(theta)
end_x = center_x + r * np.cos(theta + theta2)
end_y = center_y + r * np.sin(theta + theta2)
locations.append([start_x, end_x, start_y, end_y])
#print("location", i, locations[-1])
phase.add_input_parameter('sx%d' % i, val=start_x, units='m')
phase.add_input_parameter('sy%d' % i, val=start_y, units='m')
phase.add_input_parameter('ex%d' % i, val=end_x, units='m')
phase.add_input_parameter('ey%d' % i, val=end_y, units='m')
phase.add_input_parameter('ts%d' % i, val=t_start, units='s')
phase.add_input_parameter('te%d' % i, val=t_end, units='s')
phase.set_state_options('x%d' % i, scaler=0.01, defect_scaler=0.1)
phase.set_state_options('y%d' % i, scaler=0.01, defect_scaler=0.1)
phase.add_boundary_constraint('x%d' % i, loc='initial', equals=start_x)
phase.add_boundary_constraint('y%d' % i, loc='initial', equals=start_y)
phase.add_boundary_constraint('x%d' % i, loc='final', equals=end_x)
phase.add_boundary_constraint('y%d' % i, loc='final', equals=end_y)
# phase.set_state_options('v%d' % i, fix_initial=False, fix_final=False,
def test_steady_aircraft_for_docs(self):
import numpy as np
import matplotlib.pyplot as plt
from openmdao.api import Problem, Group, pyOptSparseDriver, DirectSolver, IndepVarComp
from openmdao.utils.assert_utils import assert_rel_error
from dymos import Phase
from dymos.examples.aircraft_steady_flight.aircraft_ode import AircraftODE
from dymos.utils.lgl import lgl
p = Problem(model=Group())
p.driver = pyOptSparseDriver()
p.driver.options['optimizer'] = 'SLSQP'
p.driver.options['dynamic_simul_derivs'] = True
num_seg = 15
seg_ends, _ = lgl(num_seg + 1)
phase = Phase('gauss-lobatto',
ode_class=AircraftODE,
num_segments=num_seg,
segment_ends=seg_ends,
transcription_order=5,
compressed=False)
# Pass design parameters in externally from an external source
assumptions = p.model.add_subsystem('assumptions', IndepVarComp())
assumptions.add_output('mach', val=0.8, units=None)
assumptions.add_output('S', val=427.8, units='m**2')
assumptions.add_output('mass_empty', val=1.0, units='kg')
assumptions.add_output('mass_payload', val=1.0, units='kg')
p.model.add_subsystem('phase0', phase)
phase.set_time_options(fix_initial=True,
duration_bounds=(300, 10000),
duration_ref=3600)
phase.set_state_options('range', units='NM', fix_initial=True, fix_final=False,
scaler=0.001,
defect_scaler=1.0E-2)
phase.set_state_options('mass_fuel', units='lbm', fix_initial=True, fix_final=True,
upper=1.5E5, lower=0.0, scaler=1.0E-5, defect_scaler=1.0E-1)
phase.add_control('alt', units='kft', opt=True, lower=0.0, upper=50.0,
rate_param='climb_rate',
rate_continuity=True, rate_continuity_scaler=1.0,
rate2_continuity=True, rate2_continuity_scaler=1.0, ref=1.0,
fix_initial=True, fix_final=True)
phase.add_input_parameter('mach', units=None)
phase.add_input_parameter('S', units='m**2')
phase.add_input_parameter('mass_empty', units='kg')
phase.add_input_parameter('mass_payload', units='kg')
phase.add_path_constraint('propulsion.tau', lower=0.01, upper=1.0)
phase.add_path_constraint('alt_rate', units='ft/min', lower=-3000, upper=3000, ref=3000)
p.model.connect('assumptions.mach', 'phase0.input_parameters:mach')
p.model.connect('assumptions.S', 'phase0.input_parameters:S')
p.model.connect('assumptions.mass_empty', 'phase0.input_parameters:mass_empty')
p.model.connect('assumptions.mass_payload', 'phase0.input_parameters:mass_payload')
phase.add_objective('range', loc='final', ref=-1.0)
p.model.linear_solver = DirectSolver(assemble_jac=True)
p.setup()
p['phase0.t_initial'] = 0.0
p['phase0.t_duration'] = 3600.0
p['phase0.states:range'] = phase.interpolate(ys=(0, 1000.0), nodes='state_input')
p['phase0.states:mass_fuel'] = phase.interpolate(ys=(30000, 0), nodes='state_input')
p['phase0.controls:alt'][:] = 10.0
p['assumptions.mach'][:] = 0.8
p['assumptions.S'] = 427.8
p['assumptions.mass_empty'] = 0.15E6
p['assumptions.mass_payload'] = 84.02869 * 400
p.run_driver()
exp_out = phase.simulate(times=np.linspace(0, p['phase0.t_duration'], 500), record=True,
record_file='test_doc_aircraft_steady_flight_rec.db')
assert_rel_error(self, phase.get_values('range', units='NM')[-1], 726.7, tolerance=1.0E-2)
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('alt', nodes='all', units='ft'),
'ro')
plt.plot(exp_out.get_values('time'),
exp_out.get_values('alt', units='ft'),
'b-')
plt.suptitle('Altitude vs Time')
plt.xlabel('Time (s)')
plt.ylabel('Altitude (ft)')
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('alt_rate', nodes='all', units='ft/min'),
'ro')
plt.plot(exp_out.get_values('time'),
exp_out.get_values('alt_rate', units='ft/min'),
'b-')
plt.suptitle('Climb Rate vs Time')
plt.xlabel('Time (s)')
plt.ylabel('Climb Rate (ft/min)')
plt.figure()
plt.plot(phase.get_values('time', nodes='all'),
phase.get_values('mass_fuel', nodes='all', units='lbm'),
'ro')
plt.plot(exp_out.get_values('time'),
exp_out.get_values('mass_fuel', units='lbm'),
'b-')
plt.suptitle('Fuel Mass vs Time')
plt.xlabel('Time (s)')
plt.ylabel('Fuel Mass (lbm)')
plt.show()