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()