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added Optimize.py and Plot_Mission.py
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‎Lithium_Air_Sizing/Mission.py‎

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# Missions.py
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#
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# Created: May 2015, T. Lukaczyk
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# Created: Jan 2017, M. Vegh
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# Modified:
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@@ -84,7 +84,7 @@ def base(analyses):
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segment.analyses.extend( analyses.cruise )
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segment.altitude_end = 2.0 * Units.km
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segment.air_speed = 80.* Units['m/s']
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segment.air_speed = 100.* Units['m/s']
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segment.climb_rate = 6.0 * Units['m/s']
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segment.state.numerics.tolerance_solution = sol_tol
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# add to mission

‎Lithium_Air_Sizing/Optimize.py‎

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# Optimize.py
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#
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# Created: Jan 2017, M. Vegh
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# Modified:
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# ----------------------------------------------------------------------
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# Imports
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# ----------------------------------------------------------------------
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import SUAVE
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from SUAVE.Core import Units, Data
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import numpy as np
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import Vehicle
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import Analyses
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import Mission
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import Sizing as Procedure
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import Plot_Mission
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from SUAVE.Optimization.Nexus import Nexus
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import SUAVE.Optimization.Package_Setups.pyopt_setup as pyopt_setup
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from SUAVE.Sizing.Sizing_Loop import Sizing_Loop
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# ----------------------------------------------------------------------
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# Run the whole thing
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# ----------------------------------------------------------------------
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def main():
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problem = setup()
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output = pyopt_setup.Pyopt_Solve(problem, sense_step = 1E-2, solver='SNOPT')
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print output
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Plot_Mission.plot_mission(problem)
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return
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# ----------------------------------------------------------------------
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# Inputs, Objective, & Constraints
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# ----------------------------------------------------------------------
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def setup():
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nexus = Nexus()
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problem = Data()
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nexus.optimization_problem = problem
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nexus.sizing_loop = Sizing_Loop()
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# -------------------------------------------------------------------
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# Inputs
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# -------------------------------------------------------------------
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# [ tag , initial, [lb,ub], scaling, units ]
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problem.inputs = np.array([
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[ 'thrust_loading' , .2 , (.05 , .3 ) , .1, 'continuous', Units.less],
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[ 'fan_pressure_ratio' , 1.5 , (1.05 , 2.6 ) , 1., 'continuous', Units.less],
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#[ 'aspect_ratio' , 14. , (5. , 14. ) , 10., 'continuous', Units.less],
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[ 'wing_loading' , 400. , (200. , 800. ) , 100.,'continuous', Units.kg/Units.meter**2.],
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#[ 'taper' , 0.1000 , (.1 , .3 ) , .1, 'continuous', Units.less ],
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[ 'wing_thickness' , .105 , (0.07 , 0.20 ) , .1, 'continuous', Units.less ],
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[ 'v_climb_1' , 80. , (50. , 230. ) , 1E2, 'continuous', Units.meter/Units.second],
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[ 'v_climb_2' , 100. , (50. , 230 ) , 1E2, 'continuous', Units.meter/Units.second],
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[ 'v_climb_3' , 140 , (50. , 230 ) , 1E2, 'continuous', Units.meter/Units.second],
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[ 'cruise_altitude' , 33000. , (20000. , 35000 ) , 1E4, 'continuous', Units.ft],
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[ 'climb_alt_fraction_1' , 0.1 , (.1 , 1. ) , 1., 'continuous', Units.less],
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[ 'climb_alt_fraction_2' , .2 , (.2 , 1. ) , 1., 'continuous', Units.less],
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[ 'descent_alt_fraction_1' , .2 , (.1 , 1. ) , 1., 'continuous', Units.less],
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])
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# -------------------------------------------------------------------
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# Objective
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# -------------------------------------------------------------------
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# throw an error if the user isn't specific about wildcards
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# [ tag, scaling, units ]
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problem.objective = np.array([
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[ 'landing_weight', 1E4, Units.kg ]
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])
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# -------------------------------------------------------------------
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# Constraints
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# -------------------------------------------------------------------
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# [ tag, sense, edge, scaling, units ]
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problem.constraints = np.array([
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#[ 'power_margin' , '>', 0 , 1E6 , Units.meters],
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#['lithium_ion_energy_margin' , '>', 0 , 1E0 , Units.less],
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[ 'climb_constraint_1' , '>', 0 , 1E2 , Units.meters],
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[ 'climb_constraint_2' , '>', 0 , 1E3 , Units.meters], #handled by bounds
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[ 'descent_constraint_1' , '>', 0 , 1E2 , Units.meters],
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[ 'min_alpha_constraint' , '>', 0 , 1E1 , Units.degrees],
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[ 'max_alpha_constraint' , '>', 0 , 1E1 , Units.degrees],
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[ 'takeoff_field_constraint' , '>', 0 , 1E3 , Units.ft],
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[ 'landing_field_constraint' , '>', 0 , 1E3 , Units.ft],
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[ 'max_throttle_constraint' , '>', 0 , 1 , Units.less],
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['climb_velocity_constraint_1' , '>', 0 , 1E2 , Units.meters/Units.second],
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['climb_velocity_constraint_2' , '>', 0 , 1E2 , Units.meters/Units.second],
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[ 'iteration_constraint' , '>', 0 , 1 , Units.less],
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])
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'''
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problem.constraints = np.array([
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[ 'power_margin' , '>', 0 , 1E6 , Units.meters],
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#[ 'range_margin' , '>', 0 , 1E6 , Units.meters],
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[ 'washout' , '>', 0 , 1E0 , Units.radians],
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[ 'climb_constraint_1' , '>', 0 , 1E3 , Units.km],
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[ 'climb_constraint_2' , '>', 0 , 1E3 , Units.km],
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[ 'climb_constraint_3' , '>', 0 , 1E3 , Units.km],
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[ 'climb_constraint_4' , '>', 0 , 1E3 , Units.km],
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[ 'descent_constraint_1' , '>', 0 , 1E3 , Units.km],
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[ 'descent_constraint_2' , '>', 0 , 1E3 , Units.km],
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[ 'min_alpha_constraint' , '>', 0 , 1E1 , Units.degrees],
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[ 'max_alpha_constraint' , '>', 0 , 1E1 , Units.degrees],
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#[ 'takeoff_field_constraint' , '>', 0 , 1E3 , Units.ft],
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#[ 'landing_field_constraint' , '>', 0 , 1E3 , Units.ft],
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])
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'''
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# -------------------------------------------------------------------
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# Aliases
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# -------------------------------------------------------------------
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# [ 'alias' , ['data.path1.name','data.path2.name'] ]
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problem.aliases = [
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#Inputs
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[ 'thrust_loading' , 'vehicle_configurations.*.thrust_loading' ],
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[ 'fan_pressure_ratio' , 'vehicle_configurations.*.energy_network.propulsor.fan.pressure_ratio'],
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[ 'aspect_ratio' , 'vehicle_configurations.*.wings.main_wing.aspect_ratio' ],
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[ 'wing_loading' , 'vehicle_configurations.*.wing_loading'],
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[ 'wing_thickness' , 'vehicle_configurations.*.wings.main_wing.thickness_to_chord'],
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[ 'taper' , 'vehicle_configurations.*.wings.main_wing.taper'],
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[ 'climb_alt_fraction_1' , 'missions.base.climb_alt_fraction_1'],
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[ 'climb_alt_fraction_2' , 'missions.base.climb_alt_fraction_2'],
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[ 'descent_alt_fraction_1' , 'missions.base.descent_alt_fraction_1' ],
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[ 'cruise_altitude' , 'missions.base.segments.climb_3.altitude_end' ],
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[ 'v_climb_1' , 'missions.base.segments.climb_1.air_speed'],
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[ 'v_climb_2' , 'missions.base.segments.climb_2.air_speed'],
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[ 'v_climb_3' , 'missions.base.segments.climb_3.air_speed'],
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#outputs
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[ 'landing_weight' , 'results.segments[-1].conditions.weights.total_mass[-1,0]' ],
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[ 'total_range' , 'results.total_range' ],
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[ 'max_power' , 'results.Pmax' ],
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#constraints
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[ 'max_throttle_constraint' , 'results.max_throttle_constraint' ],
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[ 'climb_constraint_1' , 'results.climb_constraint_1' ],
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[ 'climb_constraint_2' , 'results.climb_constraint_2' ],
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[ 'descent_constraint_1' , 'results.descent_constraint_1' ],
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[ 'max_alpha_constraint' , 'results.max_alpha_constraint' ],
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[ 'min_alpha_constraint' , 'results.min_alpha_constraint' ],
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[ 'takeoff_field_constraint' , 'results.takeoff_field_constraint' ],
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[ 'landing_field_constraint' , 'results.landing_field_constraint' ],
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[ 'cost_constraint' , 'results.cost_constraint' ],
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[ 'climb_velocity_constraint_1' , 'results.climb_velocity_constraint_1' ],
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[ 'climb_velocity_constraint_2' , 'results.climb_velocity_constraint_2' ],
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[ 'iteration_constraint' , 'iteration_constraint'],
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]
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# -------------------------------------------------------------------
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# Vehicles
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# -------------------------------------------------------------------
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nexus.vehicle_configurations = Vehicle.setup()
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# -------------------------------------------------------------------
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# Analyses
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# -------------------------------------------------------------------
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nexus.analyses = Analyses.setup(nexus.vehicle_configurations)
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# -------------------------------------------------------------------
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# Missions
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# -------------------------------------------------------------------
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nexus.missions = Mission.setup(nexus.analyses)
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# -------------------------------------------------------------------
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# Procedure
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# -------------------------------------------------------------------
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nexus.procedure = Procedure.setup()
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nexus.total_number_of_iterations = 0
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return nexus
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if __name__ == '__main__':
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main()
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