def main():
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# --- Takeoff Configuration ---
configuration = configs.takeoff
configuration.wings['main_wing'].flaps_angle = 20. * Units.deg
configuration.wings['main_wing'].slats_angle = 25. * Units.deg
configuration.V2_VS_ratio = 1.21
analyses = SUAVE.Analyses.Analysis.Container()
analyses = base_analysis(configuration)
analyses.aerodynamics.settings.maximum_lift_coefficient_factor = 0.90
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
# Set Tofl
target_tofl = 1487.92650289
# Compute take off weight given tofl
max_tow = find_take_off_weight_given_tofl(configuration, analyses, airport,
target_tofl)
truth_max_tow = 46656.50026628
max_tow_error = np.max(np.abs(max_tow[0] - truth_max_tow))
print('Range Error = %.4e' % max_tow_error)
assert (max_tow_error < 1e-6)
return
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
# --- Vehicle definition ---
vehicle = vehicle_setup()
configs=configs_setup(vehicle)
# --- Landing Configuration ---
landing_config = configs.landing
landing_config.wings['main_wing'].flaps.angle = 30. * Units.deg
landing_config.wings['main_wing'].slats.angle = 25. * Units.deg
landing_config.wings['main_wing'].high_lift = True
# Vref_V2_ratio may be informed by user. If not, use default value (1.23)
landing_config.Vref_VS_ratio = 1.23
# CLmax for a given configuration may be informed by user
# landing_config.maximum_lift_coefficient = 2.XX
# Used defined ajust factor for maximum lift coefficient
landing_config.max_lift_coefficient_factor = 0.90
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
# =====================================
# Landing field length evaluation
# =====================================
w_vec = np.linspace(20000.,44000.,10)
landing_field_length = np.zeros_like(w_vec)
for id_w,weight in enumerate(w_vec):
landing_config.mass_properties.landing = weight
landing_field_length[id_w] = estimate_landing_field_length(landing_config,landing_config,airport)
truth_LFL = np.array( [ 723.67022689 , 786.82625714 , 849.98228739 , 913.13831764 , 976.29434789 , 1039.45037815 , 1102.6064084 , 1165.76243865 , 1228.9184689 , 1292.07449915])
LFL_error = np.max(np.abs(landing_field_length-truth_LFL))
print('Maximum Landing Field Length Error= %.4e' % LFL_error)
title = "LFL vs W"
plt.figure(1);
plt.plot(w_vec,landing_field_length, 'k-', label = 'Landing Field Length')
plt.title(title); plt.grid(True)
plt.figure(1); plt.plot(w_vec,truth_LFL, label = 'Landing Field Length (true)')
legend = plt.legend(loc='lower right', shadow = 'true')
plt.xlabel('Weight (kg)')
plt.ylabel('Landing Field Length (m)')
#assert( LFL_error < 1e-5 )
return
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
# --- Vehicle definition ---
vehicle = vehicle_setup()
configs=configs_setup(vehicle)
# --- Landing Configuration ---
landing_config = configs.landing
landing_config.wings['main_wing'].flaps.angle = 30. * Units.deg
landing_config.wings['main_wing'].slats.angle = 25. * Units.deg
landing_config.wings['main_wing'].high_lift = True
# Vref_V2_ratio may be informed by user. If not, use default value (1.23)
landing_config.Vref_VS_ratio = 1.23
# CLmax for a given configuration may be informed by user
# landing_config.maximum_lift_coefficient = 2.XX
# Used defined ajust factor for maximum lift coefficient
landing_config.max_lift_coefficient_factor = 0.90
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
# =====================================
# Landing field length evaluation
# =====================================
w_vec = np.linspace(20000.,44000.,10)
landing_field_length = np.zeros_like(w_vec)
for id_w,weight in enumerate(w_vec):
landing_config.mass_properties.landing = weight
landing_field_length[id_w] = estimate_landing_field_length(landing_config,landing_config,airport)
truth_LFL = np.array( [ 723.67022689 , 786.82625714 , 849.98228739 , 913.13831764 , 976.29434789 , 1039.45037815 , 1102.6064084 , 1165.76243865 , 1228.9184689 , 1292.07449915])
LFL_error = np.max(np.abs(landing_field_length-truth_LFL))
print 'Maximum Landing Field Length Error= %.4e' % LFL_error
title = "LFL vs W"
plt.figure(1); plt.hold
plt.plot(w_vec,landing_field_length, 'k-', label = 'Landing Field Length')
plt.title(title); plt.grid(True)
plt.figure(1); plt.plot(w_vec,truth_LFL, label = 'Landing Field Length (true)')
legend = plt.legend(loc='lower right', shadow = 'true')
plt.xlabel('Weight (kg)')
plt.ylabel('Landing Field Length (m)')
#assert( LFL_error < 1e-5 )
return
def full_setup():
# vehicle data
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# vehicle analyses
configs_analyses = analyses_setup(configs)
# mission analyses
mission = mission_setup(configs_analyses)
analyses = SUAVE.Analyses.Analysis.Container()
analyses.configs = configs_analyses
analyses.missions = mission
return configs, analyses
def full_setup():
# vehicle data
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# vehicle analyses
configs_analyses = analyses_setup(configs)
# mission analyses
mission = mission_setup(configs_analyses)
analyses = SUAVE.Analyses.Analysis.Container()
analyses.configs = configs_analyses
analyses.missions = mission
return configs, analyses
def setup():
nexus = Nexus()
problem = Data()
nexus.optimization_problem = problem
# -------------------------------------------------------------------
# Inputs
# -------------------------------------------------------------------
# [ tag , initial, (lb,ub) , scaling , units ]
problem.inputs = np.array([
[ 'wing_area' , 95 , ( 90. , 130. ) , 100. , Units.meter**2],
[ 'cruise_altitude' , 11 , ( 9 , 14. ) , 10. , Units.km],
])
# -------------------------------------------------------------------
# Objective
# -------------------------------------------------------------------
# throw an error if the user isn't specific about wildcards
# [ tag, scaling, units ]
problem.objective = np.array([
[ 'fuel_burn', 10000, Units.kg ]
])
# -------------------------------------------------------------------
# Constraints
# -------------------------------------------------------------------
# [ tag, sense, edge, scaling, units ]
problem.constraints = np.array([
[ 'design_range_fuel_margin' , '>', 0., 1E-1, Units.less], #fuel margin defined here as fuel
])
# -------------------------------------------------------------------
# Aliases
# -------------------------------------------------------------------
# [ 'alias' , ['data.path1.name','data.path2.name'] ]
problem.aliases = [
[ 'wing_area' , ['vehicle_configurations.*.wings.main_wing.areas.reference',
'vehicle_configurations.*.reference_area' ]],
[ 'cruise_altitude' , 'missions.base.segments.climb_5.altitude_end' ],
[ 'fuel_burn' , 'summary.base_mission_fuelburn' ],
[ 'design_range_fuel_margin' , 'summary.max_zero_fuel_margin' ],
]
# -------------------------------------------------------------------
# Vehicles
# -------------------------------------------------------------------
vehicle = vehicle_setup()
nexus.vehicle_configurations = configs_setup(vehicle)
# -------------------------------------------------------------------
# Analyses
# -------------------------------------------------------------------
nexus.analyses = Analyses2.setup(nexus.vehicle_configurations)
# -------------------------------------------------------------------
# Missions
# -------------------------------------------------------------------
nexus.missions = Missions2.setup(nexus.analyses)
# -------------------------------------------------------------------
# Procedure
# -------------------------------------------------------------------
nexus.procedure = Procedure2.setup()
# -------------------------------------------------------------------
# Summary
# -------------------------------------------------------------------
nexus.summary = Data()
return nexus
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
# --- Vehicle definition ---
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# --- Landing Configuration ---
landing_config = configs.landing
landing_config.wings[
'main_wing'].control_surfaces.flap.deflection = 30. * Units.deg
landing_config.wings[
'main_wing'].control_surfaces.slat.deflection = 25. * Units.deg
landing_config.wings['main_wing'].high_lift = True
# Vref_V2_ratio may be informed by user. If not, use default value (1.23)
landing_config.Vref_VS_ratio = 1.23
# CLmax for a given configuration may be informed by user
# Used defined ajust factor for maximum lift coefficient
analyses = base_analysis(vehicle)
analyses.aerodynamics.settings.maximum_lift_coefficient_factor = 0.90
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
# =====================================
# Landing field length evaluation
# =====================================
w_vec = np.linspace(20000., 44000., 10)
landing_field_length = np.zeros_like(w_vec)
for id_w, weight in enumerate(w_vec):
landing_config.mass_properties.landing = weight
landing_field_length[id_w] = estimate_landing_field_length(
landing_config, analyses, airport)
truth_LFL = np.array([
736.09211533, 800.90439737, 865.71667941, 930.52896146, 995.3412435,
1060.15352554, 1124.96580759, 1189.77808963, 1254.59037167,
1319.40265372
])
LFL_error = np.max(np.abs(landing_field_length - truth_LFL))
assert (LFL_error < 1e-6)
print('Maximum Landing Field Length Error= %.4e' % LFL_error)
title = "LFL vs W"
plt.figure(1)
plt.plot(w_vec, landing_field_length, 'k-', label='Landing Field Length')
plt.title(title)
plt.grid(True)
plt.figure(1)
plt.plot(w_vec, truth_LFL, label='Landing Field Length (true)')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Landing Field Length (m)')
#assert( LFL_error < 1e-5 )
return
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# --- Takeoff Configuration ---
configuration = configs.takeoff
configuration.wings['main_wing'].flaps_angle = 20. * Units.deg
configuration.wings['main_wing'].slats_angle = 25. * Units.deg
# V2_V2_ratio may be informed by user. If not, use default value (1.2)
configuration.V2_VS_ratio = 1.21
analyses = SUAVE.Analyses.Analysis.Container()
analyses = base_analysis(vehicle)
analyses.aerodynamics.settings.maximum_lift_coefficient_factor = 0.90
# CLmax for a given configuration may be informed by user
# configuration.maximum_lift_coefficient = 2.XX
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
w_vec = np.linspace(40000., 52000., 10)
engines = (2, 3, 4)
takeoff_field_length = np.zeros((len(w_vec), len(engines)))
second_seg_clb_grad = np.zeros((len(w_vec), len(engines)))
compute_clb_grad = 1 # flag for Second segment climb estimation
for id_eng, engine_number in enumerate(engines):
configuration.propulsors.turbofan.number_of_engines = engine_number
for id_w, weight in enumerate(w_vec):
configuration.mass_properties.takeoff = weight
takeoff_field_length[id_w,id_eng],second_seg_clb_grad[id_w,id_eng] = \
estimate_take_off_field_length(configuration,analyses,airport,compute_clb_grad)
truth_TOFL = np.array([[1132.02796293, 735.9383927, 532.69742204],
[1197.35974193, 774.67804758, 560.33363101],
[1265.59738094, 814.98266121, 589.04125774],
[1336.81070755, 856.87662796, 618.83286389],
[1411.07189875, 900.38501278, 649.7212839],
[1488.45551849, 945.53356385, 681.71963124],
[1569.03855498, 992.34872487, 714.84130444],
[1652.90045778, 1040.85764732, 749.09999299],
[1740.12317463, 1091.08820251, 784.50968324],
[1830.79118831, 1143.06899356, 821.08466403]])
print(' takeoff_field_length = ', takeoff_field_length)
print(' second_seg_clb_grad = ', second_seg_clb_grad)
truth_clb_grad = np.array([[0.06842616, 0.24573587, 0.42304558],
[0.0624858, 0.23365346, 0.40482112],
[0.05691173, 0.22233091, 0.38775008],
[0.05167129, 0.21169929, 0.3717273],
[0.04673554, 0.20169777, 0.35666],
[0.04207879, 0.19227239, 0.34246598],
[0.03767816, 0.18337517, 0.32907217],
[0.03351319, 0.17496329, 0.31641339],
[0.02956553, 0.16699843, 0.30443134],
[0.02581868, 0.15944617, 0.29307367]])
TOFL_error = np.max(np.abs(truth_TOFL - takeoff_field_length) / truth_TOFL)
GRAD_error = np.max(
np.abs(truth_clb_grad - second_seg_clb_grad) / truth_clb_grad)
print('Maximum Take OFF Field Length Error= %.4e' % TOFL_error)
print('Second Segment Climb Gradient Error= %.4e' % GRAD_error)
import pylab as plt
title = "TOFL vs W"
plt.figure(1)
plt.plot(w_vec, takeoff_field_length[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, takeoff_field_length[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, takeoff_field_length[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_TOFL[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Takeoff field length (m)')
title = "2nd Segment Climb Gradient vs W"
plt.figure(2)
plt.plot(w_vec, second_seg_clb_grad[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_clb_grad[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Second Segment Climb Gradient (%)')
assert (TOFL_error < 1e-6)
assert (GRAD_error < 1e-6)
return
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# --- Takeoff Configuration ---
configuration = configs.takeoff
configuration.wings['main_wing'].flaps_angle = 20. * Units.deg
configuration.wings['main_wing'].slats_angle = 25. * Units.deg
# V2_V2_ratio may be informed by user. If not, use default value (1.2)
configuration.V2_VS_ratio = 1.21
configuration.max_lift_coefficient_factor = 0.90
analyses = SUAVE.Analyses.Analysis.Container()
analyses.base = base_analysis(vehicle)
# CLmax for a given configuration may be informed by user
# configuration.maximum_lift_coefficient = 2.XX
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
w_vec = np.linspace(40000., 52000., 10)
engines = (2, 3, 4)
takeoff_field_length = np.zeros((len(w_vec), len(engines)))
second_seg_clb_grad = np.zeros((len(w_vec), len(engines)))
compute_clb_grad = 1 # flag for Second segment climb estimation
for id_eng, engine_number in enumerate(engines):
configuration.propulsors.turbofan.number_of_engines = engine_number
for id_w, weight in enumerate(w_vec):
configuration.mass_properties.takeoff = weight
takeoff_field_length[id_w,id_eng],second_seg_clb_grad[id_w,id_eng] = \
estimate_take_off_field_length(configuration,analyses,airport,compute_clb_grad)
truth_TOFL = np.array([[1188.96105839, 769.70626688, 556.7892293],
[1258.89622705, 811.03166826, 586.22911148],
[1331.98245573, 854.04157057, 616.81833361],
[1408.2986729, 898.76345152, 648.5709987],
[1487.92650289, 945.22556064, 681.5015251],
[1570.95030987, 993.45693386, 715.62465361],
[1657.45724176, 1043.48740797, 750.95545452],
[1747.53727375, 1095.34763481, 787.50933445],
[1841.28325183, 1149.06909545, 825.30204308],
[1938.7909361, 1204.68411412, 864.34967986]])
print(' takeoff_field_length = ', takeoff_field_length)
print(' second_seg_clb_grad = ', second_seg_clb_grad)
truth_clb_grad = np.array([[0.0802881, 0.25686068, 0.43343326],
[0.07416381, 0.2446121, 0.41506038],
[0.0684322, 0.23314888, 0.39786556],
[0.06305712, 0.22239872, 0.38174032],
[0.05800668, 0.21229785, 0.36658901],
[0.0532527, 0.20278987, 0.35232705],
[0.04877011, 0.19382471, 0.3388793],
[0.04453662, 0.18535773, 0.32617884],
[0.04053228, 0.17734905, 0.31416581],
[0.03673921, 0.16976291, 0.3027866]])
TOFL_error = np.max(np.abs(truth_TOFL - takeoff_field_length) / truth_TOFL)
GRAD_error = np.max(
np.abs(truth_clb_grad - second_seg_clb_grad) / truth_clb_grad)
print('Maximum Take OFF Field Length Error= %.4e' % TOFL_error)
print('Second Segment Climb Gradient Error= %.4e' % GRAD_error)
import pylab as plt
title = "TOFL vs W"
plt.figure(1)
plt.plot(w_vec, takeoff_field_length[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, takeoff_field_length[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, takeoff_field_length[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_TOFL[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Takeoff field length (m)')
title = "2nd Segment Climb Gradient vs W"
plt.figure(2)
plt.plot(w_vec, second_seg_clb_grad[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_clb_grad[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Second Segment Climb Gradient (%)')
assert (TOFL_error < 1e-6)
assert (GRAD_error < 1e-6)
return
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
vehicle = vehicle_setup()
configs=configs_setup(vehicle)
# --- Takeoff Configuration ---
configuration = configs.takeoff
configuration.wings['main_wing'].flaps_angle = 20. * Units.deg
configuration.wings['main_wing'].slats_angle = 25. * Units.deg
# V2_V2_ratio may be informed by user. If not, use default value (1.2)
configuration.V2_VS_ratio = 1.21
configuration.max_lift_coefficient_factor = 0.90
analyses = SUAVE.Analyses.Analysis.Container()
analyses.base = base_analysis(vehicle)
# CLmax for a given configuration may be informed by user
# configuration.maximum_lift_coefficient = 2.XX
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
w_vec = np.linspace(40000.,52000.,10)
engines = (2,3,4)
takeoff_field_length = np.zeros((len(w_vec),len(engines)))
second_seg_clb_grad = np.zeros((len(w_vec),len(engines)))
compute_clb_grad = 1 # flag for Second segment climb estimation
for id_eng,engine_number in enumerate(engines):
configuration.propulsors.turbofan.number_of_engines = engine_number
for id_w,weight in enumerate(w_vec):
configuration.mass_properties.takeoff = weight
takeoff_field_length[id_w,id_eng],second_seg_clb_grad[id_w,id_eng] = \
estimate_take_off_field_length(configuration,analyses,airport,compute_clb_grad)
truth_TOFL = np.array([[ 1118.63611639, 727.97884809, 527.01392339],
[ 1182.89024405, 766.11098981, 554.22570668],
[ 1249.99344765, 805.78023921, 582.49069546],
[ 1320.01349207, 847.01029051, 611.82110075],
[ 1393.02041385, 889.82548587, 642.22939685],
[ 1469.08655728, 934.2508275 , 673.72832735],
[ 1548.28661027, 980.31198958, 706.33091096],
[ 1630.69763999, 1028.03532998, 740.05044723],
[ 1716.39912829, 1077.44790196, 774.9005222 ],
[ 1805.47300708, 1128.57746562, 810.89501387]])
print ' takeoff_field_length=', takeoff_field_length
print ' second_seg_clb_grad = ', second_seg_clb_grad
truth_clb_grad = np.array([[ 0.07389745, 0.25138656, 0.42887567],
[ 0.06775111, 0.23909388, 0.41043665],
[ 0.06199853, 0.22758873, 0.39317893],
[ 0.05660348, 0.21679862, 0.37699377],
[ 0.051534 , 0.20665966, 0.36178532],
[ 0.04676181, 0.19711529, 0.34746877],
[ 0.04226183, 0.18811533, 0.33396883],
[ 0.03801168, 0.17961503, 0.32121838],
[ 0.03399137, 0.17157441, 0.30915745],
[ 0.03018298, 0.16395762, 0.29773227]])
TOFL_error = np.max(np.abs(truth_TOFL-takeoff_field_length)/truth_TOFL)
GRAD_error = np.max(np.abs(truth_clb_grad-second_seg_clb_grad)/truth_clb_grad)
print 'Maximum Take OFF Field Length Error= %.4e' % TOFL_error
print 'Second Segment Climb Gradient Error= %.4e' % GRAD_error
import pylab as plt
title = "TOFL vs W"
plt.figure(1); plt.hold
plt.plot(w_vec,takeoff_field_length[:,0], 'k-', label = '2 Engines')
plt.plot(w_vec,takeoff_field_length[:,1], 'r-', label = '3 Engines')
plt.plot(w_vec,takeoff_field_length[:,2], 'b-', label = '4 Engines')
plt.title(title); plt.grid(True)
plt.plot(w_vec,truth_TOFL[:,0], 'k--o', label = '2 Engines [truth]')
plt.plot(w_vec,truth_TOFL[:,1], 'r--o', label = '3 Engines [truth]')
plt.plot(w_vec,truth_TOFL[:,2], 'b--o', label = '4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow = 'true')
plt.xlabel('Weight (kg)')
plt.ylabel('Takeoff field length (m)')
title = "2nd Segment Climb Gradient vs W"
plt.figure(2); plt.hold
plt.plot(w_vec,second_seg_clb_grad[:,0], 'k-', label = '2 Engines')
plt.plot(w_vec,second_seg_clb_grad[:,1], 'r-', label = '3 Engines')
plt.plot(w_vec,second_seg_clb_grad[:,2], 'b-', label = '4 Engines')
plt.title(title); plt.grid(True)
plt.plot(w_vec,truth_clb_grad[:,0], 'k--o', label = '2 Engines [truth]')
plt.plot(w_vec,truth_clb_grad[:,1], 'r--o', label = '3 Engines [truth]')
plt.plot(w_vec,truth_clb_grad[:,2], 'b--o', label = '4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow = 'true')
plt.xlabel('Weight (kg)')
plt.ylabel('Second Segment Climb Gradient (%)')
assert( TOFL_error < 1e-6 )
assert( GRAD_error < 1e-6 )
return
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# --- Takeoff Configuration ---
configuration = configs.takeoff
configuration.wings['main_wing'].flaps_angle = 20. * Units.deg
configuration.wings['main_wing'].slats_angle = 25. * Units.deg
# V2_V2_ratio may be informed by user. If not, use default value (1.2)
configuration.V2_VS_ratio = 1.21
analyses = SUAVE.Analyses.Analysis.Container()
analyses = base_analysis(vehicle)
analyses.aerodynamics.settings.maximum_lift_coefficient_factor = 0.90
# CLmax for a given configuration may be informed by user
# configuration.maximum_lift_coefficient = 2.XX
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
w_vec = np.linspace(40000., 52000., 10)
engines = (2, 3, 4)
takeoff_field_length = np.zeros((len(w_vec), len(engines)))
second_seg_clb_grad = np.zeros((len(w_vec), len(engines)))
compute_clb_grad = 1 # flag for Second segment climb estimation
for id_eng, engine_number in enumerate(engines):
configuration.propulsors.turbofan.number_of_engines = engine_number
for id_w, weight in enumerate(w_vec):
configuration.mass_properties.takeoff = weight
takeoff_field_length[id_w,id_eng],second_seg_clb_grad[id_w,id_eng] = \
estimate_take_off_field_length(configuration,analyses,airport,compute_clb_grad)
truth_TOFL = np.array([[1173.30474724, 760.43161763, 550.17542593],
[1241.97048851, 801.0454711, 579.11942109],
[1313.71925195, 843.31076941, 609.19124856],
[1388.62740991, 887.25412516, 640.40457932],
[1466.77393275, 932.90289417, 672.77338767],
[1548.24043104, 980.28518949, 706.31195806],
[1633.11119749, 1029.42989526, 741.03489188],
[1721.47324876, 1080.36668034, 776.95711399],
[1813.41636696, 1133.12601188, 814.09387926],
[1909.0331412, 1187.7391687, 852.46077892]])
print(' takeoff_field_length = ', takeoff_field_length)
print(' second_seg_clb_grad = ', second_seg_clb_grad)
truth_clb_grad = np.array([[0.07244437, 0.24921567, 0.42598697],
[0.06651232, 0.23715452, 0.40779672],
[0.06094702, 0.22585304, 0.39075907],
[0.05571568, 0.21524227, 0.37476886],
[0.0507893, 0.20526131, 0.35973331],
[0.04614213, 0.19585619, 0.34557024],
[0.04175123, 0.18697891, 0.33220659],
[0.03759607, 0.17858664, 0.3195772],
[0.03365829, 0.17064104, 0.30762378],
[0.02992135, 0.16310768, 0.29629402]])
TOFL_error = np.max(np.abs(truth_TOFL - takeoff_field_length) / truth_TOFL)
GRAD_error = np.max(
np.abs(truth_clb_grad - second_seg_clb_grad) / truth_clb_grad)
print('Maximum Take OFF Field Length Error= %.4e' % TOFL_error)
print('Second Segment Climb Gradient Error= %.4e' % GRAD_error)
import pylab as plt
title = "TOFL vs W"
plt.figure(1)
plt.plot(w_vec, takeoff_field_length[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, takeoff_field_length[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, takeoff_field_length[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_TOFL[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Takeoff field length (m)')
title = "2nd Segment Climb Gradient vs W"
plt.figure(2)
plt.plot(w_vec, second_seg_clb_grad[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_clb_grad[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Second Segment Climb Gradient (%)')
assert (TOFL_error < 1e-6)
assert (GRAD_error < 1e-6)
return
def main():
# ----------------------------------------------------------------------
# Main
# ----------------------------------------------------------------------
vehicle = vehicle_setup()
configs = configs_setup(vehicle)
# --- Takeoff Configuration ---
configuration = configs.takeoff
configuration.wings['main_wing'].flaps_angle = 20. * Units.deg
configuration.wings['main_wing'].slats_angle = 25. * Units.deg
# V2_V2_ratio may be informed by user. If not, use default value (1.2)
configuration.V2_VS_ratio = 1.21
configuration.max_lift_coefficient_factor = 0.90
analyses = SUAVE.Analyses.Analysis.Container()
analyses.base = base_analysis(vehicle)
# CLmax for a given configuration may be informed by user
# configuration.maximum_lift_coefficient = 2.XX
# --- Airport definition ---
airport = SUAVE.Attributes.Airports.Airport()
airport.tag = 'airport'
airport.altitude = 0.0 * Units.ft
airport.delta_isa = 0.0
airport.atmosphere = SUAVE.Analyses.Atmospheric.US_Standard_1976()
w_vec = np.linspace(40000., 52000., 10)
engines = (2, 3, 4)
takeoff_field_length = np.zeros((len(w_vec), len(engines)))
second_seg_clb_grad = np.zeros((len(w_vec), len(engines)))
compute_clb_grad = 1 # flag for Second segment climb estimation
for id_eng, engine_number in enumerate(engines):
configuration.propulsors.turbofan.number_of_engines = engine_number
for id_w, weight in enumerate(w_vec):
configuration.mass_properties.takeoff = weight
takeoff_field_length[id_w,id_eng],second_seg_clb_grad[id_w,id_eng] = \
estimate_take_off_field_length(configuration,analyses,airport,compute_clb_grad)
truth_TOFL = np.array([[1116.10635509, 726.47454766, 525.93957657],
[1180.15587618, 764.49121395, 553.07064632],
[1247.04359555, 804.03963238, 581.25141247],
[1316.83687778, 845.14335923, 610.49401596],
[1389.60534387, 887.82659431, 640.81085913],
[1465.42090714, 932.1141929, 672.21461168],
[1544.3578087, 978.0316776, 704.71821645],
[1626.49265282, 1025.60525002, 738.33489512],
[1711.90444209, 1074.86180226, 773.07815381],
[1800.67461244, 1125.82892836, 808.96178847]])
print ' takeoff_field_length=', takeoff_field_length
print ' second_seg_clb_grad = ', second_seg_clb_grad
truth_clb_grad = np.array([[0.07441427, 0.25242021, 0.43042615],
[0.06825112, 0.24009391, 0.4119367],
[0.0624828, 0.22855727, 0.39463173],
[0.05707296, 0.21773759, 0.37840221],
[0.05198957, 0.20757081, 0.36315205],
[0.04720429, 0.19800024, 0.34879619],
[0.04269194, 0.18897554, 0.33525915],
[0.0384301, 0.18045186, 0.32247363],
[0.03439872, 0.1723891, 0.31037949],
[0.03057983, 0.16475133, 0.29892282]])
TOFL_error = np.max(np.abs(truth_TOFL - takeoff_field_length))
GRAD_error = np.max(np.abs(truth_clb_grad - second_seg_clb_grad))
print 'Maximum Take OFF Field Length Error= %.4e' % TOFL_error
print 'Second Segment Climb Gradient Error= %.4e' % GRAD_error
import pylab as plt
title = "TOFL vs W"
plt.figure(1)
plt.hold
plt.plot(w_vec, takeoff_field_length[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, takeoff_field_length[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, takeoff_field_length[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_TOFL[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_TOFL[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Takeoff field length (m)')
title = "2nd Segment Climb Gradient vs W"
plt.figure(2)
plt.hold
plt.plot(w_vec, second_seg_clb_grad[:, 0], 'k-', label='2 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 1], 'r-', label='3 Engines')
plt.plot(w_vec, second_seg_clb_grad[:, 2], 'b-', label='4 Engines')
plt.title(title)
plt.grid(True)
plt.plot(w_vec, truth_clb_grad[:, 0], 'k--o', label='2 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 1], 'r--o', label='3 Engines [truth]')
plt.plot(w_vec, truth_clb_grad[:, 2], 'b--o', label='4 Engines [truth]')
legend = plt.legend(loc='lower right', shadow='true')
plt.xlabel('Weight (kg)')
plt.ylabel('Second Segment Climb Gradient (%)')
assert (TOFL_error < 1e-5)
assert (GRAD_error < 1e-5)
return
def setup():
nexus = Nexus()
problem = Data()
nexus.optimization_problem = problem
# -------------------------------------------------------------------
# Inputs
# -------------------------------------------------------------------
# [ tag , initial, (lb,ub) , scaling , units ]
problem.inputs = np.array([
['wing_area', 95, (90., 130.), 100., Units.meter**2],
['cruise_altitude', 11, (9, 14.), 10., Units.km],
])
# -------------------------------------------------------------------
# Objective
# -------------------------------------------------------------------
# throw an error if the user isn't specific about wildcards
# [ tag, scaling, units ]
problem.objective = np.array([['fuel_burn', 10000, Units.kg]])
# -------------------------------------------------------------------
# Constraints
# -------------------------------------------------------------------
# [ tag, sense, edge, scaling, units ]
problem.constraints = np.array([
['design_range_fuel_margin', '>', 0., 1E-1,
Units.less], #fuel margin defined here as fuel
])
# -------------------------------------------------------------------
# Aliases
# -------------------------------------------------------------------
# [ 'alias' , ['data.path1.name','data.path2.name'] ]
problem.aliases = [
[
'wing_area',
[
'vehicle_configurations.*.wings.main_wing.areas.reference',
'vehicle_configurations.*.reference_area'
]
],
['cruise_altitude', 'missions.base.segments.climb_5.altitude_end'],
['fuel_burn', 'summary.base_mission_fuelburn'],
['design_range_fuel_margin', 'summary.max_zero_fuel_margin'],
]
# -------------------------------------------------------------------
# Vehicles
# -------------------------------------------------------------------
vehicle = vehicle_setup()
nexus.vehicle_configurations = configs_setup(vehicle)
# -------------------------------------------------------------------
# Analyses
# -------------------------------------------------------------------
nexus.analyses = Analyses2.setup(nexus.vehicle_configurations)
# -------------------------------------------------------------------
# Missions
# -------------------------------------------------------------------
nexus.missions = Missions2.setup(nexus.analyses)
# -------------------------------------------------------------------
# Procedure
# -------------------------------------------------------------------
nexus.procedure = Procedure2.setup()
# -------------------------------------------------------------------
# Summary
# -------------------------------------------------------------------
nexus.summary = Data()
return nexus
