Merge pull request #633 from suavecode/fix_rotor

Fix rotor
suavecode · Nov 29, 2022 · 469036e · 469036e
2 parents f01d6a2 + f1b984b
commit 469036e
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Showing 19 changed files with 91 additions and 61 deletions.
diff --git a/regression/scripts/AVL/test_AVL.py b/regression/scripts/AVL/test_AVL.py
@@ -141,7 +141,7 @@ def main():
 
     # lift coefficient check
     lift_coefficient              = results.segments.cruise.conditions.aerodynamics.lift_coefficient[0][0]
-    lift_coefficient_true         = 0.6124936427552575
+    lift_coefficient_true         = 0.6125259974142665
 
     print(lift_coefficient)
     diff_CL                       = np.abs(lift_coefficient  - lift_coefficient_true) 
@@ -151,7 +151,7 @@ def main():
 
     # moment coefficient check
     moment_coefficient            = results.segments.cruise.conditions.stability.static.CM[0][0]
-    moment_coefficient_true       = -0.5764235338199974
+    moment_coefficient_true       = -0.5764667256663776
 
     print(moment_coefficient)
     diff_CM                       = np.abs(moment_coefficient - moment_coefficient_true)

diff --git a/regression/scripts/B737/results_mission_B737.res b/regression/scripts/B737/results_mission_B737.res
diff --git a/regression/scripts/Embraer_E190_constThr/results_mission_E190_constThr.res b/regression/scripts/Embraer_E190_constThr/results_mission_E190_constThr.res
diff --git a/regression/scripts/Regional_Jet_Optimization/Optimize2.py b/regression/scripts/Regional_Jet_Optimization/Optimize2.py
@@ -39,10 +39,10 @@ def main():
     print(con3)
 
     actual = Data()
-    actual.obj  = 0.66680042
-    actual.con  = 2.89275501
-    actual.obj2 = 0.69643961
-    actual.con3 = 3.08464784
+    actual.obj  = 0.6645457
+    actual.con  = 2.89918485
+    actual.obj2 = 0.69389189
+    actual.con3 = 3.09059233
 
     error = Data()
     error.obj  = (actual.obj - obj)/actual.obj

diff --git a/regression/scripts/aerodynamics/aerodynamics_results.res b/regression/scripts/aerodynamics/aerodynamics_results.res
@@ -1 +1 @@
-{"lift": [[-0.5259630550568174], [-0.3760451720034401], [-0.3475304118160083], [-0.24452696114041383], [-0.003967881856492357], [0.26347572475103526], [0.46598722965669714], [0.6889146999385382], [1.0119888177923257], [1.4020969697893308], [1.3459572899206365]], "cd_c": [[0.00021084213592037642], [3.216025849507262e-08], [1.7266684526204684e-22], [3.2904740881154703e-09], [0.0005339274191304674], [4.644407858546013e-05], [1.5108473501523067e-09], [2.3892863212650703e-11], [4.142548005778556e-05], [0.0026569168600391714], [4.8816063850836635e-14]], "cd_i": [[0.017628827563233505], [0.011808053631861447], [0.010803464137949876], [0.0067126108543920735], [0.0027304524751980115], [0.004614811166757508], [0.012401997536030988], [0.026706125679655527], [0.052429912509830055], [0.09272377262369227], [0.10637381506803112]], "cd_m": [[0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587]], "cd_p_fuse": [[0.004946796492229381], [0.005779147627615916], [0.008926136636732203], [0.005664504686306866], [0.005781749578763487], [0.004836139656952647], [0.005932995796868884], [0.007354422551288761], [0.005775532561515405], [0.005181868350841586], [0.006015432386719305]], "cd_p_wing": [[0.005798868938543027], [0.005927946059650478], [0.009429864691794812], [0.005732597261818282], [0.0065300434752118205], [0.00501664506296736], [0.005990576383227908], [0.007597374507523542], [0.006009631658542192], [0.005562832184720839], [0.006025780055498028]], "cd_tot": [[0.036147188285001824], [0.030083172706561703], [0.038839811604950675], [0.024413069226369204], [0.02269722921446303], [0.020122392432332686], [0.030977266721887275], [0.05002292710332585], [0.07170013330317539], [0.11427882129980278], [0.12698533787625896]]}
+{"lift": [[-0.5259630548735018], [-0.37604517190863146], [-0.3475304118725103], [-0.24452696096385945], [-0.003967881653940969], [0.2634757253938914], [0.46598723017773197], [0.688914700606597], [1.0119888185935246], [1.4020969707315618], [1.3459572911433624]], "cd_c": [[0.0002108421359963761], [3.2160258502353464e-08], [1.7266684529335444e-22], [3.2904740887327617e-09], [0.000533927419149616], [4.6444078584106674e-05], [1.5108473500279697e-09], [2.389286321020139e-11], [4.142548005311629e-05], [0.002656916860077522], [4.881606384980262e-14]], "cd_i": [[0.017628827555745446], [0.011808053598313455], [0.010803464107462003], [0.006712610832532182], [0.002730452465217076], [0.004614811173823257], [0.012401997552561989], [0.02670612571277804], [0.052429912563271966], [0.09272377271092394], [0.10637381518027891]], "cd_m": [[0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587], [0.0011255918999274587]], "cd_p_fuse": [[0.004946796492229381], [0.005779147627615916], [0.008926136636732203], [0.005664504686306866], [0.005781749578763487], [0.004836139656952647], [0.005932995796868884], [0.007354422551288761], [0.005775532561515405], [0.005181868350841586], [0.006015432386719305]], "cd_p_wing": [[0.005798868938543027], [0.005927946059650478], [0.009429864691794812], [0.005732597261818282], [0.0065300434752118205], [0.00501664506296736], [0.005990576383227908], [0.007597374507523542], [0.006009631658542192], [0.005562832184720839], [0.006025780055498028]], "cd_tot": [[0.03531806817991019], [0.030083097303558317], [0.038839811573853036], [0.024413064835146384], [0.02248085232699704], [0.02011383189665597], [0.03097726654153106], [0.05002292713486758], [0.07169738680074404], [0.11408212364314657], [0.12698533799074646]]}
diff --git a/regression/scripts/aerodynamics/control_surfaces_vlm_results.res b/regression/scripts/aerodynamics/control_surfaces_vlm_results.res
@@ -1 +1 @@
-{"CL": [-0.29720186925002035, 0.33834971768961464, 0.9595777066043815, -0.3167309679838157, 0.30943821920666836, 0.9157391929138856, -0.1914640232768408, 0.4093977795624484, 0.9819953212211241], "CDi": [0.021208501808035806, 0.013598563518241147, 0.0658330743959147, 0.043118905010923914, 0.028550015888229776, 0.07370811948530372, 0.10914058053146088, 0.09741034034681852, 0.14366943311207356], "CM": [0.20453038484502795, -0.6374102387969508, -1.4635778378551703, 1.2148330984404698, 0.38820808150475056, -0.4375665458027248, 1.5898563244892279, 0.7901615069649182, -0.010244539859071405]}
+{"CL": [-0.29720186878924787, 0.3383497179239063, 0.9595777065891437, -0.3167309673245075, 0.30943821976675145, 0.9157391933420813, -0.1914640234430447, 0.4093977780983102, 0.9819953184645844], "CDi": [0.021208501734265337, 0.013598563593377919, 0.06583307457673096, 0.04311890497828657, 0.028550016040742556, 0.07370811973286943, 0.10914058183610603, 0.09741034184271874, 0.14366943495424145], "CM": [0.20453038370934515, -0.6374102399771059, -1.463577839065431, 1.2148330942911774, 0.38820807739555296, -0.4375665498001729, 1.5898563236149348, 0.790161507051483,  -0.01024454]}
diff --git a/regression/scripts/multifidelity/f_data.npy b/regression/scripts/multifidelity/f_data.npy
diff --git a/regression/scripts/multifidelity/x_samples.npy b/regression/scripts/multifidelity/x_samples.npy
diff --git a/regression/scripts/noise_optimization/Noise_Test.py b/regression/scripts/noise_optimization/Noise_Test.py
@@ -40,7 +40,7 @@ def main():
     # Compare with truth values
     noise_cumulative_margin        = objectives[0]
     actual                         = Data()
-    actual.noise_cumulative_margin = 21.586738829964858
+    actual.noise_cumulative_margin = 21.639139008007746
 
 
     error                         = Data()

diff --git a/regression/scripts/propeller/propeller_test.py b/regression/scripts/propeller/propeller_test.py
@@ -219,10 +219,10 @@ def main():
     Cplast_a_truth  = 0.10450832
 
     # Truth values for propeller without airfoil geometry defined 
-    F_truth         = 2629.013537561697
-    Q_truth         = 787.38469662
-    P_truth         = 163115.87734548
-    Cplast_truth    = 0.08407389
+    F_truth         = 2682.883049614873
+    Q_truth         = 804.66619031
+    P_truth         = 166695.93931239
+    Cplast_truth    = 0.08591914
 
     # Truth values for rotor with airfoil geometry defined 
     Fr_a_truth      = 1266.0906132241278
@@ -231,10 +231,10 @@ def main():
     Cplastr_a_truth = 0.03486995
 
     # Truth values for rotor without airfoil geometry defined 
-    Fr_truth        = 1250.185882189092
-    Qr_truth        = 121.95416738
-    Pr_truth        = 25264.22102656
-    Cplastr_truth   = 0.03973936
+    Fr_truth        = 1276.4378657580712
+    Qr_truth        = 125.37681959
+    Pr_truth        = 25973.26315058
+    Cplastr_truth   = 0.04085465
 
     # Store errors 
     error = Data()

diff --git a/regression/scripts/segments/segment_test.py b/regression/scripts/segments/segment_test.py
@@ -74,25 +74,25 @@ def main():
             print(val)
 
     # Truth values
-    climb_throttle_1_truth   = 1.0779171064877817
-    climb_throttle_2_truth   = 1.0825265840224687
-    climb_throttle_3_truth   = 0.674660268669148 
-    climb_throttle_4_truth   = 1.1315606426230955
-    climb_throttle_5_truth   = 1.1836691794281005
-    climb_throttle_6_truth   = 0.7820927446131135
-    climb_throttle_7_truth   = 0.9575782120087092
-    climb_throttle_8_truth   = 1.1806251177582514
-    climb_throttle_9_truth   = 1.2803044387670226
-    climb_throttle_10_truth  = 1.0 
-    cruise_CL_1_truth        = 0.697527528118587  
-    cruise_CL_2_truth        = 0.6978305032649874  
-    cruise_CL_3_truth        = 0.7853555716641899  
-    descent_throttle_1_truth = 0.09557733021666127  
-    descent_throttle_2_truth = 0.2467066714518043  
-    single_pt_CL_1_truth     = 0.25119411851114865  
-    single_pt_CL_2_truth     = 0.2511952953215362 
-    loiter_CL_truth          = 0.5115243029776504 
-    descent_throttle_3_truth = 0.17985343172510482 
+    climb_throttle_1_truth   = 1.0779172001580994
+    climb_throttle_2_truth   = 1.082526695692354
+    climb_throttle_3_truth   = 0.6746599245287441
+    climb_throttle_4_truth   = 1.131556307691754
+    climb_throttle_5_truth   = 1.183629999830914
+    climb_throttle_6_truth   = 0.7796000622149822
+    climb_throttle_7_truth   = 0.9470934374535483
+    climb_throttle_8_truth   = 1.1619277522734948
+    climb_throttle_9_truth   = 1.260973822735993
+    climb_throttle_10_truth  = 1.0
+    cruise_CL_1_truth        = 0.6977166846933968
+    cruise_CL_2_truth        = 0.6980183965324797
+    cruise_CL_3_truth        = 0.7854348456470898
+    descent_throttle_1_truth = 0.09562278771507186
+    descent_throttle_2_truth = 0.24681832658985817
+    single_pt_CL_1_truth     = 0.2512631812992136
+    single_pt_CL_2_truth     = 0.25126434016263305
+    loiter_CL_truth          = 0.5116647507936652
+    descent_throttle_3_truth = 0.17994332698047444
 
     # Store errors 
     error = Data()

diff --git a/regression/scripts/segments/transition_segment_test.py b/regression/scripts/segments/transition_segment_test.py
@@ -55,17 +55,21 @@ def main():
     transition_1_throttle  = results.segments.transition_1.conditions.propulsion.throttle[:,0]
     cruise_throttle        = results.segments.cruise.conditions.propulsion.throttle[:,0]
 
+    print(departure_throttle)
+    print(transition_1_throttle)
+    print(cruise_throttle)
+
     # Truth values   
-    departure_throttle_truth          = 0.651687547816525
-    transition_1_throttle_truth       = 0.601399797479313
-    cruise_throttle_truth             = 0.4649280739025156
+    departure_throttle_truth          = 0.6516875478807475
+    transition_1_throttle_truth       = 0.6013997974737667
+    cruise_throttle_truth             = 0.46492807449474316
 
     # Store errors 
     error = Data()
     error.departure_throttle          = np.abs(departure_throttle[-1] - departure_throttle_truth)
-    error.transition_1_throttle       = np.abs(transition_1_throttle[-1] - transition_1_throttle_truth)   
-    error.cruise_throttle             = np.abs(cruise_throttle[-1] - cruise_throttle_truth) 
-
+    error.transition_1_throttle       = np.abs(transition_1_throttle[-1] - transition_1_throttle_truth)
+    error.cruise_throttle             = np.abs(cruise_throttle[-1] - cruise_throttle_truth)
+    
     print('Errors:')
     print(error)
 

diff --git a/regression/scripts/solar_network/solar_network.py b/regression/scripts/solar_network/solar_network.py
@@ -74,10 +74,10 @@ def main():
 
     # Truth results
 
-    truth_F   = 82.5075384708843
-    truth_rpm = 196.48257054445452
-    truth_i   = 86.20577553870862
-    truth_bat = 124605420.10966778
+    truth_F   = 82.50753846534539
+    truth_rpm = 194.40119841317366
+    truth_i   = 86.06579017876555
+    truth_bat = 124628733.8676211
 
     print('battery energy')
     print(energy)

diff --git a/regression/scripts/sweeps/test_sweeps.py b/regression/scripts/sweeps/test_sweeps.py
@@ -31,7 +31,7 @@ def main():
 
     outputs_sweep    = linear_sweep(problem)
 
-    truth_obj_sweeps = [[6964.39612518, 6400.84619649]]
+    truth_obj_sweeps = [[6938.91890449, 6372.63693836]]
 
     print('sweeps = {}'.format(outputs_sweep['objective']))
 
@@ -44,8 +44,8 @@ def main():
 
     outputs_carpet = variable_sweep(problem)
 
-    truth_obj_carp = [[6867.55035192, 6407.40469717],
-                      [7185.2512495 , 6375.68648074]]
+    truth_obj_carp = [[6845.86363474, 6382.72737946],
+                       [7160.2722498,  6350.28087445]]
     print('carpet:\n{}'.format(outputs_carpet['objective']))
 
     #print outputs_carpet

diff --git a/regression/scripts/variable_cruise_distance/variable_cruise_distance.py b/regression/scripts/variable_cruise_distance/variable_cruise_distance.py
@@ -45,7 +45,7 @@ def main():
 
     plot_results(results)
 
-    distance_regression = 3902453.700210854
+    distance_regression = 3909067.571732345
     distance_calc       = results.conditions.frames.inertial.position_vector[-1,0]
     print('distance_calc = ', distance_calc)
     error_distance      = abs((distance_regression - distance_calc )/distance_regression)

diff --git a/trunk/SUAVE/Input_Output/OpenVSP/vsp_read.py b/trunk/SUAVE/Input_Output/OpenVSP/vsp_read.py
@@ -15,10 +15,11 @@
 from copy import deepcopy
 
 import SUAVE
-from SUAVE.Input_Output.OpenVSP.vsp_propeller import read_vsp_propeller
-from SUAVE.Input_Output.OpenVSP.vsp_fuselage  import read_vsp_fuselage
-from SUAVE.Input_Output.OpenVSP.vsp_wing      import read_vsp_wing
-from SUAVE.Input_Output.OpenVSP.vsp_nacelle   import read_vsp_nacelle
+from SUAVE.Input_Output.OpenVSP.vsp_propeller        import read_vsp_propeller
+from SUAVE.Input_Output.OpenVSP.vsp_fuselage         import read_vsp_fuselage
+from SUAVE.Input_Output.OpenVSP.vsp_wing             import read_vsp_wing
+from SUAVE.Input_Output.OpenVSP.vsp_nacelle          import read_vsp_nacelle
+from SUAVE.Input_Output.OpenVSP.get_vsp_measurements import get_vsp_measurements
 
 from SUAVE.Components.Energy.Networks.Lift_Cruise              import Lift_Cruise
 from SUAVE.Components.Energy.Networks.Battery_Propeller        import Battery_Propeller
@@ -40,7 +41,7 @@
 
 
 ## @ingroup Input_Output-OpenVSP
-def vsp_read(tag, units_type='SI',specified_network=None,use_scaling=True): 
+def vsp_read(tag, units_type='SI',specified_network=None,use_scaling=True,calculate_wetted_area=True): 
     """This reads an OpenVSP vehicle geometry and writes it into a SUAVE vehicle format.
     Includes wings, fuselages, and propellers.
 
@@ -163,6 +164,17 @@ def vsp_read(tag, units_type='SI',specified_network=None,use_scaling=True):
         geom_name = vsp.GetGeomName(geom)
         geom_names.append(geom_name)
         print(str(geom_name) + ': ' + geom)
+
+
+    # Use OpenVSP to calculate wetted area
+    if calculate_wetted_area:
+        measurements = get_vsp_measurements()
+        if units_type == 'SI':
+            units_factor = Units.meter * 1.
+        elif units_type == 'imperial':
+            units_factor = Units.foot * 1.
+        elif units_type == 'inches':
+            units_factor = Units.inch * 1.	         
 
     # --------------------------------
     # AUTOMATIC VSP ENTRY & PROCESSING
@@ -196,20 +208,28 @@ def vsp_read(tag, units_type='SI',specified_network=None,use_scaling=True):
             sym_flag = [1] 
         for fux_idx in range(num_fus):	# loop through fuselages on aircraft 
             fuselage = read_vsp_fuselage(fuselage_id,fux_idx,sym_flag[fux_idx],units_type,use_scaling)
+
+            if calculate_wetted_area:
+                fuselage.areas.wetted = measurements[vsp.GetGeomName(fuselage_id)] * (units_factor**2)
+
             vehicle.append_component(fuselage)
 
     # --------------------------------------------------			    
     # Read Wings 
     # --------------------------------------------------			
     for wing_id in vsp_wings:
         wing = read_vsp_wing(wing_id, units_type,use_scaling)
+        if calculate_wetted_area:
+            wing.areas.wetted = measurements[vsp.GetGeomName(wing_id)] * (units_factor**2)  
         vehicle.append_component(wing)		 
 
     # --------------------------------------------------			    
     # Read Nacelles 
     # --------------------------------------------------			
     for nac_id, nacelle_id in enumerate(vsp_nacelles):
         nacelle = read_vsp_nacelle(nacelle_id,vsp_nacelle_type[nac_id], units_type)
+        if calculate_wetted_area:
+            nacelle.areas.wetted = measurements[vsp.GetGeomName(nacelle_id)] * (units_factor**2)         
         vehicle.append_component(nacelle)	  
 
     # --------------------------------------------------			    

diff --git a/trunk/SUAVE/Methods/Aerodynamics/AERODAS/section_properties.py b/trunk/SUAVE/Methods/Aerodynamics/AERODAS/section_properties.py
@@ -59,7 +59,8 @@ def section_properties(state,settings,geometry):
 
     # Calculate 2-D CLmax
     # From 241 A/B notes
-    Cl_max_ref = -0.0009*tc*tc*tc + 0.0217*tc*tc - 0.0442*tc + 0.7005
+    tc_1 = tc*100
+    Cl_max_ref = -0.0009*tc_1*tc_1*tc_1 + 0.0217*tc_1*tc_1 - 0.0442*tc_1 + 0.7005
     Re_ref     = 9.*10**6
     #CL1maxp = Cl_max_ref * ( RE / Re_ref ) **0.1
     CL1maxp = 1.5 * np.ones_like(state.conditions.freestream.altitude)

diff --git a/...k/SUAVE/Methods/Aerodynamics/Common/Fidelity_Zero/Drag/compressibility_drag_wing_total.py b/...k/SUAVE/Methods/Aerodynamics/Common/Fidelity_Zero/Drag/compressibility_drag_wing_total.py
@@ -40,15 +40,17 @@ def compressibility_drag_wing_total(state,settings,geometry):
     # unpack
     conditions             = state.conditions
     wings                  = geometry.wings 
+    S_ref                  = geometry.reference_area
 
     #compute parasite drag total
     total_compressibility_drag = 0.0
 
     # from wings
     for wing in wings.values():
+        s_wing = wing.areas.reference
         compressibility_drag = conditions.aerodynamics.drag_breakdown.compressible[wing.tag].compressibility_drag
         conditions.aerodynamics.drag_breakdown.compressible[wing.tag].compressibility_drag = compressibility_drag * 1. # avoid linking variables
-        total_compressibility_drag += compressibility_drag 
+        total_compressibility_drag += compressibility_drag * (s_wing/S_ref)
 
     conditions.aerodynamics.drag_breakdown.compressible.total  = total_compressibility_drag
 

diff --git a/trunk/SUAVE/Methods/Aerodynamics/Common/Fidelity_Zero/Lift/BET_calculations.py b/trunk/SUAVE/Methods/Aerodynamics/Common/Fidelity_Zero/Lift/BET_calculations.py
@@ -83,7 +83,9 @@ def compute_airfoil_aerodynamics(beta,c,r,R,B,Wa,Wt,a,nu,airfoils,a_loc,ctrl_pts
                 Cdval[:,locs] = Cdval_af[:,locs]
     else:
         # Estimate Cl max
-        Cl_max_ref = -0.0009*tc**3 + 0.0217*tc**2 - 0.0442*tc + 0.7005
+        tc_1 = tc*100
+        Cl_max_ref = -0.0009*tc_1**3 + 0.0217*tc_1**2 - 0.0442*tc_1 + 0.7005
+        Cl_max_ref[Cl_max_ref<0.7] = 0.7
         Re_ref     = 9.*10**6
         Cl1maxp    = Cl_max_ref * ( Re / Re_ref ) **0.1
 
@@ -95,7 +97,8 @@ def compute_airfoil_aerodynamics(beta,c,r,R,B,Wa,Wt,a,nu,airfoils,a_loc,ctrl_pts
         Cl[alpha>=np.pi/2] = 0.
 
         # Scale for Mach, this is Karmen_Tsien
-        Cl[Ma[:,:]<1.] = Cl[Ma[:,:]<1.]/((1-Ma[Ma[:,:]<1.]*Ma[Ma[:,:]<1.])**0.5+((Ma[Ma[:,:]<1.]*Ma[Ma[:,:]<1.])/(1+(1-Ma[Ma[:,:]<1.]*Ma[Ma[:,:]<1.])**0.5))*Cl[Ma<1.]/2)
+        KT_cond = np.logical_and((Ma[:,:]<1.),(Cl>0))
+        Cl[KT_cond] = Cl[KT_cond]/((1-Ma[KT_cond]*Ma[KT_cond])**0.5+((Ma[KT_cond]*Ma[KT_cond])/(1+(1-Ma[KT_cond]*Ma[KT_cond])**0.5))*Cl[KT_cond]/2)
 
         # If the blade segments are supersonic, don't scale
         Cl[Ma[:,:]>=1.] = Cl[Ma[:,:]>=1.]