def test1(self):
geom = CCBladeGeometry()
geom.Rtip = 63.0
geom.precone = 5.0
check_gradient_unit_test(self, geom)
def test_OutputsAero():
data = {}
data['AEP_in'] = 23490703.70603071
data['V_in'] = np.array([0.178275041966, 0.190296788962, 0.202568028297, 0.215071993446, 0.227791807017, 0.240710518196, 0.253811139789, 0.267076684744, 0.280490202059, 0.294034811963, 0.307693740274, 0.32145035184, 0.335288182978, 0.349190972822, 0.363142693506, 0.377127579106, 0.391130153286, 0.405135255571, 0.419128066214, 0.43309412959, 0.447019376098, 0.460890142513, 0.474693190784, 0.488415725243, 0.502045408211, 0.515570374001, 0.528979241305, 0.54226112398, 0.555405640233, 0.568402920224, 0.581243612108, 0.593918886545, 0.606420439704, 0.618740494789, 0.630871802149, 0.642807637993, 0.654541801767, 0.666068612246, 0.67738290239, 0.68848001302, 0.699355785386, 0.710006552662, 0.720429130464, 0.730620806428, 0.740579328925, 0.750302894983, 0.759790137479, 0.76904011166, 0.778052281079, 0.786826502994, 0.795363013307, 0.803662411103, 0.811725642861, 0.819553986387, 0.827149034543, 0.834512678823, 0.841647092838, 0.848554715765, 0.855238235811, 0.861700573747, 0.867944866556, 0.873974451244, 0.879792848857, 0.885403748745, 0.890810993109, 0.896018561866, 0.90103055787, 0.90585119251, 0.91048477172, 0.914935682413, 0.919208379383, 0.923307372661, 0.927237215373, 0.931002492094, 0.934607807711, 0.93805777681, 0.941357013592, 0.944510122313, 0.947521688261, 0.950396269264, 0.95313838773, 0.955752523204, 0.95824310546, 0.960614508091, 0.962871042612, 0.965016953057, 0.967056411054, 0.968993511377, 0.970832267946, 0.972576610282, 0.974230380379, 0.975797329995, 0.977281118336, 0.978685310119, 0.980013374, 0.981268681344, 0.982454505324, 0.98357402033, 0.984630301666, 0.985626325531, 0.986564969246, 0.987449011729, 0.988281134189, 0.98906392103, 0.989799860938, 0.990491348148, 0.991140683869, 0.991750077849, 0.992321650072, 0.992857432566, 0.993359371317, 0.99382932827, 0.994269083401, 0.994680336859, 0.995064711163, 0.995423753433, 0.995758937661, 0.996071667003, 0.996363276084, 0.996635033314, 0.996888143197, 0.997123748634, 0.997342933215, 0.997546723483, 0.997736091178, 0.997911955448, 0.998075185027, 0.998226600365, 0.998366975728, 0.998497041241, 0.998617484891, 0.99872895447, 0.998832059475, 0.998927372946, 0.999015433252, 0.999096745819, 0.999171784802, 0.999240994698, 0.999304791902, 0.999363566204, 0.999417682229, 0.999467480822, 0.999513280372, 0.999555378083, 0.999594051191, 0.999629558123, 0.999662139611, 0.999692019741, 0.999719406969, 0.999744495073, 0.999767464065, 0.999788481055, 0.99980770107, 0.999825267834, 0.999841314496, 0.999855964334, 0.999869331401, 0.999881521151, 0.999892631024, 0.999902750988, 0.999911964064, 0.999920346811, 0.999927969778, 0.99993489794, 0.999941191092, 0.999946904234, 0.999952087915, 0.999956788569, 0.99996104882, 0.999964907768, 0.99996840126, 0.999971562138, 0.999974420473, 0.999977003779, 0.999979337216, 0.999981443776, 0.999983344458, 0.999985058426, 0.999986603162, 0.999987994599, 0.999989247253, 0.999990374339, 0.999991387879, 0.999992298805, 0.999993117053, 0.999993851641, 0.999994510758, 0.999995101829, 0.999995631585, 0.999996106123, 0.999996530963, 0.999996911098, 0.999997251045, 0.999997554883, 0.999997826298, 0.999998068616, 0.999998284835, 0.999998477661, 0.999998649529, 0.999998802632])
data['P_in'] = np.array([22025.3984542, 31942.1185436, 42589.4002304, 53993.2085473, 66179.5085267, 79174.2652013, 93003.4436034, 107693.008766, 123268.925721, 139757.159501, 157183.67514, 175574.437668, 194955.41212, 215352.563527, 236791.856922, 259299.257337, 282900.729806, 307622.23936, 333489.751032, 360529.229855, 388766.640862, 418227.949084, 448939.119554, 480926.117306, 514214.907371, 548831.454781, 584801.724571, 622151.681771, 660907.291415, 701094.518535, 742739.328164, 785867.685334, 830505.555078, 876678.902429, 924413.692418, 973735.890078, 1024671.46044, 1077246.36854, 1131486.57941, 1187418.05809, 1245066.76959, 1304458.67896, 1365619.75124, 1428575.95144, 1493353.24461, 1559977.59577, 1628474.96996, 1698871.33222, 1771192.64757, 1845464.88105, 1921713.99769, 1999965.96251, 2080246.74057, 2162582.29688, 2246998.59648, 2333521.6044, 2422177.28568, 2512991.60535, 2605990.52843, 2701200.01997, 2798646.04499, 2898354.56853, 3000351.55562, 3104662.97129, 3211314.78058, 3320332.94852, 3431743.44013, 3545572.22046, 3661284.29229, 3777883.06101, 3895967.17288, 4015492.83297, 4136416.74759, 4258697.48598, 4382294.05017, 4507165.36302, 4631531.67845, 4757024.71876, 4883638.63072, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0])
data['rated_V_in'] = 11.738606532616528
data['rated_Omega_in'] = 12.
data['rated_pitch_in'] = 0.0
data['rated_T_in'] = 714206.5321080858
data['rated_Q_in'] = 3978873.5772973835
data['hub_diameter_in'] = 3.075
data['diameter_in'] = 125.95500453593273
data['max_chord_in'] = 3.0459289459935825
data['V_extreme_in'] = 70.0
data['T_extreme_in'] = 0.0
data['Q_extreme_in'] = 0.0
data['Rtip_in'] = 63.0375
data['precurveTip_in'] = 0.0
data['precsweepTip_in'] = 0.0
prob = Problem()
prob.root = Group()
prob.root.add('comp', OutputsAero(len(data['P_in'])), promotes=['*'])
prob = init_IndepVar_add(prob, data)
prob.root.comp.deriv_options['check_step_calc'] = 'relative'
prob.setup(check=False)
prob = init_IndepVar_set(prob, data)
check_gradient_unit_test(prob)
def test1(self):
tower = TowerCostAdder()
tower.tower_cost = 1000000.0
check_gradient_unit_test(self, tower)
def test1(self):
gc = GeometricConstraints()
gc.d = [4.0, 3.0, 2.0]
gc.t = [0.4, 0.23, 0.14]
check_gradient_unit_test(self, gc)
def test1(self):
bc = BladeCurvature()
bc.r = np.array([
1.5375, 1.84056613137, 1.93905987557, 2.03755361977, 2.14220322299,
2.24069696719, 2.33919071139, 2.90419974, 3.04095863882,
3.13945238302, 5.637500205, 7.04226699698, 8.370800055,
11.8494282928, 13.8375, 14.7182548841, 15.887499795, 18.5537233505,
19.9875, 22.0564071286, 24.087500205, 26.16236509, 28.187499795,
32.2875, 33.5678634821, 36.387500205, 38.5725768593, 40.487499795,
40.6967540173, 40.7964789782, 40.8975, 42.6919644014, 44.5875,
52.787499795, 56.204199945, 58.937499795, 61.67080026, 63.0375
])
bc.precurve = np.array([
0.0, 0.043324361025, 0.0573893371698, 0.0714469497372,
0.0863751069858, 0.100417566593, 0.114452695996, 0.194824077331,
0.214241777459, 0.228217752953, 0.580295739194, 0.776308800624,
0.960411633829, 1.4368012564, 1.7055214864, 1.823777005,
1.98003324362, 2.32762426752, 2.50856911855, 2.76432512112,
3.0113656418, 3.26199245912, 3.50723775206, 4.0150233695,
4.17901272929, 4.55356019347, 4.85962948702, 5.14086873143,
5.17214747287, 5.18708601127, 5.20223968442, 5.47491847385,
5.77007321175, 7.12818875977, 7.7314427824, 8.22913789456,
8.73985955154, 9.0
])
bc.presweep = np.array([
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
])
bc.precone = 2.5
check_gradient_unit_test(self, bc, tol=5e-5)
def test_gradient(self):
self.nac.above_yaw_mass = np.random.rand(1)[0] # 5000.
self.nac.yawMass = np.random.rand(1)[0] # 5000.
self.nac.lss_mass = np.random.rand(1)[0] # 5000.
self.nac.main_bearing_mass = np.random.rand(1)[0] # 5000.
self.nac.second_bearing_mass = np.random.rand(1)[0] # 5000.
self.nac.gearbox_mass = np.random.rand(1)[0] # 5000.
self.nac.hss_mass = np.random.rand(1)[0] # 5000.
self.nac.generator_mass = np.random.rand(1)[0] # 5000.
self.nac.bedplate_mass = np.random.rand(1)[0] # 5000.
self.nac.mainframe_mass = np.random.rand(1)[0] # 6000.
self.nac.lss_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.main_bearing_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.second_bearing_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.gearbox_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.hss_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.generator_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.bedplate_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.lss_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.main_bearing_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.second_bearing_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.gearbox_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.hss_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.generator_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.bedplate_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
check_gradient_unit_test(self, self.nac, tol=1e-5, display=False)
def test1(self):
tower = TowerCostAdder()
tower.tower_cost = 1000000.0
check_gradient_unit_test(self, tower)
def test1(self):
dt = CSMDrivetrain()
dt.aeroPower = np.array([94518.9621316, 251637.667571, 525845.9078, 949750.895039, 1555959.84151, 2377079.95943, 3445718.46102, 4767739.26659, 6246980.6699, 7776655.12685, 9138828.60234, 10145691.7573, 10870259.0229, 11496057.2782, 12090978.6194, 12642721.8686, 13122354.9713, 13502608.5891, 13772424.3097, 13929508.977])
dt.ratedPower = 5000000.0
check_gradient_unit_test(self, dt)
def test1(self):
geom = CCBladeGeometry()
geom.Rtip = 63.0
geom.precone = 5.0
check_gradient_unit_test(self, geom)
def test4(self):
dt = CSMDrivetrain()
dt.aeroPower = np.linspace(-10.0, 30.0, 50)
dt.ratedPower = 5.0
check_gradient_unit_test(self, dt)
def test1(self):
rcdf = RayleighCDF()
rcdf.xbar = 6.0
rcdf.x = np.array([3.0, 3.08805770406, 3.17611540812, 3.26417311218, 3.35223081624, 3.4402885203, 3.52834622436, 3.61640392842, 3.70446163248, 3.79251933654, 3.8805770406, 3.96863474466, 4.05669244872, 4.14475015278, 4.23280785684, 4.3208655609, 4.40892326496, 4.49698096902, 4.58503867308, 4.67309637714, 4.7611540812, 4.84921178526, 4.93726948932, 5.02532719338, 5.11338489744, 5.2014426015, 5.28950030556, 5.37755800962, 5.46561571369, 5.55367341775, 5.64173112181, 5.72978882587, 5.81784652993, 5.90590423399, 5.99396193805, 6.08201964211, 6.17007734617, 6.25813505023, 6.34619275429, 6.43425045835, 6.52230816241, 6.61036586647, 6.69842357053, 6.78648127459, 6.87453897865, 6.96259668271, 7.05065438677, 7.13871209083, 7.22676979489, 7.31482749895, 7.40288520301, 7.49094290707, 7.57900061113, 7.66705831519, 7.75511601925, 7.84317372331, 7.93123142737, 8.01928913143, 8.10734683549, 8.19540453955, 8.28346224361, 8.37151994767, 8.45957765173, 8.54763535579, 8.63569305985, 8.72375076391, 8.81180846797, 8.89986617203, 8.98792387609, 9.07598158015, 9.16403928421, 9.25209698827, 9.34015469233, 9.42821239639, 9.51627010045, 9.60432780451, 9.69238550857, 9.78044321263, 9.86850091669, 9.95655862075, 10.0446163248, 10.1326740289, 10.2207317329, 10.308789437, 10.3968471411, 10.4849048451, 10.5729625492, 10.6610202532, 10.7490779573, 10.8371356614, 10.9251933654, 11.0132510695, 11.1013087735, 11.1893664776, 11.2774241817, 11.3654818857, 11.4535395898, 11.5415972938, 11.6296549979, 11.717712702, 11.8505355749, 11.9833584479, 12.1161813209, 12.2490041939, 12.3818270669, 12.5146499398, 12.6474728128, 12.7802956858, 12.9131185588, 13.0459414318, 13.1787643047, 13.3115871777, 13.4444100507, 13.5772329237, 13.7100557967, 13.8428786696, 13.9757015426, 14.1085244156, 14.2413472886, 14.3741701616, 14.5069930345, 14.6398159075, 14.7726387805, 14.9054616535, 15.0382845265, 15.1711073994, 15.3039302724, 15.4367531454, 15.5695760184, 15.7023988914, 15.8352217644, 15.9680446373, 16.1008675103, 16.2336903833, 16.3665132563, 16.4993361293, 16.6321590022, 16.7649818752, 16.8978047482, 17.0306276212, 17.1634504942, 17.2962733671, 17.4290962401, 17.5619191131, 17.6947419861, 17.8275648591, 17.960387732, 18.093210605, 18.226033478, 18.358856351, 18.491679224, 18.6245020969, 18.7573249699, 18.8901478429, 19.0229707159, 19.1557935889, 19.2886164618, 19.4214393348, 19.5542622078, 19.6870850808, 19.8199079538, 19.9527308267, 20.0855536997, 20.2183765727, 20.3511994457, 20.4840223187, 20.6168451916, 20.7496680646, 20.8824909376, 21.0153138106, 21.1481366836, 21.2809595565, 21.4137824295, 21.5466053025, 21.6794281755, 21.8122510485, 21.9450739215, 22.0778967944, 22.2107196674, 22.3435425404, 22.4763654134, 22.6091882864, 22.7420111593, 22.8748340323, 23.0076569053, 23.1404797783, 23.2733026513, 23.4061255242, 23.5389483972, 23.6717712702, 23.8045941432, 23.9374170162, 24.0702398891, 24.2030627621, 24.3358856351, 24.4687085081, 24.6015313811, 24.734354254, 24.867177127, 25.0])
check_gradient_unit_test(self, rcdf, tol=2e-6)
def test1(self):
comp = Total()
comp.turbine_cost = 2000000.0
comp.nTurbines = 100
comp.transportation_cost = 200000000.0
comp.engineering_cost = 1112596.36154
comp.powerperf_cost = 912133.333333
comp.roads_cost = 7713048.0
comp.compound_cost = 901575.0
comp.building_cost = 633735.251317
comp.foundation_cost = 11286436.7811
comp.erection_cost = 9382605.40137
comp.elecmat_cost = 14675585.0
comp.elecinst_cost = 7830230.0
comp.substation_cost = 5530851.41472
comp.transmission_cost = 4246267.80099
comp.projmgmt_cost = 2607139.155
comp.development_cost = 5000000.0
comp.insurance_cost = 665728.735622
comp.markup_cost = -26040000.0
comp.insurance_alpha = 0.0056
comp.markup_alpha = 0.1302
comp.multiplier = 1.3
check_gradient_unit_test(self, comp)
def test1(self):
coeff = Coefficients()
coeff.V = np.array([
12.5, 11.5574318317, 10.7470459579, 10.0428591371, 9.42527942463,
8.87925487168, 8.39303048389, 7.95729238704, 7.56456542753,
7.2087807692, 6.88496003209, 6.58898090313, 6.31740071221,
6.06732191135, 5.83628828803, 5.62220402072, 5.42326991915,
5.2379327383
])
coeff.T = np.array([
297537.442366, 287373.577926, 276842.263638, 266577.02588,
257357.173035, 249612.50174, 243430.855264, 238328.580357,
232897.327461, 226569.543695, 218948.774702, 210325.108191,
201373.59928, 192450.494842, 183749.591171, 175393.691013,
167431.667222, 159881.687873
])
coeff.Q = np.array([
2771187.76066, 2708873.98497, 2608206.05664, 2489419.14819,
2369374.79424, 2256062.60666, 2150350.91314, 2043415.20025,
1921526.97181, 1784742.05328, 1635134.27376, 1484081.73688,
1340896.38225, 1209094.24861, 1089686.69666, 982501.972978,
886537.720876, 800672.778302
])
coeff.P = np.array([
1741188.62212, 1702035.72214, 1638784.19732, 1564148.18153,
1488722.08943, 1417525.94222, 1351105.32627, 1283915.63627,
1207331.00366, 1121386.50463, 1027385.16442, 932476.05638,
842510.044742, 759696.321788, 684670.344188, 617324.196089,
557028.078207, 503077.543649
])
coeff.R = 62.9400379597
coeff.rho = 1.225
check_gradient_unit_test(self, coeff)
def test1(self):
comp = Total()
comp.turbine_cost = 2000000.0
comp.nTurbines = 100
comp.transportation_cost = 200000000.0
comp.engineering_cost = 1112596.36154
comp.powerperf_cost = 912133.333333
comp.roads_cost = 7713048.0
comp.compound_cost = 901575.0
comp.building_cost = 633735.251317
comp.foundation_cost = 11286436.7811
comp.erection_cost = 9382605.40137
comp.elecmat_cost = 14675585.0
comp.elecinst_cost = 7830230.0
comp.substation_cost = 5530851.41472
comp.transmission_cost = 4246267.80099
comp.projmgmt_cost = 2607139.155
comp.development_cost = 5000000.0
comp.insurance_cost = 665728.735622
comp.markup_cost = -26040000.0
comp.insurance_alpha = 0.0056
comp.markup_alpha = 0.1302
comp.multiplier = 1.3
check_gradient_unit_test(self, comp)
def test_gradient(self):
self.nac.above_yaw_mass = np.random.rand(1)[0] # 5000.
self.nac.yawMass = np.random.rand(1)[0] # 5000.
self.nac.lss_mass = np.random.rand(1)[0] # 5000.
self.nac.main_bearing_mass = np.random.rand(1)[0] # 5000.
self.nac.second_bearing_mass = np.random.rand(1)[0] # 5000.
self.nac.gearbox_mass = np.random.rand(1)[0] # 5000.
self.nac.hss_mass = np.random.rand(1)[0] # 5000.
self.nac.generator_mass = np.random.rand(1)[0] # 5000.
self.nac.bedplate_mass = np.random.rand(1)[0] # 5000.
self.nac.mainframe_mass = np.random.rand(1)[0] # 6000.
self.nac.lss_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.main_bearing_cm = np.random.rand(
3) # np.array([-2.0, 1.0, 1.0])
self.nac.second_bearing_cm = np.random.rand(
3) # np.array([-2.0, 1.0, 1.0])
self.nac.gearbox_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.hss_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.generator_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.bedplate_cm = np.random.rand(3) # np.array([-2.0, 1.0, 1.0])
self.nac.lss_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.main_bearing_I = np.random.rand(
3) # np.array([1000., 1000., 1000.])
self.nac.second_bearing_I = np.random.rand(
3) # np.array([1000., 1000., 1000.])
self.nac.gearbox_I = np.random.rand(
3) # np.array([1000., 1000., 1000.])
self.nac.hss_I = np.random.rand(3) # np.array([1000., 1000., 1000.])
self.nac.generator_I = np.random.rand(
3) # np.array([1000., 1000., 1000.])
self.nac.bedplate_I = np.random.rand(
3) # np.array([1000., 1000., 1000.])
check_gradient_unit_test(self, self.nac, tol=1e-5, display=False)
def test4(self):
dt = CSMDrivetrain()
dt.aeroPower = np.linspace(-10.0, 30.0, 50)
dt.ratedPower = 5.0
check_gradient_unit_test(self, dt)
def test2(self):
ccblade = CCBlade()
ccblade.r = np.array([
2.8667, 5.6000, 8.3333, 11.7500, 15.8500, 19.9500, 24.0500,
28.1500, 32.2500, 36.3500, 40.4500, 44.5500, 48.6500, 52.7500,
56.1667, 58.9000, 61.6333
])
ccblade.chord = np.array([
3.542, 3.854, 4.167, 4.557, 4.652, 4.458, 4.249, 4.007, 3.748,
3.502, 3.256, 3.010, 2.764, 2.518, 2.313, 2.086, 1.419
])
ccblade.theta = np.array([
13.308, 13.308, 13.308, 13.308, 11.480, 10.162, 9.011, 7.795,
6.544, 5.361, 4.188, 3.125, 2.319, 1.526, 0.863, 0.370, 0.106
])
ccblade.Rhub = 1.5
ccblade.Rtip = 63.0
ccblade.hubHt = 80.0
ccblade.precone = 2.5
ccblade.tilt = -5.0
ccblade.yaw = 0.0
ccblade.B = 3
ccblade.rho = 1.225
ccblade.mu = 1.81206e-5
ccblade.shearExp = 0.2
ccblade.nSector = 4
# airfoils
basepath = '/Users/sning/Dropbox/NREL/5MW_files/5MW_AFFiles/'
# load all airfoils
airfoil_types = [0] * 8
airfoil_types[0] = basepath + 'Cylinder1.dat'
airfoil_types[1] = basepath + 'Cylinder2.dat'
airfoil_types[2] = basepath + 'DU40_A17.dat'
airfoil_types[3] = basepath + 'DU35_A17.dat'
airfoil_types[4] = basepath + 'DU30_A17.dat'
airfoil_types[5] = basepath + 'DU25_A17.dat'
airfoil_types[6] = basepath + 'DU21_A17.dat'
airfoil_types[7] = basepath + 'NACA64_A17.dat'
# place at appropriate radial stations
af_idx = [0, 0, 1, 2, 3, 3, 4, 5, 5, 6, 6, 7, 7, 7, 7, 7, 7]
n = len(ccblade.r)
af = [0] * n
for i in range(n):
af[i] = airfoil_types[af_idx[i]]
ccblade.airfoil_files = af
ccblade.run_case = 'loads'
ccblade.V_load = 12.0
ccblade.Omega_load = 10.0
ccblade.pitch_load = 0.0
ccblade.azimuth_load = 180.0
check_gradient_unit_test(self, ccblade, tol=1e-5, display=True)
def test1(self):
wcdf = WeibullWithMeanCDF()
wcdf.xbar = 8.0
wcdf.k = 2.2
wcdf.x = np.linspace(1.0, 15.0, 50)
check_gradient_unit_test(self, wcdf)
def test3(self):
pp = PowerPerformance()
pp.hubHeight = 80.0
pp.permanentMetTowers = 3.0
pp.tempMetTowers = 2.0
check_gradient_unit_test(self, pp)
def test1(self):
loads = ExtremeLoads()
loads.T = [2414072.40260361, 188461.59444074]
loads.Q = [10926313.24295958, -8041330.51312603]
loads.nBlades = 3
check_gradient_unit_test(self, loads)
def test1(self):
wcdf = WeibullWithMeanCDF()
wcdf.xbar = 8.0
wcdf.k = 2.2
wcdf.x = np.linspace(1.0, 15.0, 50)
check_gradient_unit_test(self, wcdf)
def test1(self):
grid = RGrid()
grid.r_aero = np.array([0.02222276, 0.06666667, 0.11111057, 0.2, 0.23333333, 0.3, 0.36666667, 0.43333333, 0.5, 0.56666667, 0.63333333, 0.64, 0.7, 0.83333333, 0.88888943, 0.93333333, 0.97777724])
grid.fraction = np.array([0.0, 0.221750339522, 0.293817188822, 0.365884038121, 0.442455065507, 0.514521914807, 0.586588764105, 1.0, 0.050034345133, 0.0860690751106, 1.0, 0.513945366068, 1.0, 0.636330560083, 1.0, 0.429636571789, 1.0, 0.65029839566, 1.0, 0.504611469554, 1.0, 0.506064656711, 1.0, 1.0, 0.312283760506, 1.0, 0.532945578735, 1.0, 0.510375896771, 0.75360738708, 1.0, 0.486304715835, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
grid.idxj = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 9, 9, 10, 10, 11, 11, 11, 12, 12, 13, 14, 15, 16, 17])
check_gradient_unit_test(self, grid)
def test1(self):
aep = AEP()
aep.CDF_V = np.array([0.178275041966, 0.190296788962, 0.202568028297, 0.215071993446, 0.227791807017, 0.240710518196, 0.253811139789, 0.267076684744, 0.280490202059, 0.294034811963, 0.307693740274, 0.32145035184, 0.335288182978, 0.349190972822, 0.363142693506, 0.377127579106, 0.391130153286, 0.405135255571, 0.419128066214, 0.43309412959, 0.447019376098, 0.460890142513, 0.474693190784, 0.488415725243, 0.502045408211, 0.515570374001, 0.528979241305, 0.54226112398, 0.555405640233, 0.568402920224, 0.581243612108, 0.593918886545, 0.606420439704, 0.618740494789, 0.630871802149, 0.642807637993, 0.654541801767, 0.666068612246, 0.67738290239, 0.68848001302, 0.699355785386, 0.710006552662, 0.720429130464, 0.730620806428, 0.740579328925, 0.750302894983, 0.759790137479, 0.76904011166, 0.778052281079, 0.786826502994, 0.795363013307, 0.803662411103, 0.811725642861, 0.819553986387, 0.827149034543, 0.834512678823, 0.841647092838, 0.848554715765, 0.855238235811, 0.861700573747, 0.867944866556, 0.873974451244, 0.879792848857, 0.885403748745, 0.890810993109, 0.896018561866, 0.90103055787, 0.90585119251, 0.91048477172, 0.914935682413, 0.919208379383, 0.923307372661, 0.927237215373, 0.931002492094, 0.934607807711, 0.93805777681, 0.941357013592, 0.944510122313, 0.947521688261, 0.950396269264, 0.95313838773, 0.955752523204, 0.95824310546, 0.960614508091, 0.962871042612, 0.965016953057, 0.967056411054, 0.968993511377, 0.970832267946, 0.972576610282, 0.974230380379, 0.975797329995, 0.977281118336, 0.978685310119, 0.980013374, 0.981268681344, 0.982454505324, 0.98357402033, 0.984630301666, 0.985626325531, 0.986564969246, 0.987449011729, 0.988281134189, 0.98906392103, 0.989799860938, 0.990491348148, 0.991140683869, 0.991750077849, 0.992321650072, 0.992857432566, 0.993359371317, 0.99382932827, 0.994269083401, 0.994680336859, 0.995064711163, 0.995423753433, 0.995758937661, 0.996071667003, 0.996363276084, 0.996635033314, 0.996888143197, 0.997123748634, 0.997342933215, 0.997546723483, 0.997736091178, 0.997911955448, 0.998075185027, 0.998226600365, 0.998366975728, 0.998497041241, 0.998617484891, 0.99872895447, 0.998832059475, 0.998927372946, 0.999015433252, 0.999096745819, 0.999171784802, 0.999240994698, 0.999304791902, 0.999363566204, 0.999417682229, 0.999467480822, 0.999513280372, 0.999555378083, 0.999594051191, 0.999629558123, 0.999662139611, 0.999692019741, 0.999719406969, 0.999744495073, 0.999767464065, 0.999788481055, 0.99980770107, 0.999825267834, 0.999841314496, 0.999855964334, 0.999869331401, 0.999881521151, 0.999892631024, 0.999902750988, 0.999911964064, 0.999920346811, 0.999927969778, 0.99993489794, 0.999941191092, 0.999946904234, 0.999952087915, 0.999956788569, 0.99996104882, 0.999964907768, 0.99996840126, 0.999971562138, 0.999974420473, 0.999977003779, 0.999979337216, 0.999981443776, 0.999983344458, 0.999985058426, 0.999986603162, 0.999987994599, 0.999989247253, 0.999990374339, 0.999991387879, 0.999992298805, 0.999993117053, 0.999993851641, 0.999994510758, 0.999995101829, 0.999995631585, 0.999996106123, 0.999996530963, 0.999996911098, 0.999997251045, 0.999997554883, 0.999997826298, 0.999998068616, 0.999998284835, 0.999998477661, 0.999998649529, 0.999998802632])
aep.P = np.array([22025.3984542, 31942.1185436, 42589.4002304, 53993.2085473, 66179.5085267, 79174.2652013, 93003.4436034, 107693.008766, 123268.925721, 139757.159501, 157183.67514, 175574.437668, 194955.41212, 215352.563527, 236791.856922, 259299.257337, 282900.729806, 307622.23936, 333489.751032, 360529.229855, 388766.640862, 418227.949084, 448939.119554, 480926.117306, 514214.907371, 548831.454781, 584801.724571, 622151.681771, 660907.291415, 701094.518535, 742739.328164, 785867.685334, 830505.555078, 876678.902429, 924413.692418, 973735.890078, 1024671.46044, 1077246.36854, 1131486.57941, 1187418.05809, 1245066.76959, 1304458.67896, 1365619.75124, 1428575.95144, 1493353.24461, 1559977.59577, 1628474.96996, 1698871.33222, 1771192.64757, 1845464.88105, 1921713.99769, 1999965.96251, 2080246.74057, 2162582.29688, 2246998.59648, 2333521.6044, 2422177.28568, 2512991.60535, 2605990.52843, 2701200.01997, 2798646.04499, 2898354.56853, 3000351.55562, 3104662.97129, 3211314.78058, 3320332.94852, 3431743.44013, 3545572.22046, 3661284.29229, 3777883.06101, 3895967.17288, 4015492.83297, 4136416.74759, 4258697.48598, 4382294.05017, 4507165.36302, 4631531.67845, 4757024.71876, 4883638.63072, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0, 5000000.0])
aep.lossFactor = 0.95
check_gradient_unit_test(self, aep, step_size=1) # larger step size b.c. AEP is big value
def test1(self):
gc = GeometricConstraints()
gc.d = [4.0, 3.0, 2.0]
gc.t = [0.4, 0.23, 0.14]
check_gradient_unit_test(self, gc)
def test3(self):
pp = PowerPerformance()
pp.hubHeight = 80.0
pp.permanentMetTowers = 3.0
pp.tempMetTowers = 2.0
check_gradient_unit_test(self, pp)
def test_gradient(self):
comp = BearingSmooth()
comp.bearing_type = 'SRB'
comp.lss_diameter = 0.721049014299
comp.rotor_diameter = 125.740528176
comp.bearing_switch = 'main'
check_gradient_unit_test(self, comp)
def test1(self):
loads = ExtremeLoads()
loads.T = [2414072.40260361, 188461.59444074]
loads.Q = [10926313.24295958, -8041330.51312603]
loads.nBlades = 3
check_gradient_unit_test(self, loads)
def test1(self):
rcdf = RayleighCDF()
rcdf.xbar = 6.0
rcdf.x = np.array([
3.0, 3.08805770406, 3.17611540812, 3.26417311218, 3.35223081624,
3.4402885203, 3.52834622436, 3.61640392842, 3.70446163248,
3.79251933654, 3.8805770406, 3.96863474466, 4.05669244872,
4.14475015278, 4.23280785684, 4.3208655609, 4.40892326496,
4.49698096902, 4.58503867308, 4.67309637714, 4.7611540812,
4.84921178526, 4.93726948932, 5.02532719338, 5.11338489744,
5.2014426015, 5.28950030556, 5.37755800962, 5.46561571369,
5.55367341775, 5.64173112181, 5.72978882587, 5.81784652993,
5.90590423399, 5.99396193805, 6.08201964211, 6.17007734617,
6.25813505023, 6.34619275429, 6.43425045835, 6.52230816241,
6.61036586647, 6.69842357053, 6.78648127459, 6.87453897865,
6.96259668271, 7.05065438677, 7.13871209083, 7.22676979489,
7.31482749895, 7.40288520301, 7.49094290707, 7.57900061113,
7.66705831519, 7.75511601925, 7.84317372331, 7.93123142737,
8.01928913143, 8.10734683549, 8.19540453955, 8.28346224361,
8.37151994767, 8.45957765173, 8.54763535579, 8.63569305985,
8.72375076391, 8.81180846797, 8.89986617203, 8.98792387609,
9.07598158015, 9.16403928421, 9.25209698827, 9.34015469233,
9.42821239639, 9.51627010045, 9.60432780451, 9.69238550857,
9.78044321263, 9.86850091669, 9.95655862075, 10.0446163248,
10.1326740289, 10.2207317329, 10.308789437, 10.3968471411,
10.4849048451, 10.5729625492, 10.6610202532, 10.7490779573,
10.8371356614, 10.9251933654, 11.0132510695, 11.1013087735,
11.1893664776, 11.2774241817, 11.3654818857, 11.4535395898,
11.5415972938, 11.6296549979, 11.717712702, 11.8505355749,
11.9833584479, 12.1161813209, 12.2490041939, 12.3818270669,
12.5146499398, 12.6474728128, 12.7802956858, 12.9131185588,
13.0459414318, 13.1787643047, 13.3115871777, 13.4444100507,
13.5772329237, 13.7100557967, 13.8428786696, 13.9757015426,
14.1085244156, 14.2413472886, 14.3741701616, 14.5069930345,
14.6398159075, 14.7726387805, 14.9054616535, 15.0382845265,
15.1711073994, 15.3039302724, 15.4367531454, 15.5695760184,
15.7023988914, 15.8352217644, 15.9680446373, 16.1008675103,
16.2336903833, 16.3665132563, 16.4993361293, 16.6321590022,
16.7649818752, 16.8978047482, 17.0306276212, 17.1634504942,
17.2962733671, 17.4290962401, 17.5619191131, 17.6947419861,
17.8275648591, 17.960387732, 18.093210605, 18.226033478,
18.358856351, 18.491679224, 18.6245020969, 18.7573249699,
18.8901478429, 19.0229707159, 19.1557935889, 19.2886164618,
19.4214393348, 19.5542622078, 19.6870850808, 19.8199079538,
19.9527308267, 20.0855536997, 20.2183765727, 20.3511994457,
20.4840223187, 20.6168451916, 20.7496680646, 20.8824909376,
21.0153138106, 21.1481366836, 21.2809595565, 21.4137824295,
21.5466053025, 21.6794281755, 21.8122510485, 21.9450739215,
22.0778967944, 22.2107196674, 22.3435425404, 22.4763654134,
22.6091882864, 22.7420111593, 22.8748340323, 23.0076569053,
23.1404797783, 23.2733026513, 23.4061255242, 23.5389483972,
23.6717712702, 23.8045941432, 23.9374170162, 24.0702398891,
24.2030627621, 24.3358856351, 24.4687085081, 24.6015313811,
24.734354254, 24.867177127, 25.0
])
check_gradient_unit_test(self, rcdf, tol=2e-6)
def test1(self):
bedplate = BedplateCost()
bedplate.bedplate_mass = 93090.6
bedplate.year = 2009
bedplate.month = 12
check_gradient_unit_test(self, bedplate)
def test1(self):
bedplate = BedplateCost()
bedplate.bedplate_mass = 93090.6
bedplate.year = 2009
bedplate.month = 12
check_gradient_unit_test(self, bedplate)
def test1(self):
blade = BladeCost()
blade.blade_mass = 17650.67
blade.year = 2009
blade.month = 12
check_gradient_unit_test(self, blade)
def test1(self):
yaw = YawSystemCost()
yaw.yaw_system_mass = 11878.24
yaw.year = 2009
yaw.month = 12
check_gradient_unit_test(self, yaw)
def test1(self):
lss = LowSpeedShaftCost()
lss.low_speed_shaft_mass = 31257.3
lss.year = 2009
lss.month = 12
check_gradient_unit_test(self, lss)
def test1(self):
mp = MassProperties()
mp.blade_mass = 17288.717087
mp.blade_moment_of_inertia = 11634376.0531
mp.tilt = 5.0
mp.nBlades = 3
check_gradient_unit_test(self, mp)
def test1(self):
gust = GustETM()
gust.V_mean = 10.0
gust.V_hub = 11.7733866478
gust.turbulence_class = 'B'
gust.std = 3
check_gradient_unit_test(self, gust)
def test1(self):
comp = Insurance()
comp.TCC = 1000.0
comp.farmSize = 500.0
comp.foundationCost = 1e7
comp.performanceBond = True
check_gradient_unit_test(self, comp)
def test1(self):
mp = MassProperties()
mp.blade_mass = 17288.717087
mp.blade_moment_of_inertia = 11634376.0531
mp.tilt = 5.0
mp.nBlades = 3
check_gradient_unit_test(self, mp)
def test1(self):
rotor = rotor_mass_adder()
rotor.blade_mass = 17000.0
rotor.hub_system_mass = 35000.0
rotor.blade_number = 3
check_gradient_unit_test(self, rotor)
def test1(self):
pitch = PitchSystemCost()
pitch.pitch_system_mass = 17004.0
pitch.year = 2009
pitch.month = 12
check_gradient_unit_test(self, pitch)
def test1(self):
pitch = PitchSystemCost()
pitch.pitch_system_mass = 17004.0
pitch.year = 2009
pitch.month = 12
check_gradient_unit_test(self, pitch)
def test1(self):
rotor = RotorCostAdder()
rotor.blade_cost = 20000.0
rotor.blade_number = 3
rotor.hub_system_cost = 20000.0
check_gradient_unit_test(self, rotor)
def test1(self):
hss = HighSpeedSideCost()
hss.high_speed_side_mass = 1492.45
hss.year = 2009
hss.month = 12
check_gradient_unit_test(self, hss)
def test1(self):
yaw = YawSystemCost()
yaw.yaw_system_mass = 11878.24
yaw.year = 2009
yaw.month = 12
check_gradient_unit_test(self, yaw)
def test1(self):
hss = HighSpeedSideCost()
hss.high_speed_side_mass = 1492.45
hss.year = 2009
hss.month = 12
check_gradient_unit_test(self, hss)
def test1(self):
hub = HubSystemCostAdder()
hub.hub_cost = 20000.0
hub.pitch_system_cost = 20000.0
hub.spinner_cost = 20000.0
check_gradient_unit_test(self, hub)
def test1(self):
lss = LowSpeedShaftCost()
lss.low_speed_shaft_mass = 31257.3
lss.year = 2009
lss.month = 12
check_gradient_unit_test(self, lss)
def test1(self):
rotor = rotor_mass_adder()
rotor.blade_mass = 17000.
rotor.hub_system_mass = 35000.
rotor.blade_number = 3
check_gradient_unit_test(self, rotor)
def test1(self):
rotor = RotorCostAdder()
rotor.blade_cost = 20000.0
rotor.blade_number = 3
rotor.hub_system_cost = 20000.0
check_gradient_unit_test(self, rotor)
def test1(self):
tower = TowerCost()
tower.tower_mass = 434559.0
tower.year = 2009
tower.month = 12
check_gradient_unit_test(self, tower)
def test1(self):
gust = GustETM()
gust.V_mean = 10.0
gust.V_hub = 11.7733866478
gust.turbulence_class = 'B'
gust.std = 3
check_gradient_unit_test(self, gust)
def test1(self):
spinner = SpinnerCost()
spinner.spinner_mass = 1810.5
spinner.year = 2009
spinner.month = 12
check_gradient_unit_test(self, spinner)
def test1(self):
bc = BladeCurvature()
bc.r = np.array([1.5375, 1.84056613137, 1.93905987557, 2.03755361977, 2.14220322299, 2.24069696719, 2.33919071139, 2.90419974, 3.04095863882, 3.13945238302, 5.637500205, 7.04226699698, 8.370800055, 11.8494282928, 13.8375, 14.7182548841, 15.887499795, 18.5537233505, 19.9875, 22.0564071286, 24.087500205, 26.16236509, 28.187499795, 32.2875, 33.5678634821, 36.387500205, 38.5725768593, 40.487499795, 40.6967540173, 40.7964789782, 40.8975, 42.6919644014, 44.5875, 52.787499795, 56.204199945, 58.937499795, 61.67080026, 63.0375])
bc.precurve = np.array([0.0, 0.043324361025, 0.0573893371698, 0.0714469497372, 0.0863751069858, 0.100417566593, 0.114452695996, 0.194824077331, 0.214241777459, 0.228217752953, 0.580295739194, 0.776308800624, 0.960411633829, 1.4368012564, 1.7055214864, 1.823777005, 1.98003324362, 2.32762426752, 2.50856911855, 2.76432512112, 3.0113656418, 3.26199245912, 3.50723775206, 4.0150233695, 4.17901272929, 4.55356019347, 4.85962948702, 5.14086873143, 5.17214747287, 5.18708601127, 5.20223968442, 5.47491847385, 5.77007321175, 7.12818875977, 7.7314427824, 8.22913789456, 8.73985955154, 9.0])
bc.presweep = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])
bc.precone = 2.5
check_gradient_unit_test(self, bc, tol=5e-5)
def test1(self):
hub = HubCost()
hub.hub_mass = 31644.5
hub.year = 2009
hub.month = 12
check_gradient_unit_test(self, hub)
def test1(self):
tower = TowerCost()
tower.tower_mass = 434559.0
tower.year = 2009
tower.month = 12
check_gradient_unit_test(self, tower)
def test1(self):
blade = BladeCost()
blade.blade_mass = 17650.67
blade.year = 2009
blade.month = 12
check_gradient_unit_test(self, blade)
def test1(self):
hub = HubCost()
hub.hub_mass = 31644.5
hub.year = 2009
hub.month = 12
check_gradient_unit_test(self, hub)
def test1(self):
hub = HubSystemCostAdder()
hub.hub_cost = 20000.0
hub.pitch_system_cost = 20000.0
hub.spinner_cost = 20000.0
check_gradient_unit_test(self, hub)
def test1(self):
comp = Insurance()
comp.TCC = 1000.0
comp.farmSize = 500.0
comp.foundationCost = 1e7
comp.performanceBond = True
check_gradient_unit_test(self, comp)
def test1(self):
setup = SetupPCModVarSpeed()
setup.control.tsr = 8.0
setup.control.pitch = 1.0
setup.Vrated = 12.0
setup.R = 63.0
setup.Vfactor = 0.7
check_gradient_unit_test(self, setup)
def test1(self):
t = Transportation()
t.TCC = 1000.0
t.rating = 5000.0
t.nTurbines = 100
t.hubHeight = 90.0
t.transportDist = 3.0
check_gradient_unit_test(self, t)
