def configure(self):
common_io_with_ccblade(self, self.varspeed, self.varpitch, self.cdf_type)
common_configure_with_ccblade(self, self.varspeed, self.varpitch, self.cdf_type)
# used for normalization of objective
self.add('AEP0', Float(1.0, iotype='in', desc='used for normalization'))
if self.optimizer == 'snopt':
self.replace('driver', pyOptDriver())
self.driver.optimizer = 'SNOPT'
self.driver.options = {'Major feasibility tolerance': 1e-6,
'Minor feasibility tolerance': 1e-6,
'Major optimality tolerance': 1e-5,
'Function precision': 1e-8,
'Iterations limit': 100,
'Print file': 'harpopt_snopt.out',
'Summary file': 'harpopt_snopt_summary.out'}
elif self.optimizer == 'psqp':
self.replace('driver', pyOptDriver())
self.driver.optimizer = 'PSQP'
self.driver.options = {'XMAX': 100.0,
'TOLG': 1e-4,
'MFV': 100,
'IFILE': 'harpopt_psqp.out'}
elif self.optimizer == 'slsqp':
self.replace('driver', SLSQPdriver())
self.driver.accuracy = 1.0e-6
self.driver.maxiter = 500
elif self.optimizer == "conmin":
self.replace('driver', CONMINdriver())
self.driver.delfun = 1e-6
self.driver.itmax = 500
else:
print 'invalid optimizer specified'
exit()
# objective
self.driver.add_objective('-aep.AEP/AEP0') # maximize AEP
# design variables
self.driver.add_parameter('r_max_chord', low=0.1, high=0.5)
self.driver.add_parameter('chord_sub', low=0.4, high=5.3)
self.driver.add_parameter('theta_sub', low=-10.0, high=30.0)
if self.varspeed:
self.driver.add_parameter('control.tsr', low=3.0, high=14.0)
# if optimize_stations:
# self.driver.add_parameter('r_af[1:-1]', low=0.01, high=0.99)
# outfile = open('results.txt', 'w')
# self.driver.recorders = [DumpCaseRecorder(outfile)]
self.driver.recorders = [DumpCaseRecorder()]
if self.optimizer == 'snopt' or self.optimizer == 'psqp': # pyopt has an oustanding bug for unconstrained problems, so adding inconsequential constraint
self.driver.add_constraint('spline.r_max_chord > 0.0')
def configure(self):
""" Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
# Create MultiFunction component instances
self.add('multifunction', MultiFunction())
# Create NSGA2 Optimizer instance
self.add('driver', pyOptDriver())
# Driver process definition
self.driver.workflow.add('multifunction')
self.driver.print_results = False
# NSGA2 Objective
self.driver.add_objective('multifunction.f1_x')
self.driver.add_objective('multifunction.f2_x')
# NSGA2 Design Variable
self.driver.add_parameter('multifunction.x1', low=0.1, high=1.0)
self.driver.add_parameter('multifunction.x2', low=0.0, high=5.0)
# NSGA2 Constraints
self.driver.add_constraint('multifunction.g1_x >= 6.0')
self.driver.add_constraint('multifunction.g2_x >= 1.0')
def __init__(self):
""" Creates a new Assembly containing a Paraboloid and an optimizer"""
# pylint: disable-msg=E1101
super(OptimizationConstrainedDerivatives, self).__init__()
# Create Paraboloid component instances
self.add('paraboloid', ParaboloidDerivative())
# Create CONMIN Optimizer instance
self.add('driver', pyOptDriver())
# Driver process definition
self.driver.workflow.add('paraboloid')
# CONMIN Objective
self.driver.add_objective('paraboloid.f_xy')
# CONMIN Design Variables
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_parameter('paraboloid.y', low=-50., high=50.)
# CONMIN Constraints
self.driver.add_constraint('paraboloid.x-paraboloid.y >= 15.0')
self.driver.print_results = False
self.driver.differentiator = FiniteDifference()
def configure(self):
""" Creates a new Assembly containing a Paraboloid and an optimizer"""
# pylint: disable=E1101
# Create Paraboloid component instances
self.add('paraboloid', Paraboloid())
# Create CONMIN Optimizer instance
self.add('driver', pyOptDriver())
# Driver process definition
self.driver.workflow.add('paraboloid')
# CONMIN Objective
self.driver.add_objective('paraboloid.f_xy')
# CONMIN Design Variables
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_parameter('paraboloid.y', low=-50., high=50.)
# CONMIN Constraints
self.driver.add_constraint('paraboloid.x-paraboloid.y >= 15.0')
self.driver.print_results = False
def configure(self):
# Create Optimizer instance
self.add('driver', pyOptDriver())
# Create Paraboloid component instances
self.add('one', one())
# Iteration Hierarchy
self.driver.workflow.add('one')
# SLSQP Flags
self.driver.iprint = 2
# Objective
self.driver.add_objective('one.f')
# Design Variables
self.driver.add_parameter('one.x', low=3.5, high=50.5)
# self.driver.add_parameter('one.y', low=1.0, high=500.)
# Constraints
# self.driver.add_constraint('3.0*one.x**2.0*one.y>=50.0')
# self.driver.add_constraint('3.0*one.x**2.0*one.y<=50.0')
# self.driver.gradient_options.fd_form = 'forward'
# self.driver.xmax = 0.000000000001
self.driver.optimizer = 'ALPSO'
def configure(self):
""" Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
# Create MultiFunction component instances
self.add('multifunction', MultiFunction())
# Create NSGA2 Optimizer instance
self.add('driver', pyOptDriver())
# Driver process definition
self.driver.workflow.add('multifunction')
self.driver.print_results = False
# NSGA2 Objective
self.driver.add_objective('multifunction.f1_x')
self.driver.add_objective('multifunction.f2_x')
# NSGA2 Design Variable
self.driver.add_parameter('multifunction.x1', low=0.1, high=1.0)
self.driver.add_parameter('multifunction.x2', low=0.0, high=5.0)
# NSGA2 Constraints
self.driver.add_constraint('multifunction.g1_x >= 6.0')
self.driver.add_constraint('multifunction.g2_x >= 1.0')
def configure(self):
""" Creates a new Assembly containing a Paraboloid and an optimizer"""
# pylint: disable=E1101
# Create Paraboloid component instances
self.add('paraboloid', Paraboloid())
# Create CONMIN Optimizer instance
self.add('driver', pyOptDriver())
# Driver process definition
self.driver.workflow.add('paraboloid')
# CONMIN Objective
self.driver.add_objective('paraboloid.f_xy')
# CONMIN Design Variables
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_parameter('paraboloid.y', low=-50., high=50.)
# CONMIN Constraints
self.driver.add_constraint('paraboloid.x-paraboloid.y >= 15.0')
self.driver.print_results = False
def configure(self):
# add an optimizer and an AeroStructural assembly
if pyopt_driver and 'SNOPT' in pyopt_driver._check_imports():
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {
# any changes to default SNOPT options?
}
else:
print 'SNOPT not available, using SLSQP'
self.add('driver', SLSQPdriver())
self.add('aso', AeroStructuralOpt())
# objective: minimize total power
self.driver.add_objective('aso.Ptot')
# parameter: rotor speed
self.driver.add_parameter('aso.Omega_opt',
low=0.15 * 2 * pi,
high=0.25 * 2 * pi)
self.aso.Omega_opt = 0.2 * 2 * pi # initial value
# constraint: lift >= weight
self.driver.add_constraint('aso.Mtot*9.8-aso.Ttot<=0')
def configure(self):
# Create Optimizer instance
self.add('driver', pyOptDriver())
# Create Paraboloid component instances
self.add('one', one())
# Iteration Hierarchy
self.driver.workflow.add('one')
# SLSQP Flags
self.driver.iprint = 2
# Objective
self.driver.add_objective('one.f')
# Design Variables
self.driver.add_parameter('one.x', low=3.5, high=50.5)
# self.driver.add_parameter('one.y', low=1.0, high=500.)
# Constraints
# self.driver.add_constraint('3.0*one.x**2.0*one.y>=50.0')
# self.driver.add_constraint('3.0*one.x**2.0*one.y<=50.0')
# self.driver.gradient_options.fd_form = 'forward'
# self.driver.xmax = 0.000000000001
self.driver.optimizer = 'ALPSO'
def configure(self):
self.add('func',Rosenbrock())
self.connect('func.f','output')
self.add('driver',pyOptDriver())
self.driver.optimizer='NSGA2'
self.driver.options={'maxGen':250,'pMut_real':0.4}
self.driver.add_objective('func.f')
self.driver.add_parameter('func.x1')
self.driver.add_parameter('func.x2')
self.driver.add_constraint('func.x1+func.x2-2.0<=0.0')
def configure(self):
self.add('func', Rosenbrock())
self.connect('func.f', 'output')
self.add('driver', pyOptDriver())
self.driver.optimizer = 'NSGA2'
self.driver.options = {'maxGen': 250, 'pMut_real': 0.4}
self.driver.add_objective('func.f')
self.driver.add_parameter('func.x1')
self.driver.add_parameter('func.x2')
self.driver.add_constraint('func.x1+func.x2-2.0<=0.0')
def test_initial_run(self):
# Test to make sure fix that put run_iteration
# at the top of the execute method is in place and working
class MyComp(Component):
x = Float(0.0, iotype='in', low=-10, high=10)
xx = Float(0.0, iotype='in', low=-10, high=10)
f_x = Float(iotype='out')
y = Float(iotype='out')
def execute(self):
if self.xx != 1.0:
self.raise_exception("Lazy", RuntimeError)
self.f_x = 2.0*self.x
self.y = self.x
@add_delegate(HasParameters)
class SpecialDriver(Driver):
implements(IHasParameters)
def execute(self):
self.set_parameters([1.0])
top = set_as_top(Assembly())
top.add('comp', MyComp())
try:
from pyopt_driver.pyopt_driver import pyOptDriver
except ImportError:
raise SkipTest("this test requires pyOpt to be installed")
try:
top.driver.optimizer = 'CONMIN'
except ValueError:
raise SkipTest("CONMIN not present on this system")
top.driver.title = 'Little Test'
optdict = {}
top.driver.options = optdict
top.driver.pyopt_diff = True
top.add('driver', pyOptDriver())
top.add('subdriver', SpecialDriver())
top.driver.workflow.add('subdriver')
top.subdriver.workflow.add('comp')
top.subdriver.add_parameter('comp.xx')
top.driver.add_parameter('comp.x')
top.driver.add_constraint('comp.y > 1.0')
top.driver.add_objective('comp.f_x')
top.run()
def test_initial_run(self):
# Test to make sure fix that put run_iteration
# at the top of the execute method is in place and working
class MyComp(Component):
x = Float(0.0, iotype='in', low=-10, high=10)
xx = Float(0.0, iotype='in', low=-10, high=10)
f_x = Float(iotype='out')
y = Float(iotype='out')
def execute(self):
if self.xx != 1.0:
self.raise_exception("Lazy", RuntimeError)
self.f_x = 2.0 * self.x
self.y = self.x
@add_delegate(HasParameters)
class SpecialDriver(Driver):
implements(IHasParameters)
def execute(self):
self.set_parameters([1.0])
top = set_as_top(Assembly())
top.add('comp', MyComp())
try:
from pyopt_driver.pyopt_driver import pyOptDriver
except ImportError:
raise SkipTest("this test requires pyOpt to be installed")
try:
top.driver.optimizer = 'CONMIN'
except ValueError:
raise SkipTest("CONMIN not present on this system")
top.driver.title = 'Little Test'
optdict = {}
top.driver.options = optdict
top.driver.pyopt_diff = True
top.add('driver', pyOptDriver())
top.add('subdriver', SpecialDriver())
top.driver.workflow.add('subdriver')
top.subdriver.workflow.add('comp')
top.subdriver.add_parameter('comp.xx')
top.driver.add_parameter('comp.x')
top.driver.add_constraint('comp.y > 1.0')
top.driver.add_objective('comp.f_x')
top.run()
def configure(self):
""" Creates a new Assembly containing ArrayParaboloid and an optimizer"""
# pylint: disable=E1101
self.add('paraboloid', ArrayParaboloid())
self.add('driver', pyOptDriver())
self.driver.pyopt_diff = True
self.driver.workflow.add('paraboloid')
self.driver.add_objective('paraboloid.f_xy')
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_constraint('paraboloid.x[0]-paraboloid.x[1] >= 15.0')
self.driver.print_results = False
def configure(self):
""" Creates a new Assembly containing ArrayParaboloid and an optimizer"""
# pylint: disable=E1101
self.add('paraboloid', ArrayParaboloid())
self.add('driver', pyOptDriver())
self.driver.pyopt_diff = True
self.driver.workflow.add('paraboloid')
self.driver.add_objective('paraboloid.f_xy')
self.driver.add_parameter('paraboloid.x', low=-50., high=50.)
self.driver.add_constraint('paraboloid.x[0]-paraboloid.x[1] >= 15.0')
self.driver.print_results = False
def __init__(self):
"""Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
super(BenchMarkOptimization, self).__init__()
# Create MultiFunction component instances
self.add('benchmark', BenchMark())
# Create ALPSO Optimizer instance
self.add('driver', pyOptDriver())
# Driver process definition
self.driver.workflow.add('benchmark')
# PyOpt Flags
self.driver.optimizer = 'ALPSO'
self.driver.title = 'Bench mark problem 4 - Unconstrained'
optdict = {}
optdict['SwarmSize'] = 40
optdict['maxOuterIter'] = 100
optdict['maxInnerIter'] = 3
optdict['minInnerIter'] = 3
optdict['etol'] = 1e-4
optdict['itol'] = 1e-4
optdict['c1'] = 0.8
optdict['c2'] = 0.8
optdict['w1'] = 0.9
optdict['nf'] = 5
optdict['dt'] = 1.0
optdict['vcrazy'] = 1e-4
optdict['Scaling'] = 1
optdict['seed'] = 1.0
self.driver.options = optdict
# ALPSO Objective
self.driver.add_objective('benchmark.f_x')
# ALPSO Design Variables
self.driver.add_parameter('benchmark.x1', low=0, high=42)
self.driver.add_parameter('benchmark.x2', low=0, high=42)
self.driver.add_parameter('benchmark.x3', low=0, high=42)
# ALPSO Constraints
self.driver.add_constraint('benchmark.g1_x <= 0.0')
self.driver.add_constraint('benchmark.h1_x <= 0.0')
def __init__(self):
"""Creates a new Assembly containing a MultiFunction and an optimizer"""
# pylint: disable=E1101
super(BenchMarkOptimization, self).__init__()
# Create MultiFunction component instances
self.add('benchmark', BenchMark())
# Create ALPSO Optimizer instance
self.add('driver', pyOptDriver())
# Driver process definition
self.driver.workflow.add('benchmark')
# PyOpt Flags
self.driver.optimizer = 'ALPSO'
self.driver.title = 'Bench mark problem 4 - Unconstrained'
optdict = {}
optdict['SwarmSize'] = 40
optdict['maxOuterIter'] = 100
optdict['maxInnerIter'] = 3
optdict['minInnerIter'] = 3
optdict['etol'] = 1e-4
optdict['itol'] = 1e-4
optdict['c1'] = 0.8
optdict['c2'] = 0.8
optdict['w1'] = 0.9
optdict['nf'] = 5
optdict['dt'] = 1.0
optdict['vcrazy'] = 1e-4
optdict['Scaling'] = 1
optdict['seed'] = 1.0
self.driver.options = optdict
# ALPSO Objective
self.driver.add_objective('benchmark.f_x')
# ALPSO Design Variables
self.driver.add_parameter('benchmark.x1', low=0, high=42)
self.driver.add_parameter('benchmark.x2', low=0, high=42)
self.driver.add_parameter('benchmark.x3', low=0, high=42)
# ALPSO Constraints
self.driver.add_constraint('benchmark.g1_x <= 0.0')
self.driver.add_constraint('benchmark.h1_x <= 0.0')
def configure(self):
self.driver = self.add('driver', pyOptDriver())
self.driver.optimizer = 'NSGA2'
self.driver.pyopt_diff = True
self.driver.options["PopSize"] = 4
self.driver.options["maxGen"] = 100
self.add('roseSA',rosenSA())
self.add('dakBak', get_dak_output())
self.driver.workflow.add('roseSA')
self.driver.workflow.add('dakBak')
self.add('x1',Float(0.4, iotype = 'in'))
self.driver.add_parameter('x1', low = -6, high = 6)
self.connect('x1', ['roseSA.x1', 'dakBak.x1'])
self.driver.add_objective('dakBak.mean_f')
def configure(self):
self.driver = self.add('driver', pyOptDriver())
self.driver.optimizer = 'NSGA2'
self.driver.pyopt_diff = True
self.driver.options["PopSize"] = 4
self.driver.options["maxGen"] = 100
self.add('roseSA', rosenSA())
self.add('dakBak', get_dak_output())
self.driver.workflow.add('roseSA')
self.driver.workflow.add('dakBak')
self.add('x1', Float(0.4, iotype='in'))
self.driver.add_parameter('x1', low=-6, high=6)
self.connect('x1', ['roseSA.x1', 'dakBak.x1'])
self.driver.add_objective('dakBak.mean_f')
def configure(self):
# add an optimizer and an AeroStructural assembly
if pyopt_driver and 'SNOPT' in pyopt_driver._check_imports():
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {
# any changes to default SNOPT options?
}
else:
print 'SNOPT not available, using SLSQP'
self.add('driver', SLSQPdriver())
self.add('aso', AeroStructuralOpt())
# objective: minimize total power
self.driver.add_objective('aso.Ptot')
# parameter: rotor speed
self.driver.add_parameter('aso.Omega_opt',
low=0.15*2*pi, high=0.25*2*pi)
self.aso.Omega_opt = 0.2*2*pi # initial value
# constraint: lift >= weight
self.driver.add_constraint('aso.Mtot*9.8-aso.Ttot<=0')
def __init__(self, n=1500, m=300, npts=6):
super(CADRE_Optimization, self).__init__()
# add SNOPT driver
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {
'Major optimality tolerance': 1e-3,
'Iterations limit': 500000000,
"New basis file": 10
}
if os.path.exists("fort.10"):
self.driver.options["Old basis file"] = 10
#driver = self.add("driver", CONMINdriver())
# Raw data to load
fpath = os.path.dirname(os.path.realpath(__file__))
fpath = os.path.join(fpath, 'src/CADRE/data')
solar_raw1 = np.genfromtxt(fpath + '/Solar/Area10.txt')
solar_raw2 = np.loadtxt(fpath + '/Solar/Area_all.txt')
comm_rawGdata = np.genfromtxt(fpath + '/Comm/Gain.txt')
comm_raw = (10**(comm_rawGdata / 10.0)).reshape((361, 361), order='F')
power_raw = np.genfromtxt(fpath + '/Power/curve.dat')
# Load launch data
launch_data = np.loadtxt(fpath + '/Launch/launch1.dat')
# orbit position and velocity data for each design point
r_e2b_I0s = launch_data[1::2, 1:]
# number of days since launch for each design point
LDs = launch_data[1::2, 0] - 2451545
# build design points
names = ['pt%s' % i for i in range(npts)]
for i, name in enumerate(names):
comp = self.add(
name, CADRE(n, m, solar_raw1, solar_raw2, comm_raw, power_raw))
self.driver.workflow.add(name)
comp.set("LD", LDs[i])
comp.set("r_e2b_I0", r_e2b_I0s[i])
# add parameters to driver
self.driver.add_parameter("%s.CP_Isetpt" % name, low=0., high=0.4)
self.driver.add_parameter("%s.CP_gamma" % name,
low=0,
high=np.pi / 2.)
self.driver.add_parameter("%s.CP_P_comm" % name, low=0., high=25.)
self.driver.add_parameter("%s.iSOC[0]" % name, low=0.2, high=1.)
# add constraints
self.driver.add_constraint("%s.ConCh <= 0" % name)
self.driver.add_constraint("%s.ConDs <= 0" % name)
self.driver.add_constraint("%s.ConS0 <= 0" % name)
self.driver.add_constraint("%s.ConS1 <= 0" % name)
self.driver.add_constraint("%s.SOC[0][0] = %s.SOC[0][-1]" %
(name, name))
# add parameter groups
cell_param = ["%s.cellInstd" % name for name in names]
self.driver.add_parameter(cell_param, low=0, high=1)
finangles = ["%s.finAngle" % name for name in names]
self.driver.add_parameter(finangles, low=0, high=np.pi / 2.)
antangles = ["%s.antAngle" % name for name in names]
self.driver.add_parameter(antangles, low=-np.pi / 4, high=np.pi / 4)
# add objective
obj = ''.join(["-%s.Data[0][-1]" % name for name in names])
self.driver.add_objective(obj)
def __init__(self, n=1500, m=300):
super(CADRE_Optimization, self).__init__()
npts = 6
# add SNOPT driver
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {'Major optimality tolerance': 1e-8,
'Iterations limit': 500000000}
#self.add("driver", CONMINdriver())
# specify ground station
self.add("lon", Float(-83.7264, iotype="in"))
self.add("lat", Float(42.2708, iotype="in"))
self.add("alt", Float(0.256, iotype="in"))
# Raw data to load
solar_raw1 = np.genfromtxt('CADRE/data/Solar/Area10.txt')
solar_raw2 = np.loadtxt("CADRE/data/Solar/Area_all.txt")
comm_rawGdata = np.genfromtxt('CADRE/data/Comm/Gain.txt')
comm_raw = (10 ** (comm_rawGdata / 10.0)).reshape(
(361, 361), order='F')
power_raw = np.genfromtxt('CADRE/data/Power/curve.dat')
# Initialize analysis points
LDs = [5233.5, 5294.5, 5356.5, 5417.5, 5478.5, 5537.5]
r_e2b_I0s = [np.array([4505.29362, -3402.16069, -3943.74582,
4.1923899, -1.56280012, 6.14347427]),
np.array(
[-1005.46693, -597.205348, -6772.86532, -0.61047858,
-7.54623146, 0.75907455]),
np.array(
[4401.10539, 2275.95053, -4784.13188, -5.26605537,
-1.08194926, -5.37013745]),
np.array(
[-4969.91222, 4624.84149, 1135.9414, 0.1874654,
-1.62801666, 7.4302362]),
np.array(
[-235.021232, 2195.72976, 6499.79919, -2.55956031,
-6.82743519, 2.21628099]),
np.array(
[-690.314375, -1081.78239, -6762.90367, 7.44316722,
1.19745345, -0.96035904])]
for i in xrange(npts):
aname = ''.join(["pt", str(i)])
self.add(aname, CADRE(n, m, solar_raw1, solar_raw2,
comm_raw, power_raw))
self.connect("alt", "pt%s.alt" % str(i))
self.connect("lon", "pt%s.lon" % str(i))
self.connect("lat", "pt%s.lat" % str(i))
self.get(aname).set("LD", LDs[i])
self.get(aname).set("r_e2b_I0", r_e2b_I0s[i])
# add parameters to driver
print "adding parameter: CP_Isetpt.."
for k in xrange(12):
for j in xrange(m):
param = ''.join(["pt", str(i), ".CP_Isetpt[", str(k), "][",
str(j), "]"])
self.driver.add_parameter(param, low=0.2, high=0.4)
print "adding parameter: CP_gamma.."
for k in xrange(m):
param = ''.join(["pt", str(i), ".CP_gamma[", str(k), "]"])
self.driver.add_parameter(param, low=np.pi / 4,
high=np.pi / 2.)
print "adding parameter: CP_comm.."
for k in xrange(m):
param = ''.join(["pt", str(i), ".CP_P_comm[", str(k), "]"])
self.driver.add_parameter(param, low=0.1, high=25.)
param = ''.join(["pt", str(i), ".iSOC[0]"])
self.driver.add_parameter(param, low=0.2, high=1.)
# add battery constraints
constr = ''.join(["pt", str(i), ".ConCh <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".ConDs <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".ConS0 <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".ConS1 <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".SOC[0][0] = pt",
str(i), ".SOC[0][-1]"])
self.driver.add_constraint(constr)
# add rest of parameters to driver
print "adding constraint: Cellinstd..."
for i in xrange(7):
for k in xrange(12):
param = [''.join(["pt", str(j), ".cellInstd[", str(i),
"][", str(k), "]"]) for j in xrange(npts)]
self.driver.add_parameter(param, low=0, high=1)
finangles = ["pt" + str(i) + ".finAngle" for i in xrange(npts)]
antangles = ["pt" + str(i) + ".antAngle" for i in xrange(npts)]
self.driver.add_parameter(finangles, low=0, high=np.pi / 2.)
self.driver.add_parameter(antangles, low=-np.pi / 4, high=np.pi / 4)
# add objective
obj = ''.join([''.join(["-pt", str(i), ".Data[0][-1]"])
for i in xrange(npts)])
self.driver.add_objective(obj)
plt.legend(bbox_to_anchor=(1.05, 1.0), loc=2)
plt.xlabel('utilization')
plt.ylabel('height along tower (m)')
plt.show()
# ------------
if optimize:
# --- optimizer imports ---
from pyopt_driver.pyopt_driver import pyOptDriver
from openmdao.lib.casehandlers.api import DumpCaseRecorder
# ----------------------
# --- Setup Pptimizer ---
tower.replace('driver', pyOptDriver())
tower.driver.optimizer = 'SNOPT'
tower.driver.options = {'Major feasibility tolerance': 1e-6,
'Minor feasibility tolerance': 1e-6,
'Major optimality tolerance': 1e-5,
'Function precision': 1e-8}
# ----------------------
# --- Objective ---
tower.driver.add_objective('tower1.mass / 300000')
# ----------------------
# --- Design Variables ---
tower.driver.add_parameter('z_param[1]', low=0.0, high=87.0)
tower.driver.add_parameter('d_param[:-1]', low=3.87, high=20.0)
tower.driver.add_parameter('t_param', low=0.005, high=0.2)
def __init__(self, n=1500, m=300, npts=6):
super(CADRE_Optimization, self).__init__()
# add SNOPT driver
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {'Major optimality tolerance': 1e-3,
'Iterations limit': 500000000,
"New basis file": 10}
if os.path.exists("fort.10"):
self.driver.options["Old basis file"] = 10
#driver = self.add("driver", CONMINdriver())
# Raw data to load
fpath = os.path.dirname(os.path.realpath(__file__))
fpath = os.path.join(fpath, 'data')
solar_raw1 = np.genfromtxt(fpath + '/Solar/Area10.txt')
solar_raw2 = np.loadtxt(fpath + '/Solar/Area_all.txt')
comm_rawGdata = np.genfromtxt(fpath + '/Comm/Gain.txt')
comm_raw = (10 ** (comm_rawGdata / 10.0)
).reshape((361, 361), order='F')
power_raw = np.genfromtxt(fpath + '/Power/curve.dat')
# Load launch data
launch_data = np.loadtxt(fpath + '/Launch/launch1.dat')
# orbit position and velocity data for each design point
r_e2b_I0s = launch_data[1::2, 1:]
# number of days since launch for each design point
LDs = launch_data[1::2, 0] - 2451545
# build design points
names = ['pt%s' % i for i in range(npts)]
for i, name in enumerate(names):
comp = self.add(name, CADRE(n, m, solar_raw1, solar_raw2,
comm_raw, power_raw))
comp.set("LD", LDs[i])
comp.set("r_e2b_I0", r_e2b_I0s[i])
# add parameters to driver
self.driver.add_parameter("%s.CP_Isetpt" % name, low=0., high=0.4)
self.driver.add_parameter("%s.CP_gamma" %
name, low=0, high=np.pi / 2.)
self.driver.add_parameter("%s.CP_P_comm" % name, low=0., high=25.)
self.driver.add_parameter("%s.iSOC[0]" % name, low=0.2, high=1.)
# add constraints
self.driver.add_constraint("%s.ConCh <= 0" % name)
self.driver.add_constraint("%s.ConDs <= 0" % name)
self.driver.add_constraint("%s.ConS0 <= 0" % name)
self.driver.add_constraint("%s.ConS1 <= 0" % name)
self.driver.add_constraint(
"%s.SOC[0][0] = %s.SOC[0][-1]" % (name, name))
# add parameter groups
cell_param = ["%s.cellInstd" % name for name in names]
self.driver.add_parameter(cell_param, low=0, high=1)
finangles = ["%s.finAngle" % name for name in names]
self.driver.add_parameter(finangles, low=0, high=np.pi / 2.)
antangles = ["%s.antAngle" % name for name in names]
self.driver.add_parameter(antangles, low=-np.pi / 4, high=np.pi / 4)
# add objective
obj = ''.join(["-%s.Data[0][-1]" % name for name in names])
self.driver.add_objective(obj)
plt.xlabel('wind speed (m/s)')
plt.ylabel('power (MW)')
plt.show()
# --------------------------
if optimize:
# --- optimizer imports ---
from pyopt_driver.pyopt_driver import pyOptDriver
from openmdao.lib.casehandlers.api import DumpCaseRecorder
# ----------------------
# --- Setup Pptimizer ---
rotor.replace('driver', pyOptDriver())
rotor.driver.optimizer = 'SNOPT'
rotor.driver.options = {'Major feasibility tolerance': 1e-6,
'Minor feasibility tolerance': 1e-6,
'Major optimality tolerance': 1e-5,
'Function precision': 1e-8}
# ----------------------
# --- Objective ---
rotor.driver.add_objective('-aep.AEP/%f' % AEP0)
# ----------------------
# --- Design Variables ---
rotor.driver.add_parameter('r_max_chord', low=0.1, high=0.5)
rotor.driver.add_parameter('chord_sub', low=0.4, high=5.3)
rotor.driver.add_parameter('theta_sub', low=-10.0, high=30.0)
plt.plot(rotor.V, rotor.P / 1e6)
plt.xlabel('wind speed (m/s)')
plt.ylabel('power (MW)')
plt.show()
# --------------------------
if optimize:
# --- optimizer imports ---
from pyopt_driver.pyopt_driver import pyOptDriver
from openmdao.lib.casehandlers.api import DumpCaseRecorder
# ----------------------
# --- Setup Pptimizer ---
rotor.replace('driver', pyOptDriver())
rotor.driver.optimizer = 'SNOPT'
rotor.driver.options = {
'Major feasibility tolerance': 1e-6,
'Minor feasibility tolerance': 1e-6,
'Major optimality tolerance': 1e-5,
'Function precision': 1e-8
}
# ----------------------
# --- Objective ---
rotor.driver.add_objective('-aep.AEP/%f' % AEP0)
# ----------------------
# --- Design Variables ---
rotor.driver.add_parameter('r_max_chord', low=0.1, high=0.5)
def opt_tower(
sea_depth=np.array([]),
hmax_50yr=None,
tp_50yr=None,
deck_height=None,
d_monopile=None,
t_monopile=None,
t_jacket=None,
d_tower_base=None,
d_tower_top=None,
t_tower_base=None,
t_tower_top=None,
):
mytwr = main()[0]
MDAOswitch = "md_pysnopt"
# optimization
import pyOpt
from pyopt_driver.pyopt_driver import pyOptDriver
from openmdao.lib.casehandlers.api import DumpCaseRecorder
from openmdao.lib.drivers.api import COBYLAdriver
if MDAOswitch == "md_cobyla":
mytwr.replace("driver", COBYLAdriver())
mytwr.driver.rhobeg = 0.01
mytwr.driver.rhoend = 1.0e-3
mytwr.driver.maxfun = 2000
mytwr.driver.iprint = 1
else:
mytwr.replace("driver", pyOptDriver())
if MDAOswitch == "md_pysnopt":
mytwr.driver.optimizer = "SNOPT"
mytwr.driver.pyopt_diff = True
# mytwr.driver.sens_step = 1e-8
mytwr.driver.options = {
"Major feasibility tolerance": 1e-4,
"Minor feasibility tolerance": 1e-4,
"Major optimality tolerance": 1e-4,
"Function precision": 1e-6,
}
elif MDAOswitch == "md_pyCobyla":
mytwr.driver.optimizer = "COBYLA"
mytwr.driver.options = {"RHOEND": 1.0e-2, "RHOEND": 1.0e-3, "MAXFUN": 2000, "IPRINT": 1}
else:
sys.exit(
"Error: MDAOswitch must be set to "
"pyCobyla"
" or "
"pySNOPT"
" or "
"md_cobyla"
" or "
"md_pySNOPT"
" or "
"md_pyCobyla"
"!!!"
)
# ----------------------
# --- Objective ---
mytwr.driver.add_objective("(tower1.mass) / 500.e3")
# ----------------------
# diameter and thickness variables
mytwr.driver.add_parameter("d_monopile", low=3.0, high=15.0) # this is OD monopile
mytwr.driver.add_parameter("t_monopile", low=0.01, high=0.1) # this is t of monopile
mytwr.driver.add_parameter(
"t_jacket", low=0.01, high=0.1
) # this is t of jacket # d jacket fixed by monopile + t_jacket + t_grout
mytwr.driver.add_parameter("d_tower_base", low=3.0, high=15.0) # This is OD at the base
mytwr.driver.add_parameter("t_tower_base", low=0.01, high=0.3) # This is t at the base
mytwr.driver.add_parameter("d_tower_top", low=3.87, high=8.0) # This is OD at the top # OD at top should be fixed
mytwr.driver.add_parameter("t_tower_top", low=0.01, high=0.1) # This is t at top
# node positioning variables
# mytwr.driver.add_parameter('jp.z[5]', low= 0.0, high= 0.99) # this is H2 (can't move this - will have to add extra variable to make that happen)
# --- Constraints ---#
# frequency
mytwr.driver.add_constraint("tower1.f1 >= 0.20") # from 0.28 to 0.26
# mytwr.driver.add_constraint('tower1.f1 <= 0.30')
# utilization
mytwr.driver.add_constraint("tower1.stress <= 1.0")
mytwr.driver.add_constraint("tower2.stress <= 1.0")
mytwr.driver.add_constraint("tower1.buckling <= 1.0")
mytwr.driver.add_constraint("tower2.buckling <= 1.0")
mytwr.driver.add_constraint("tower1.shellBuckling <= 1.0")
mytwr.driver.add_constraint("tower2.shellBuckling <= 1.0")
mytwr.driver.add_constraint("tower1.damage <= 1.0")
# mytwr.driver.add_constraint('gc.weldability <= 0.0') # this goes for entire structure which we don't want
# mytwr.driver.add_constraint('gc.manufacturability <= 0.0') # just going to use explicit constraints below
# uniformity of diameter and thickness of tower
mytwr.driver.add_constraint("d_tower_top <= d_tower_base")
mytwr.driver.add_constraint("d_tower_base <= d_monopile")
# mytwr.driver.add_constraint('d_monopile - d_tower_base <= 0.4')
mytwr.driver.add_constraint("t_tower_top <= t_tower_base")
# manufacturing and installation
mytwr.driver.add_constraint(
"d_tower_top/d_tower_base >= 0.40"
) # manufacturability - already covered; taper ratio for manufacturing
mytwr.driver.add_constraint(
"d_tower_base/t_tower_base >= 120.0"
) # weldibility - already covered; tower DTR for rolling operation
mytwr.driver.add_constraint("d_tower_top/t_tower_top >= 120.0")
# mytwr.driver.add_constraint('d_monopile/t_monopile <= 100.0') # pile DTR for installation
# mytwr.driver.add_constraint('d_tower_base/t_tower_base <= 200.0') # tower DTR for welding (not covered)
# mytwr.driver.add_constraint('d_tower_top/t_tower_top <= 200.0')
## mytwr.driver.add_constraint('Lp0rat >= 0.') # was for embedment - not in model
# ----------------------
# set optimization variables
if sea_depth.size:
for i in range(len(sea_depth)):
mytwr.sea_depth = sea_depth[i]
mytwr.deck_height = deck_height[i]
mytwr.wave1.hs = hmax_50yr[i]
mytwr.wave1.T = tp_50yr[i]
mytwr.wave2.hs = hmax_50yr[i]
mytwr.wave2.T = tp_50yr[i]
# reset to initial conditions for geometry
mytwr.d_monopile = d_monopile[i]
mytwr.t_monopile = t_monopile[i]
mytwr.t_jacket = t_jacket[i]
mytwr.d_tower_base = d_tower_base[i]
mytwr.d_tower_top = d_tower_top[i]
mytwr.t_tower_base = t_tower_base[i]
mytwr.t_tower_top = t_tower_top[i]
# print IC
print "Initial condition\n"
print "sea_depth=", mytwr.sea_depth
print "deck_height=", mytwr.deck_height
print "significant wave height=", mytwr.wave1.hs
print "wave period=", mytwr.wave1.T
print "d_monopile=", mytwr.d_monopile
print "t_monopile=", mytwr.t_monopile
print "t_jacket=", mytwr.t_jacket
print "d_tower_base=", mytwr.d_tower_base
print "d_tower_top=", mytwr.d_tower_top
print "t_tower_base=", mytwr.t_tower_base
print "t_tower_top=", mytwr.t_tower_top
mytwr.driver.options.update(
{"Summary file": "Case_" + str(i) + "_summary.out", "Print file": "Case_" + str(i) + "_print.out"}
)
if sea_depth[i] > 60.0: # deepwater case
mytwr.driver.options["Major optimality tolerance"] = 1e-3
else:
mytwr.driver.options["Major optimality tolerance"] = 1e-3
# RUN
import time
tt = time.time()
mytwr.run()
print "Final conditions"
print "Minimum found at Db=%f, Dt=%f, tb=%f, tt=%f; mass= (%f)" % (
mytwr.tower1.d[0],
mytwr.tower1.d[-1],
mytwr.tower1.t[0],
mytwr.tower1.t[-1],
mytwr.tower1.mass,
)
print "Minimum found at z1=%f, D1=%f, t1=%f" % (mytwr.tower1.z[1], mytwr.tower1.d[1], mytwr.tower1.t[1])
print "Minimum found at DTRb DTRt(%f, %f)" % (
mytwr.tower1.d[0] / mytwr.tower1.t[0],
mytwr.tower1.d[-1] / mytwr.tower1.t[-1],
)
print "\n"
# print FC
print "d_monopile=", mytwr.d_monopile
print "t_monopile=", mytwr.t_monopile
print "t_jacket=", mytwr.t_jacket
print "d_tower_base=", mytwr.d_tower_base
print "d_tower_top=", mytwr.d_tower_top
print "t_tower_base=", mytwr.t_tower_base
print "t_tower_top=", mytwr.t_tower_top
print "zs=", mytwr.tower1.z
print "ds=", mytwr.tower1.d
print "ts=", mytwr.tower1.t
print "\n"
print "Minimum found at Freq %f" % (mytwr.tower1.f1)
print "Minimum found at GLutil EUutil %f %f" % (
np.max(np.vstack((mytwr.tower1.buckling, mytwr.tower2.buckling))),
np.max(np.vstack((mytwr.tower1.shellBuckling, mytwr.tower2.shellBuckling))),
)
print "Minimum found at GLutil 1 and 2", mytwr.tower1.buckling, mytwr.tower2.buckling
print "Minimum found at EUutil 1 and 2", mytwr.tower1.shellBuckling, mytwr.tower2.shellBuckling
print "Elapsed time: ", time.time() - tt, "seconds\n"
# Plot
PlotTower(mytwr, util=True, savefileroot=str(i))
else:
# RUN
import time
tt = time.time()
mytwr.run()
print "\n"
print "Minimum found at Db=%f, Dt=%f, tb=%f, tt=%f; mass= (%f)" % (
mytwr.tower1.d[0],
mytwr.tower1.d[-1],
mytwr.tower1.t[0],
mytwr.tower1.t[-1],
mytwr.tower1.mass,
)
print "Minimum found at z1=%f, D1=%f, t1=%f" % (mytwr.tower1.z[1], mytwr.tower1.d[1], mytwr.tower1.t[1])
print "Minimum found at DTRb DTRt(%f, %f)" % (
mytwr.tower1.d[0] / mytwr.tower1.t[0],
mytwr.tower1.d[-1] / mytwr.tower1.t[-1],
)
print "\n"
print "zs=", mytwr.tower1.z
print "ds=", mytwr.tower1.d
print "ts=", mytwr.tower1.t
print "\n"
print "Minimum found at Freq %f" % (mytwr.tower1.f1)
print "Minimum found at GLutil EUutil %f %f" % (
np.max(np.vstack((mytwr.tower1.buckling, mytwr.tower2.buckling))),
np.max(np.vstack((mytwr.tower1.shellBuckling, mytwr.tower2.shellBuckling))),
)
print "Minimum found at GLutil 1 and 2", mytwr.tower1.buckling, mytwr.tower2.buckling
print "Minimum found at EUutil 1 and 2", mytwr.tower1.shellBuckling, mytwr.tower2.shellBuckling
print "Elapsed time: ", time.time() - tt, "seconds"
print "Execution count: ", mytwr.exec_count
# Plot
PlotTower(mytwr, util=True)
print mytwr.jp.z
print mytwr.jp.towerHeight
print (mytwr.jp.z * mytwr.jp.towerHeight) - (mytwr.d_monopile * 1.5 - mytwr.monopile_extension)
print mytwr.z_nodes
def configure(self):
# add an optimizer and a multi-point AeroStructural assembly
if pyopt_driver and 'SNOPT' in pyopt_driver._check_imports():
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {
# any changes to default SNOPT options?
}
else:
print 'SNOPT not available, using SLSQP'
self.add('driver', SLSQPdriver())
# Nothing has anlytical derivaties, but we have a lot of
# nested assemblies, so it is less problematic to just
# finite difference it all in one block.
#self.driver.gradient_options.force_fd = True
#self.driver.gradient_options.fd_step_type = 'relative'
#self.driver.gradient_options.fd_step = 1.0e-7
#self.driver.pyopt_diff = True
self.add('mp', Multipoint())
self.mp.alt_low = 0.5 # low altitude
self.mp.alt_high = 3.5 # high altitude
self.mp.alt_ratio = 35./60. # proportion of time near ground
self.mp.TWire_high = 900
self.mp.TWire_wind = 2100
self.mp.TWire_grav = 110
self.mp.OmegaRatio = 2
self.mp.vw = 0/3.6 # zero
self.mp.Cl_max = [1.4, 1.35, 1.55] # max control
# objective: minimize total power
self.driver.add_objective('mp.P')
# parameter: rotor speed
self.driver.add_parameter('mp.Omega_low',
low=0.15*2*pi, high=0.25*2*pi)
self.mp.Omega_low = 0.20*2*pi # initial value
self.driver.add_parameter('mp.Omega_high',
low=0.15*2*pi, high=0.19*2*pi)
self.mp.Omega_high = 0.17*2*pi # initial value
# parameter: lift distribution at high altitude
self.driver.add_parameter('mp.Cl0_high',
low=0.8, high=1.4)
self.mp.Cl0_high = 1.
self.driver.add_parameter('mp.Cl1_high',
low=0.8, high=1.3)
self.mp.Cl1_high = 1.
# constraint: lift >= weight
self.driver.add_constraint('mp.Mtot_low*9.8-mp.Ttot_low<=0')
self.driver.add_constraint('mp.Mtot_high*9.8-mp.Ttot_high<=0')
# TODO: optional constraints
# if flags.ConFail:
# Structural Failure in Rotor Spar (ConFail)
# Buckling failure of spar (ConFailBuck)
# Tensile failure in wire (ConFailWire)
#
# if flags.ConDef:
# Constraints on Maximum Deformation (ConDelta)
#
# if flags.MultiPoint && flags.ConJigCont:
# Consistent jig twist (ConAlphaJig)
#
# if flags.MultiPoint && flags.ConWireCont
# Wire stretch consistency (conWire)
# Optimization Constraints (not used... yet)
vrCon = VariableTree()
vrCon.MaxDelta = -0.1
vrCon.MinDelta = 0.1
vrCon.FOSmat = 0.55 # 1.3
vrCon.FOSbuck = 0.5 # 1.3
vrCon.FOSquadbuck = 5.
vrCon.FOStorbuck = 0.5 # 1.5
vrCon.FOSwire = 0.5 # 2
self.driver.workflow.add('mp')
def opt_tower(sea_depth=np.array([]), hmax_50yr=None, tp_50yr=None, deck_height=None, d_monopile=None, t_monopile=None, t_jacket=None, \
d_tower_base=None, d_tower_top=None, t_tower_base=None, t_tower_top=None):
mytwr = main()[0]
MDAOswitch = 'md_pysnopt'
# optimization
import pyOpt
from pyopt_driver.pyopt_driver import pyOptDriver
from openmdao.lib.casehandlers.api import DumpCaseRecorder
from openmdao.lib.drivers.api import COBYLAdriver
if MDAOswitch == 'md_cobyla':
mytwr.replace('driver', COBYLAdriver())
mytwr.driver.rhobeg = 0.01
mytwr.driver.rhoend = 1.e-3
mytwr.driver.maxfun = 2000
mytwr.driver.iprint = 1
else:
mytwr.replace('driver', pyOptDriver())
if MDAOswitch == 'md_pysnopt':
mytwr.driver.optimizer = 'SNOPT'
mytwr.driver.pyopt_diff = True
#mytwr.driver.sens_step = 1e-8
mytwr.driver.options = {
'Major feasibility tolerance': 1e-4,
'Minor feasibility tolerance': 1e-4,
'Major optimality tolerance': 1e-4,
'Function precision': 1e-6
}
elif MDAOswitch == 'md_pyCobyla':
mytwr.driver.optimizer = 'COBYLA'
mytwr.driver.options = {
'RHOEND': 1.e-2,
'RHOEND': 1.e-3,
'MAXFUN': 2000,
'IPRINT': 1
}
else:
sys.exit('Error: MDAOswitch must be set to '
'pyCobyla'
' or '
'pySNOPT'
' or '
'md_cobyla'
' or '
'md_pySNOPT'
' or '
'md_pyCobyla'
'!!!')
# ----------------------
# --- Objective ---
mytwr.driver.add_objective('(tower1.mass) / 500.e3')
# ----------------------
#diameter and thickness variables
mytwr.driver.add_parameter('d_monopile', low=3.0,
high=15.0) # this is OD monopile
mytwr.driver.add_parameter('t_monopile', low=0.01,
high=0.1) # this is t of monopile
mytwr.driver.add_parameter(
't_jacket', low=0.01, high=0.1
) # this is t of jacket # d jacket fixed by monopile + t_jacket + t_grout
mytwr.driver.add_parameter('d_tower_base', low=3.0,
high=15.0) #This is OD at the base
mytwr.driver.add_parameter('t_tower_base', low=0.01,
high=0.3) #This is t at the base
mytwr.driver.add_parameter(
'd_tower_top', low=3.87,
high=8.0) #This is OD at the top # OD at top should be fixed
mytwr.driver.add_parameter('t_tower_top', low=0.01,
high=0.1) #This is t at top
# node positioning variables
#mytwr.driver.add_parameter('jp.z[5]', low= 0.0, high= 0.99) # this is H2 (can't move this - will have to add extra variable to make that happen)
#--- Constraints ---#
# frequency
mytwr.driver.add_constraint('tower1.f1 >= 0.20') # from 0.28 to 0.26
#mytwr.driver.add_constraint('tower1.f1 <= 0.30')
# utilization
mytwr.driver.add_constraint('tower1.stress <= 1.0')
mytwr.driver.add_constraint('tower2.stress <= 1.0')
mytwr.driver.add_constraint('tower1.buckling <= 1.0')
mytwr.driver.add_constraint('tower2.buckling <= 1.0')
mytwr.driver.add_constraint('tower1.shellBuckling <= 1.0')
mytwr.driver.add_constraint('tower2.shellBuckling <= 1.0')
mytwr.driver.add_constraint('tower1.damage <= 1.0')
#mytwr.driver.add_constraint('gc.weldability <= 0.0') # this goes for entire structure which we don't want
#mytwr.driver.add_constraint('gc.manufacturability <= 0.0') # just going to use explicit constraints below
# uniformity of diameter and thickness of tower
mytwr.driver.add_constraint('d_tower_top <= d_tower_base')
mytwr.driver.add_constraint('d_tower_base <= d_monopile')
#mytwr.driver.add_constraint('d_monopile - d_tower_base <= 0.4')
mytwr.driver.add_constraint('t_tower_top <= t_tower_base')
# manufacturing and installation
mytwr.driver.add_constraint(
'd_tower_top/d_tower_base >= 0.40'
) # manufacturability - already covered; taper ratio for manufacturing
mytwr.driver.add_constraint(
'd_tower_base/t_tower_base >= 120.0'
) # weldibility - already covered; tower DTR for rolling operation
mytwr.driver.add_constraint('d_tower_top/t_tower_top >= 120.0')
#mytwr.driver.add_constraint('d_monopile/t_monopile <= 100.0') # pile DTR for installation
#mytwr.driver.add_constraint('d_tower_base/t_tower_base <= 200.0') # tower DTR for welding (not covered)
#mytwr.driver.add_constraint('d_tower_top/t_tower_top <= 200.0')
## mytwr.driver.add_constraint('Lp0rat >= 0.') # was for embedment - not in model
# ----------------------
# set optimization variables
if sea_depth.size:
for i in range(len(sea_depth)):
mytwr.sea_depth = sea_depth[i]
mytwr.deck_height = deck_height[i]
mytwr.wave1.hs = hmax_50yr[i]
mytwr.wave1.T = tp_50yr[i]
mytwr.wave2.hs = hmax_50yr[i]
mytwr.wave2.T = tp_50yr[i]
#reset to initial conditions for geometry
mytwr.d_monopile = d_monopile[i]
mytwr.t_monopile = t_monopile[i]
mytwr.t_jacket = t_jacket[i]
mytwr.d_tower_base = d_tower_base[i]
mytwr.d_tower_top = d_tower_top[i]
mytwr.t_tower_base = t_tower_base[i]
mytwr.t_tower_top = t_tower_top[i]
# print IC
print 'Initial condition\n'
print 'sea_depth=', mytwr.sea_depth
print 'deck_height=', mytwr.deck_height
print 'significant wave height=', mytwr.wave1.hs
print 'wave period=', mytwr.wave1.T
print 'd_monopile=', mytwr.d_monopile
print 't_monopile=', mytwr.t_monopile
print 't_jacket=', mytwr.t_jacket
print 'd_tower_base=', mytwr.d_tower_base
print 'd_tower_top=', mytwr.d_tower_top
print 't_tower_base=', mytwr.t_tower_base
print 't_tower_top=', mytwr.t_tower_top
mytwr.driver.options.update({
'Summary file':
'Case_' + str(i) + '_summary.out',
'Print file':
'Case_' + str(i) + '_print.out'
})
if sea_depth[i] > 60.0: # deepwater case
mytwr.driver.options['Major optimality tolerance'] = 1e-3
else:
mytwr.driver.options['Major optimality tolerance'] = 1e-3
#RUN
import time
tt = time.time()
mytwr.run()
print "Final conditions"
print "Minimum found at Db=%f, Dt=%f, tb=%f, tt=%f; mass= (%f)" % (
mytwr.tower1.d[0], mytwr.tower1.d[-1], mytwr.tower1.t[0],
mytwr.tower1.t[-1], mytwr.tower1.mass)
print "Minimum found at z1=%f, D1=%f, t1=%f" % (
mytwr.tower1.z[1], mytwr.tower1.d[1], mytwr.tower1.t[1])
print "Minimum found at DTRb DTRt(%f, %f)" % (
mytwr.tower1.d[0] / mytwr.tower1.t[0],
mytwr.tower1.d[-1] / mytwr.tower1.t[-1])
print "\n"
# print FC
print 'd_monopile=', mytwr.d_monopile
print 't_monopile=', mytwr.t_monopile
print 't_jacket=', mytwr.t_jacket
print 'd_tower_base=', mytwr.d_tower_base
print 'd_tower_top=', mytwr.d_tower_top
print 't_tower_base=', mytwr.t_tower_base
print 't_tower_top=', mytwr.t_tower_top
print 'zs=', mytwr.tower1.z
print 'ds=', mytwr.tower1.d
print 'ts=', mytwr.tower1.t
print "\n"
print "Minimum found at Freq %f" % (mytwr.tower1.f1)
print "Minimum found at GLutil EUutil %f %f" % (
np.max(
np.vstack((mytwr.tower1.buckling, mytwr.tower2.buckling))),
np.max(
np.vstack((mytwr.tower1.shellBuckling,
mytwr.tower2.shellBuckling))))
print "Minimum found at GLutil 1 and 2", mytwr.tower1.buckling, mytwr.tower2.buckling
print "Minimum found at EUutil 1 and 2", mytwr.tower1.shellBuckling, mytwr.tower2.shellBuckling
print "Elapsed time: ", time.time() - tt, "seconds\n"
#Plot
PlotTower(mytwr, util=True, savefileroot=str(i))
else:
#RUN
import time
tt = time.time()
mytwr.run()
print "\n"
print "Minimum found at Db=%f, Dt=%f, tb=%f, tt=%f; mass= (%f)" % (
mytwr.tower1.d[0], mytwr.tower1.d[-1], mytwr.tower1.t[0],
mytwr.tower1.t[-1], mytwr.tower1.mass)
print "Minimum found at z1=%f, D1=%f, t1=%f" % (
mytwr.tower1.z[1], mytwr.tower1.d[1], mytwr.tower1.t[1])
print "Minimum found at DTRb DTRt(%f, %f)" % (
mytwr.tower1.d[0] / mytwr.tower1.t[0],
mytwr.tower1.d[-1] / mytwr.tower1.t[-1])
print "\n"
print 'zs=', mytwr.tower1.z
print 'ds=', mytwr.tower1.d
print 'ts=', mytwr.tower1.t
print "\n"
print "Minimum found at Freq %f" % (mytwr.tower1.f1)
print "Minimum found at GLutil EUutil %f %f" % (
np.max(np.vstack((mytwr.tower1.buckling, mytwr.tower2.buckling))),
np.max(
np.vstack(
(mytwr.tower1.shellBuckling, mytwr.tower2.shellBuckling))))
print "Minimum found at GLutil 1 and 2", mytwr.tower1.buckling, mytwr.tower2.buckling
print "Minimum found at EUutil 1 and 2", mytwr.tower1.shellBuckling, mytwr.tower2.shellBuckling
print "Elapsed time: ", time.time() - tt, "seconds"
print "Execution count: ", mytwr.exec_count
#Plot
PlotTower(mytwr, util=True)
print mytwr.jp.z
print mytwr.jp.towerHeight
print(mytwr.jp.z * mytwr.jp.towerHeight) - (mytwr.d_monopile * 1.5 -
mytwr.monopile_extension)
print mytwr.z_nodes
plt.legend(bbox_to_anchor=(1.05, 1.0), loc=2)
plt.xlabel('utilization')
plt.ylabel('height along tower (m)')
plt.show()
# ------------
if optimize:
# --- optimizer imports ---
from pyopt_driver.pyopt_driver import pyOptDriver
from openmdao.lib.casehandlers.api import DumpCaseRecorder
# ----------------------
# --- Setup Pptimizer ---
tower.replace('driver', pyOptDriver())
tower.driver.optimizer = 'SNOPT'
tower.driver.options = {'Major feasibility tolerance': 1e-6,
'Minor feasibility tolerance': 1e-6,
'Major optimality tolerance': 1e-5,
'Function precision': 1e-8}
# ----------------------
# --- Objective ---
tower.driver.add_objective('tower1.mass / 300000')
# ----------------------
# --- Design Variables ---
tower.driver.add_parameter('z_param[1]', low=0.0, high=87.0)
tower.driver.add_parameter('d_param[:-1]', low=3.87, high=20.0)
tower.driver.add_parameter('t_param', low=0.005, high=0.2)
def configure(self):
#Components
self.add("DeformationCavity_meta",FoamMetaModel())
self.DeformationCavity_meta.includes=['x1','x2','f1','f2']
self.DeformationCavity_meta.model = DeformationCavity()
self.DeformationCavity_meta.default_surrogate = ResponseSurface()
self.DeformationCavity_meta.surrogates["f1.latestTimeValue"] = FloatKrigingSurrogate()
self.DeformationCavity_meta.surrogates["f2.latestTimeValue"] = FloatKrigingSurrogate()
self.DeformationCavity_meta.surrogates["f1.latestTimeValue"].nugget = 0.0
self.DeformationCavity_meta.surrogates["f2.latestTimeValue"].nugget = 0.0
self.DeformationCavity_meta.recorder = DBCaseRecorder()
#Training the MetaModel
self.add("DOE_Trainer",DOEdriver())
self.DOE_Trainer.DOEgenerator = FullFactorial()
self.DOE_Trainer.DOEgenerator.num_levels = 4
self.DOE_Trainer.add_parameter('DeformationCavity_meta.x1', low= -0.1, high=0.1)
self.DOE_Trainer.add_parameter('DeformationCavity_meta.x2', low= 0.9, high=1.1)
self.DOE_Trainer.case_outputs = ["DeformationCavity_meta.f1.latestTimeValue",
"DeformationCavity_meta.f2.latestTimeValue"]
self.DOE_Trainer.record_doe = False
self.DOE_Trainer.add_event("DeformationCavity_meta.train_next")
self.DOE_Trainer.recorders = [DBCaseRecorder()]
#MetaModel Validation
self.add("DeformationCavity", DeformationCavity())
self.add("DOE_Validate", DOEdriver())
self.DOE_Validate.DOEgenerator = FullFactorial()
self.DOE_Validate.DOEgenerator.num_levels = 3
self.DOE_Validate.add_parameter(("DeformationCavity_meta.x1", "DeformationCavity.x1"), low=-0.1, high=0.1)
self.DOE_Validate.add_parameter(("DeformationCavity_meta.x2", "DeformationCavity.x2"), low= 0.9, high=1.1)
self.DOE_Validate.case_outputs = ["DeformationCavity.f1.latestTimeValue",
"DeformationCavity.f2.latestTimeValue",
"DeformationCavity_meta.f1.latestTimeValue",
"DeformationCavity_meta.f2.latestTimeValue"]
self.DOE_Validate.record_doe = False
self.DOE_Validate.recorders = [DBCaseRecorder()]
# Create NSGA2 Optimizer instance
self.add('NSGA2', pyOptDriver())
self.NSGA2.print_results = True
# NSGA2 Objective
self.NSGA2.add_objective('DeformationCavity_meta.f1.latestTimeValue')
self.NSGA2.add_objective('DeformationCavity_meta.f2.latestTimeValue')
# NSGA2 Design Variable
self.NSGA2.add_parameter('DeformationCavity_meta.x1', low=-0.1, high=0.1)
self.NSGA2.add_parameter('DeformationCavity_meta.x2', low= 0.9, high=1.1)
# NSGA2 Constraints
# self.NSGA2.add_constraint('DeformationCavity_meta.x2 - DeformationCavity_meta.x1 >= 1.0')
self.NSGA2.optimizer = 'NSGA2'
optdict = {}
optdict['PopSize'] = 100 # a multiple of 4
optdict['maxGen'] = 5
optdict['pCross_real'] = 0.6 #prob of crossover of design variables in range (0.6-1.0)
optdict['pMut_real'] = 0.5 #prob of mutation of (1/design varaibles)
optdict['eta_c'] = 10.0 #distribution index for crossover in range (5 - 20)
optdict['eta_m'] = 50.0 #distribution index for mutation in range (5 - 50)
optdict['pCross_bin'] = 1.0 #prob of crossover of binary variable in range(0.6 - 1.0)
optdict['pMut_real'] = 1.0 #prob of mutation of binary variables in (1/nbits)
optdict['PrintOut'] = 1 #flag to turn on output to files (0-None, 1-Subset,2-All)
optdict['seed'] = 0.0 #random seed number (0-autoseed based on time clock)
self.NSGA2.options = optdict
#Iteration Hierarchy
self.driver.workflow = SequentialWorkflow()
self.driver.workflow.add(['DOE_Trainer','DOE_Validate','NSGA2'])
self.DOE_Trainer.workflow.add('DeformationCavity_meta')
self.DOE_Validate.workflow.add('DeformationCavity_meta')
self.DOE_Validate.workflow.add('DeformationCavity')
# Driver process definition
self.NSGA2.workflow.add('DeformationCavity_meta')
def configure(self):
# add an optimizer and a multi-point AeroStructural assembly
if pyopt_driver and 'SNOPT' in pyopt_driver._check_imports():
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {
# any changes to default SNOPT options?
}
else:
print 'SNOPT not available, using SLSQP'
self.add('driver', SLSQPdriver())
self.add('mp', Multipoint())
self.mp.alt_low = 0.5 # low altitude
self.mp.alt_high = 3.5 # high altitude
self.mp.alt_ratio = 35. / 60. # proportion of time near ground
self.mp.TWire_high = 900
self.mp.TWire_wind = 2100
self.mp.TWire_grav = 110
self.mp.OmegaRatio = 2
self.mp.vw = 0 / 3.6 # zero
self.mp.Cl_max = [1.4, 1.35, 1.55] # max control
# objective: minimize total power
self.driver.add_objective('mp.P')
# parameter: rotor speed
self.driver.add_parameter('mp.Omega_low',
low=0.15 * 2 * pi,
high=0.25 * 2 * pi)
self.mp.Omega_low = 0.20 * 2 * pi # initial value
self.driver.add_parameter('mp.Omega_high',
low=0.15 * 2 * pi,
high=0.19 * 2 * pi)
self.mp.Omega_high = 0.17 * 2 * pi # initial value
# parameter: lift distribution at high altitude
self.driver.add_parameter('mp.Cl0_high', low=0.8, high=1.4)
self.mp.Cl0_high = 1.
self.driver.add_parameter('mp.Cl1_high', low=0.8, high=1.3)
self.mp.Cl1_high = 1.
# constraint: lift >= weight
self.driver.add_constraint('mp.Mtot_low*9.8-mp.Ttot_low<=0')
self.driver.add_constraint('mp.Mtot_high*9.8-mp.Ttot_high<=0')
# TODO: optional constraints
# if flags.ConFail:
# Structural Failure in Rotor Spar (ConFail)
# Buckling failure of spar (ConFailBuck)
# Tensile failure in wire (ConFailWire)
#
# if flags.ConDef:
# Constraints on Maximum Deformation (ConDelta)
#
# if flags.MultiPoint && flags.ConJigCont:
# Consistent jig twist (ConAlphaJig)
#
# if flags.MultiPoint && flags.ConWireCont
# Wire stretch consistency (conWire)
# Optimization Constraints (not used... yet)
vrCon = VariableTree()
vrCon.MaxDelta = -0.1
vrCon.MinDelta = 0.1
vrCon.FOSmat = 0.55 # 1.3
vrCon.FOSbuck = 0.5 # 1.3
vrCon.FOSquadbuck = 5.
vrCon.FOStorbuck = 0.5 # 1.5
vrCon.FOSwire = 0.5 # 2
def __init__(self, n=1500, m=300, npts=6):
super(CADRE_Optimization, self).__init__()
# add SNOPT driver
self.add("driver", pyopt_driver.pyOptDriver())
self.driver.optimizer = "SNOPT"
self.driver.options = {'Major optimality tolerance': 1e-4,
'Iterations limit': 500000000,
"New basis file": 10}
if os.path.exists("fort.10"):
self.driver.options["Old basis file"] = 10
#self.add("driver", CONMINdriver())
# Raw data to load
fpath = os.path.dirname(os.path.realpath(__file__))
solar_raw1 = np.genfromtxt(fpath + '/data/Solar/Area10.txt')
solar_raw2 = np.loadtxt(fpath + "/data/Solar/Area_all.txt")
comm_rawGdata = np.genfromtxt(fpath + '/data/Comm/Gain.txt')
comm_raw = (10 ** (comm_rawGdata / 10.0)).reshape(
(361, 361), order='F')
power_raw = np.genfromtxt(fpath + '/data/Power/curve.dat')
# Load launch data
launch_data = np.loadtxt(fpath + "/data/Launch/launch1.dat")
# orbit position and velocity data for each design point
r_e2b_I0s = launch_data[1::2, 1:]
# number of days since launch for each design point
LDs = launch_data[1::2, 0] - 2451545
# LDs = [5233.5, 5294.5, 5356.5, 5417.5, 5478.5, 5537.5]
# r_e2b_I0s = [np.array([4505.29362, -3402.16069, -3943.74582,
# 4.1923899, -1.56280012, 6.14347427]),
# np.array(
# [-1005.46693, -597.205348, -6772.86532, -0.61047858,
# -7.54623146, 0.75907455]),
# np.array(
# [4401.10539, 2275.95053, -4784.13188, -5.26605537,
# -1.08194926, -5.37013745]),
# np.array(
# [-4969.91222, 4624.84149, 1135.9414, 0.1874654,
# -1.62801666, 7.4302362]),
# np.array(
# [-235.021232, 2195.72976, 6499.79919, -2.55956031,
# -6.82743519, 2.21628099]),
# np.array(
# [-690.314375, -1081.78239, -6762.90367, 7.44316722,
# 1.19745345, -0.96035904])]
# build design points
for i in xrange(npts):
i_ = str(i)
aname = ''.join(["pt", str(i)])
self.add(aname, CADRE(n, m, solar_raw1, solar_raw2,
comm_raw, power_raw))
self.get(aname).set("LD", LDs[i])
self.get(aname).set("r_e2b_I0", r_e2b_I0s[i])
# add parameters to driver
self.driver.add_parameter("pt%s.CP_Isetpt" % i_, low=0., high=0.4)
self.driver.add_parameter("pt%s.CP_gamma" % i_, low=0,
high=np.pi / 2.)
self.driver.add_parameter("pt%s.CP_P_comm" % i_, low=0., high=25.)
param = ''.join(["pt", str(i), ".iSOC[0]"])
self.driver.add_parameter(param, low=0.2, high=1.)
# add constraints
constr = ''.join(["pt", str(i), ".ConCh <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".ConDs <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".ConS0 <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".ConS1 <= 0"])
self.driver.add_constraint(constr)
constr = ''.join(["pt", str(i), ".SOC[0][0] = pt",
str(i), ".SOC[0][-1]"])
self.driver.add_constraint(constr)
cell_param = ["pt%s.cellInstd" % str(i) for i in xrange(npts)]
self.driver.add_parameter(cell_param, low=0, high=1)
finangles = ["pt" + str(i) + ".finAngle" for i in xrange(npts)]
antangles = ["pt" + str(i) + ".antAngle" for i in xrange(npts)]
self.driver.add_parameter(finangles, low=0, high=np.pi / 2.)
self.driver.add_parameter(antangles, low=-np.pi / 4, high=np.pi / 4)
# add objective
obj = ''.join([''.join(["-pt", str(i), ".Data[0][-1]"])
for i in xrange(npts)])
self.driver.add_objective(obj)
