def _load_thrust_table(self, path):
self._get_thrust_table_limits()
data = read_tabulated_data_with_header(path)
self._normMach = Normalization(data["Mach"].min(), data["Mach"].max(), 0, 1)
self._normAlt = Normalization(data["altitude"].min(), data["altitude"].max(), 0, 1)
self._normTreq = Normalization(data["ThrustRequired"].min(), data["ThrustRequired"].max(), 0, 1)
normMach = self._normMach.normalize(data["Mach"])
normAlt = self._normAlt.normalize(data["altitude"])
normTreq = self._normTreq.normalize(data["ThrustRequired"])
self.sfcModel = Rbf(normMach, normAlt, normTreq, data["sfc"])
def _get_thrust_table_limits(self):
n = 10
MachMin = 0.05
MachMax = 1.0
altMin = 0
altMax = 2e4
Tmc = self.totalThrust
Tmin = 0.05 * Tmc
Tmax = Tmc
self._normMach = Normalization(MachMin, MachMax, 0, 1)
self._normAlt = Normalization(altMin, altMax, 0, 1)
self._normTreq = Normalization(Tmin, Tmax, 0, 1)
return n, MachMin, MachMax, altMin, altMax, Tmin, Tmax
class CostFunction(object):
def __init__(self,costFcn,lb,ub):
""" cost function should return f,g"""
self.costFcn = costFcn
self.nEval = 0
self.penalty = 1.0e5
self.norm = Normalization(lb,ub,0,1)
def evaluate(self,x,penalty=None):
x = self.norm.denormalize(x)
if penalty==None:
penalty = self.penalty
f,g = self.costFcn(x)
self.nEval += 1
cost = f
for cnstr in g:
cost += max([0.0,cnstr]) * penalty
return cost,f,g
def __call__(self,x,penalty=None):
x = np.asarray(x)
if x.ndim==1:
return self.evaluate(x,penalty)
elif x.ndim==2:
n = x.shape[0]
cost = np.zeros(n)
f = np.zeros(n)
cost[0],f[0],gtmp = self.evaluate(x[0],penalty)
g = np.zeros([n,len(gtmp)])
g[0] = gtmp
for i in range(1,n):
cost[i],f[i],g[i] = self.evaluate(x[i],penalty)
return cost,f,g
def __init__(self,x0,lb,ub):
self.x0 = x0
self.af = None
self.clCruise = [0.2,0.3]
self.clmaxMin = 1.4
self.tcMin = 0.135
self.tcMax = 0.145
self.norm = Normalization(lb,ub)
self.cruise = FlightConditions(55,1500)
self.landing = FlightConditions(1.2*20.6, 0)
self.cdminAlpha = [0,3.0]
self.afBaseline = cst_x(x0)
def setup(self):
self.neval = 0
self.lb = np.array([40, 40, 6.00, 3.00, 0.5, 1.00, 3.000, -4, -4])
#self.lb = np.array([40, 40, 6.00, 3.00, 0.5, 1.00, 3.000, -4, -4])
self.ub = np.array([60, 60, 7.50, 5.25, 1.8, 1.80, 3.200, 0, 0])
#self.ub = np.array([60, 60, 7.50, 5.25, 1.8, 1.80, 3.200, 0, 0])
self.x0 = np.array([55, 55, 6.91, 4.15, 1.1, 1.44, 3.115, 0, -3])
self.norm = Normalization(self.lb, self.ub,-1.,1.)
self.xCurrent = np.zeros(len(self.x0))
self.x0norm = self.norm.normalize(self.x0)
#self.bnds = np.array([[l,u] for l,u in zip(self.lb,self.ub)])
# --- constraints ---
self.WemptyMax = 3500.0
self.CnbMin = 0.003
self.ClbMax = -0.075 #-6.0e-4
self.SMmin = 0.05
self.SMmax = 0.15
self.combatRadiusMin= 750.0
self.RCmin = 125.0
self.VmaxMin = 0.90 # Mach
self.minSectionLen = 1.4*self.propulsion.engine.length
self.CmdeReq = -0.01 # baseline -0.00866
self.alphaTrimMax = 8.0+1e-4 # deg
self.elevTrimMax = 20.0
self.elevTrimMin = -20.0
self.gvfmAero = True
self.Vtrim = 65.0 # 135kts: assumed value
self._load_rbf_models()
# --- payload ---
self.SDB = MassComponent('drop payload', 1132.0, np.array([4.5, 0.0, 0.12]))
# --- misc ---
self.analysisData = np.zeros(10)
# self._upd_approximation()
# --- initial data ---
self.Wf = self.mass.fuel.mass
self.CGf = self.mass.fuel.coords
self.engineOffset = 0.75*self.propulsion.engine.length
self.payloadOffset = 0.75*self.propulsion.engine.length
self.fileFeasible = 'ucav_feasible.txt'
self.set_x(self.x0norm)
class Propulsion(object):
def __init__(self):
self.numberOfEngines = 1
self.engine = TurbofanEngine()
self.CGx = None
self.CGy = None
self.CGz = None
self.numberOfTanks = 1
self.sfcModel = None
def load(self, name, buildTable=False):
self.engine.load(name)
self._process_data(buildTable)
def _process_data(self, buildTable=False):
self.totalThrust = self.engine.thrustMC * self.numberOfEngines
self._calc_cg()
if buildTable:
path = MyPaths()
thrustTablePath = "%s//ThrustTable_%s.txt" % (path.db.wdir, self.engine.name)
if os.path.isfile(thrustTablePath):
# print 'loading thrust table'
self._load_thrust_table(thrustTablePath)
else:
# print 'building thrust table'
self._build_thrust_table()
def _calc_cg(self):
if hasattr(self.CGx, "__iter__"):
mass = ones(self.numberOfEngines) * self.engine.mass
self.totalMass, self.CG = get_total_cg(mass, self.CGx, self.CGy, self.CGz)
def get_sfc_direct(self, Mach, altitude, thrustReq):
Mach = float(Mach)
altitude = float(altitude)
thrustReq = float(thrustReq) / self.numberOfEngines # thrust per engine
sfcPerEngine = self.engine.get_sfc(Mach, altitude, thrustReq)
return sfcPerEngine * self.numberOfEngines / 3600.0 # kg/(N*sec)
def get_sfc2(self, Mach, altitude, thrustReq):
Mach = self._normMach.normalize(Mach)
alt = self._normAlt.normalize(altitude)
Treq = self._normTreq.normalize(thrustReq)
return self.sfcModel(Mach, alt, Treq)
def get_sfc(self, Mach, altitude, thrustReq):
if self.sfcModel == None:
return self.get_sfc_direct(Mach, altitude, thrustReq)
else:
return self.get_sfc2(Mach, altitude, thrustReq)
def _load_thrust_table(self, path):
self._get_thrust_table_limits()
data = read_tabulated_data_with_header(path)
self._normMach = Normalization(data["Mach"].min(), data["Mach"].max(), 0, 1)
self._normAlt = Normalization(data["altitude"].min(), data["altitude"].max(), 0, 1)
self._normTreq = Normalization(data["ThrustRequired"].min(), data["ThrustRequired"].max(), 0, 1)
normMach = self._normMach.normalize(data["Mach"])
normAlt = self._normAlt.normalize(data["altitude"])
normTreq = self._normTreq.normalize(data["ThrustRequired"])
self.sfcModel = Rbf(normMach, normAlt, normTreq, data["sfc"])
def _get_thrust_table_limits(self):
n = 10
MachMin = 0.05
MachMax = 1.0
altMin = 0
altMax = 2e4
Tmc = self.totalThrust
Tmin = 0.05 * Tmc
Tmax = Tmc
self._normMach = Normalization(MachMin, MachMax, 0, 1)
self._normAlt = Normalization(altMin, altMax, 0, 1)
self._normTreq = Normalization(Tmin, Tmax, 0, 1)
return n, MachMin, MachMax, altMin, altMax, Tmin, Tmax
def _build_thrust_table(self):
n, MachMin, MachMax, altMin, altMax, Tmin, Tmax = self._get_thrust_table_limits()
MachList = linspace(MachMin, MachMax, n)
altList = linspace(altMin, altMax, n)
TreqList = linspace(Tmin, Tmax, n)
nsfc = n * n * n
sfc = ones(nsfc)
Mach = ones(nsfc)
altitude = ones(nsfc)
thrustReq = ones(nsfc)
i = 0
for M in MachList:
for alt in altList:
for Treq in TreqList:
_sfc = self.get_sfc_direct(M, alt, Treq)
if not isnan(_sfc):
sfc[i] = _sfc
Mach[i] = M # self._normMach.normalize(M)
altitude[i] = alt # self._normAlt.normalize(alt)
thrustReq[i] = Treq # self._normTreq.normalize(Treq)
i += 1
# print '%d\t%.4f\t%.0f\t%.0f\t%.6f'%(i, M, alt, Treq, _sfc)
path = MyPaths()
thrustTablePath = "%s//ThrustTable_%s.txt" % (path.db.wdir, self.engine.name)
fid = open(thrustTablePath, "wt")
fid.write("Mach\taltitude\tThrustRequired\tsfc\n")
for M, alt, Treq, _sfc in zip(Mach[:i], altitude[:i], thrustReq[:i], sfc[:i]):
fid.write("%.32f\t%.32e\t%.32e\t%.32e\n" % (M, alt, Treq, _sfc))
fid.close()
normMach = self._normMach.normalize(Mach[:i])
normAlt = self._normAlt.normalize(altitude[:i])
normTreq = self._normTreq.normalize(thrustReq[:i])
self.sfcModel = Rbf(normMach, normAlt, normTreq, sfc[:i])
def __call__(self, Mach, altitude, powerSetting):
""" NOTE: powerSetting is linear function - will be replaced """
thrustReq = self.engine.thrustMC * float(powerSetting) / 100.0
return self.get_sfc(Mach, altitude, thrustReq)
def get_thrust_available(self, altitude):
atm = ISAtmosphere(altitude)
rho0 = 1.2255
return atm.density / rho0 * self.totalThrust
def test(self):
plt.figure()
plt.hold(True)
legend = list()
alt = 1e4
Mach = linspace(0.1, 1, 200)
Tmc = self.totalThrust
Pset = linspace(0.05 * Tmc, Tmc, 5)
sfc = ones([len(Pset), len(Mach)])
sfc2 = ones([len(Pset), len(Mach)])
for i, p in enumerate(Pset):
for j, M in enumerate(Mach):
sfc[i, j] = self.get_sfc_direct(M, alt, p)
sfc2[i, j] = self.get_sfc2(M, alt, p)
plt.plot(Mach, sfc[i], marker="*")
plt.plot(Mach, sfc2[i])
legend.append("%.0f" % p)
legend.append("%.0frbf" % p)
plt.legend(legend)
plt.show()
class AirfoilObjective:
def __init__(self,x0,lb,ub):
self.x0 = x0
self.af = None
self.clCruise = [0.2,0.3]
self.clmaxMin = 1.4
self.tcMin = 0.135
self.tcMax = 0.145
self.norm = Normalization(lb,ub)
self.cruise = FlightConditions(55,1500)
self.landing = FlightConditions(1.2*20.6, 0)
self.cdminAlpha = [0,3.0]
self.afBaseline = cst_x(x0)
def set_cst(self,xnorm):
x = self.norm.denormalize(xnorm)
# for x1,x2 in zip(xnorm,x):
# print '%.4f\t%.4f'%(x1,x2)
# raw_input()
self.af = cst_x(x,35)
self.tc = self.af.thickness
def f(self,x):
sys.stdout.write('.')
self.set_cst(x)
pol = self.af.get_jfoil_polar(self.cruise.Mach, self.cruise.Re, [-10,10,0.5])
try:
cd = np.array([pol.get_cd_at_cl(cl) for cl in self.clCruise])
return cd.mean()
except ValueError:
#self.af.display()
#pol.display()
return pol.cd[0]
def fDeriv(self,x,dx=1e-2):
grad = np.zeros(len(x))
fval = self.f(x)
for i,xx in enumerate(x):
X = np.copy(x)
X[i] = X[i]+dx
grad[i] = (self.f(X)-fval)/dx
return grad
def g1Deriv(self,x,dx=2e-3):
grad = np.zeros(len(x))
fval = self.g1high(x)
for i,xx in enumerate(x):
X = np.copy(x)
X[i] = X[i]+dx
grad[i] = (self.g1high(X)-fval)/dx
return grad
def run_cfd(self,x,alpha=[12,14,16,18]):
self.set_cst(x)
self.af.coord = self.af.pts
solver = CFDsolver(self.af,self.landing,1.0,mesh='O')
solver.fluent.residuals['energy']=1e-5
solver.fluent.relaxationFactor['xvelocity'] = 1e-4
solver.fluent.residuals['continuity']=1e-4
solver.mesh._airfoilPts = 75
solver.mesh._interiorPts = 100
solver.mesh._dsTE = 2e-4
solver.mesh._dsLE = 1e-3
solver.mesh._growthRate = 1.15
solver.create_mesh()
result = solver.run_for_multiple_aoa(alpha,'ke-realizable')
result.Mach = self.landing.Mach
result.Re = self.landing.Re
result._calc_clmax()
sys.stdout.write('|')
return result
def g1high(self,x):
pol = self.run_cfd(x)
return pol.clmax - self.clmaxMin
def g1low(self,x):
sys.stdout.write('.')
self.set_cst(x)
pol = self.af.get_jfoil_polar(self.landing.Mach, self.landing.Re, [0,20,1])
return pol.clmax-self.clmaxMin
def g2(self,x):
self.set_cst(x)
return self.tc - self.tcMin
def g3(self,x):
self.set_cst(x)
return self.tcMax - self.tc
def g4(self,x):
self.set_cst(x)
pol = self.af.get_jfoil_polar(self.cruise.Mach, self.cruise.Re, [-10,10,0.5])
return pol.get_alpha_cdmin() - self.cdminAlpha[0]
def g5(self,x):
self.set_cst(x)
pol = self.af.get_jfoil_polar(self.cruise.Mach, self.cruise.Re, [-10,10,0.5])
return self.cdminAlpha[1] - pol.get_alpha_cdmin()
def run_optimization_1():
pathIn = "design_out4.txt"
pathInSamples = "DOE_LHS250_FFD2_3_3.txt"
learnData = read_tabulated_data_without_header(pathIn)
xNorm = read_tabulated_data_without_header(pathInSamples)
# xNorm = np.transpose(xNorm)
learnData = np.transpose(learnData)
WemptyMax = 3500.0
CnbMin = 0.0001
ClbMax = -0.05
SMmin = -0.05
SMmax = 0.10
combatRadiusMin = 1000.0
RCmin = 125.0
VmaxMin = 0.90 # Mach
LD = RbfMod(xNorm, learnData[0])
We = RbfMod(xNorm, learnData[1])
_Cnb = RbfMod(xNorm, (learnData[2]) * 1e3)
Clb = RbfMod(xNorm, learnData[3])
_SM = RbfMod(xNorm, learnData[4] * 1e3)
Rcombat = RbfMod(xNorm, learnData[5])
RC = RbfMod(xNorm, learnData[6])
Vmax = RbfMod(xNorm, learnData[7])
Cnb = lambda x: _Cnb(x) / 1e3
SM = lambda x: _SM(x) / 1e3
bnds = np.ones([9, 2])
bnds[:, 0] = -bnds[:, 0]
bnds[8, 0] = 0
bnds[7, 0] = 0
bnds = tuple(bnds)
f = lambda x: -LD(x)
g1 = lambda x: WemptyMax - We(x)
g2 = lambda x: (Cnb(x) - CnbMin) * 1e3
g3 = lambda x: ClbMax - Clb(x)
g4 = lambda x: SMmax - SM(x)
g5 = lambda x: SM(x) - SMmin
g6 = lambda x: Rcombat(x) / 1e3 - combatRadiusMin
g7 = lambda x: RC(x) - RCmin
g8 = lambda x: Vmax(x) - VmaxMin
cnstr = (
{"type": "ineq", "fun": g1},
{"type": "ineq", "fun": g2},
{"type": "ineq", "fun": g3},
{"type": "ineq", "fun": g4},
{"type": "ineq", "fun": g5},
{"type": "ineq", "fun": g6},
{"type": "ineq", "fun": g7},
{"type": "ineq", "fun": g8},
)
x0 = np.zeros(9)
rslt = minimize(f, x0, method="SLSQP", constraints=cnstr, bounds=bnds)
print rslt
rslt2 = minimize(f, x0, constraints=cnstr, bounds=bnds, options={"maxiter": 10000})
print rslt2
xopt = rslt.x
print g1(xopt), We(xopt)
print g2(xopt), Cnb(xopt)
print g3(xopt), Clb(xopt)
print g4(xopt), SM(xopt)
print g5(xopt), SM(xopt)
print g6(xopt), Rcombat(xopt)
print g7(xopt), RC(xopt)
print g8(xopt), Vmax(xopt)
ac = DesignFormulation()
ac.load_xls("Baseline1")
ac.setup()
ac.set_x(ac.x0)
x2dBaseline = ac.wing.x2d
y2dBaseline = ac.wing.y2d
print "Baseline"
print ac.analysisData
print "--->"
normalize = Normalization(ac.lb, ac.ub)
xoptDenorm = normalize.denormalize(xopt)
print xoptDenorm
ac.set_x(xoptDenorm)
x2dOptimum = ac.wing.x2d
y2dOptimum = ac.wing.y2d
print ac.analysisData, "\n---"
print (ac.analysisData[0] - LD(xopt)) / ac.analysisData[0]
print (ac.analysisData[1] - We(xopt)) / ac.analysisData[1]
print (ac.analysisData[2] - Cnb(xopt)) / ac.analysisData[2]
print (ac.analysisData[3] - Clb(xopt)) / ac.analysisData[3]
print (ac.analysisData[4] - SM(xopt)) / ac.analysisData[4]
print (ac.analysisData[5] - Rcombat(xopt)) / ac.analysisData[5]
print (ac.analysisData[6] - RC(xopt)) / ac.analysisData[6]
print (ac.analysisData[7] - Vmax(xopt)) / ac.analysisData[7]
plt.figure()
plt.hold(True)
plt.plot(x2dBaseline, y2dBaseline, "r-")
plt.plot(x2dOptimum, y2dOptimum, "k-")
plt.legend(["Baseline", "Low-fi Optimum"])
plt.show()
ac.display()
class DesignFormulation(design.Design):
def setup(self):
self.neval = 0
self.lb = np.array([40, 40, 6.00, 3.00, 0.5, 1.00, 3.000, -4, -4])
#self.lb = np.array([40, 40, 6.00, 3.00, 0.5, 1.00, 3.000, -4, -4])
self.ub = np.array([60, 60, 7.50, 5.25, 1.8, 1.80, 3.200, 0, 0])
#self.ub = np.array([60, 60, 7.50, 5.25, 1.8, 1.80, 3.200, 0, 0])
self.x0 = np.array([55, 55, 6.91, 4.15, 1.1, 1.44, 3.115, 0, -3])
self.norm = Normalization(self.lb, self.ub,-1.,1.)
self.xCurrent = np.zeros(len(self.x0))
self.x0norm = self.norm.normalize(self.x0)
#self.bnds = np.array([[l,u] for l,u in zip(self.lb,self.ub)])
# --- constraints ---
self.WemptyMax = 3500.0
self.CnbMin = 0.003
self.ClbMax = -0.075 #-6.0e-4
self.SMmin = 0.05
self.SMmax = 0.15
self.combatRadiusMin= 750.0
self.RCmin = 125.0
self.VmaxMin = 0.90 # Mach
self.minSectionLen = 1.4*self.propulsion.engine.length
self.CmdeReq = -0.01 # baseline -0.00866
self.alphaTrimMax = 8.0+1e-4 # deg
self.elevTrimMax = 20.0
self.elevTrimMin = -20.0
self.gvfmAero = True
self.Vtrim = 65.0 # 135kts: assumed value
self._load_rbf_models()
# --- payload ---
self.SDB = MassComponent('drop payload', 1132.0, np.array([4.5, 0.0, 0.12]))
# --- misc ---
self.analysisData = np.zeros(10)
# self._upd_approximation()
# --- initial data ---
self.Wf = self.mass.fuel.mass
self.CGf = self.mass.fuel.coords
self.engineOffset = 0.75*self.propulsion.engine.length
self.payloadOffset = 0.75*self.propulsion.engine.length
self.fileFeasible = 'ucav_feasible.txt'
self.set_x(self.x0norm)
def get_bounds(self,x0,c1=0.3):
n = len(self.x0norm)
#c1 = 0.25
treshold = 0.005
xUold = np.ones(n)
xLold = -np.ones(n)
xUnew = np.zeros(n)
xLnew = np.zeros(n)
u = xUold-x0
l = x0 - xLold
delta = np.zeros(len(self.x0))
i=0
for _l,_u in zip(l,u):
delta[i] = min([_l,_u])*c1
if delta[i]<treshold:
d = c1*(xUold[i]-xLold[i])
if _u<treshold:
xLnew[i] = x0[i] - d
xUnew[i] = x0[i]
else:
xLnew[i] = x0[i]
xUnew[i] = x0[i] + d
else:
xUnew[i] = x0[i] + delta[i]
xLnew[i] = x0[i] - delta[i]
print '%.4f\t%.4f\t%.4f'%(_l,_u,delta[i])
i += 1
bounds = np.transpose(np.vstack([xLnew,xUnew]))
return bounds
#
# def _upd_approximation(self):
# pathIn = 'design_out4.txt'
# pathInSamples = 'DOE_LHS250_FFD2_3_3.txt'
# learnData = read_tabulated_data_without_header(pathIn)
# xNorm = read_tabulated_data_without_header(pathInSamples)
# learnData = np.transpose(learnData)
# _Cnb = RbfMod(xNorm, (learnData[2])*1e3)
# self.Cnb = lambda x: _Cnb(x)/1e3
# self.Clb = RbfMod(xNorm, learnData[3])
# self.LD = RbfMod(xNorm, learnData[0])
def set_x(self,xnorm,fullUpdate=True):
"""
To minimize function evaluation, this function re-calculates analysis if
new x is given, otherwise precalculated results are used.
"""
self.xcurNorm = xnorm
x = self.norm.denormalize(xnorm)
try:
self._upd_configuration(x)
self._upd_analysis(xnorm,fullUpdate)
except:
print x
print xnorm
self.display_2d()
self._upd_configuration(x)
print 'Error occured'
self._upd_analysis(xnorm,fullUpdate)
# self.analysisData[0] = 0.0
# self.analysisData[1:] = -np.ones(len(self.analysisData)-1)*100.0
# raise ValueError
def _upd_configuration(self,x):
sweep1 = x[0]
sweep2 = x[1]
chord1 = x[2]
chord2 = x[3]
chord3 = x[4]
span1 = x[5]
span2 = x[6]
twist1 = x[7]
twist2 = x[8]
self.set_spans([span1,span2])
self.set_sweep_angles([sweep1, sweep2])
self.set_chords([chord1,chord2,chord3])
self.set_twist_by_index(twist1,0)
self.set_twist_by_index(twist2,1)
self._set_engine_location()
self._update_mass()
def _set_engine_location(self):
engineDiameter = self.propulsion.engine.diameter
x,l = self.wing.get_max_segment_length(engineDiameter)
self.maxSectionLength = l
cgNew = x+self.engineOffset
cgNew2 = x+self.payloadOffset
#self.mass.empty.update_item_cg('engine',cgNew,0,0)
#self.set_engine_cg(cgNew,0,0)
self.SDB = MassComponent('drop payload', 1132.0, np.array([cgNew2, 0.0, 0.12]))
#self.mass.payload.update_item_cg('drop payload',cgNew,.0,.0)
def _upd_analysis(self,xnorm,fullUpdate):
#self._update_mass()
self._upd_drag()
alt = self.designGoals.cruiseAltitude
aero = self.get_aero_single_point(0.7,1e4,2.0)
self.analysisData[0] = aero.LD
if fullUpdate:
# mission
self.mass.set_fuel_mass(self.Wf, self.CGf)
if not self.mass.payload.item_exists(self.SDB.name):
self.mass.payload.add_component(self.SDB)
self.mass.set_fuel_mass(self.Wf,self.CGf)
self.combatRadius = run_mission_B15(self) /1e3
# performance
self.mass.set_fuel_mass(self.Wf,self.CGf)
if not self.mass.payload.item_exists(self.SDB.name):
self.mass.payload.add_component(self.SDB)
slf = SteadyLevelFlight(self)
self.analysisData[1] = self.mass.empty()
self.analysisData[2] = aero.derivs.Cnb
self.analysisData[3] = aero.derivs.Clb #self.aero.derivs.Clb
self.analysisData[4] = aero.SM
self.analysisData[5] = self.combatRadius
self.analysisData[7] = slf.run_max_TAS(alt).Mach
aeroTrim = self.get_aero_trim(self.Vtrim, 0.0)
self.analysisData[8] = aeroTrim.elevator
self.analysisData[9] = aeroTrim.alpha
self.mass.set_fuel_mass(self.Wf,self.CGf)
if not self.mass.payload.item_exists(self.SDB.name):
self.mass.payload.add_component(self.SDB)
clm = ClimbDescent(self)
self.analysisData[6] = clm.run_max_climb_rate(0).climbRate
print self.analysisData[0]
def f(self,x):
self.neval += 1
self.set_x(x,False)
return -self.analysisData[0]
def g(self,x):
self.set_x(x,True)
_x = self.norm.denormalize(x)
g = np.zeros(12)
g[0] = self.WemptyMax - self.analysisData[1]
g[1] = self.analysisData[2] - self.CnbMin
g[2] = self.ClbMax - self.analysisData[3]
g[3] = self.SMmax - self.analysisData[4]
g[4] = self.analysisData[4] - self.SMmin
g[5] = self.analysisData[5] - self.combatRadiusMin
g[6] = self.analysisData[6] - self.RCmin
g[7] = self.analysisData[7] - self.VmaxMin
g[8] = self.maxSectionLength - self.minSectionLen
g[9] = self.analysisData[8] - self.elevTrimMin
g[10] = _x[0] - _x[1]
g[11] = self.alphaTrimMax - self.analysisData[9]
print g>0
out = ''
for v in g:
out += '%.0e '%v
print out
print '%.4f\t%.4f\t%.4f'%(self.analysisData[1],self.analysisData[5],self.analysisData[8])
g[0] *= 1e-2
g[1] *= 1e4
g[2] *= 1e3
g[3] *= 1e3
g[4] *= 1e3
g[5] *= 1e-1
g[6] *= 1e-1
g[7] *= 1e2
g[9] *= 10.
g[11] *= 10
return g*1000.
def get_aero_single_point(self,velocity,altitude,alpha=0.0,beta=0.0,
elevator=0.0,mass=None,cg=None,inertia=None,CD0=None):
aero = super(DesignFormulation,self).get_aero_single_point(velocity,altitude,alpha,beta,elevator,mass,cg,inertia,CD0)
if self.gvfmAero:
sys.stdout.write('GVFM add> ')
xcurrent = self.xcurNorm
LDold = aero.coef.CL/(aero.coef.CD-self.CD0rbf(xcurrent))
aero.coef.CL += self.CLrbf(xcurrent)
aero.coef.CD += self.CDrbf(xcurrent)-self.CD0rbf(xcurrent)
aero.LD = LDold + self.LDrbf(xcurrent)
aero.SM += self.SMrbf(xcurrent)
aero.CD0 += self.CD0rbf(xcurrent)
aero.k += self.krbf(xcurrent)
return aero
def update_aero_trim(self,velocity,altitude,CmTrim=0.0,loadFactor=1.0,
mass=None,cg=None,inertia=None,CD0=None):
super(DesignFormulation,self).update_aero_trim(velocity,altitude,CmTrim,loadFactor,mass,cg,inertia,CD0)
if self.gvfmAero:
xcurrent = self.xcurNorm
#self.aeroResults.CD0 += self.CD0rbf(xcurrent)
self.aeroResults.k += self.krbf(xcurrent)
def get_drag(self,velocity=None,altitude=None):
cd0 = super(DesignFormulation,self).get_drag(velocity,altitude)
if self.gvfmAero:
return cd0 + self.CD0rbf(self.xcurNorm)
else:
return cd0
def _load_rbf_models(self,DOEpath=None,rsltPath=None):
if DOEpath==None:
DOEpath = r'D:\1. Current work\2014 - UAV performance code\Results\DOE\LHS_dvar9_sample24.txt'
if rsltPath==None:
rsltPath = r'D:\1. Current work\2014 - UAV performance code\Results\DOE\CFDresults.txt'
dCD0 = 0.0005
xDOE = read_tabulated_data_without_header(DOEpath)
fDOE = read_tabulated_data_without_header(rsltPath,1)
self.CLrbf = RbfMod(xDOE, fDOE[:,4]-fDOE[:,13])
self.CDrbf = RbfMod(xDOE, fDOE[:,5]-fDOE[:,14])
self.CD0rbf= RbfMod(xDOE, fDOE[:,11]-fDOE[:,19]+dCD0)
self.krbf = RbfMod(xDOE, fDOE[:,12]-fDOE[:,20])
self.SMrbf = RbfMod(xDOE, fDOE[:,10]-fDOE[:,18],0.5)
self.LDrbf = RbfMod(xDOE, fDOE[:,7] -fDOE[:,15])
self._xdoe = xDOE
def show_results(self):
print '{0:10}={1:10.4f}'.format('LD',self.analysisData[0])
print '{0:10}={1:10.4f}'.format('SM',self.analysisData[4])
print '{0:10}={1:10.4f}'.format('Cnb',self.analysisData[2])
print '{0:10}={1:10.4f}'.format('Clb',self.analysisData[3])
print '{0:10}={1:10.4f}'.format('elev',self.analysisData[8])
print '{0:10}={1:10.4f}'.format('alpha',self.analysisData[9])
print '{0:10}={1:10.4f}'.format('We',self.analysisData[1])
print '{0:10}={1:10.4f}'.format('Rcombat',self.analysisData[5])
print '{0:10}={1:10.4f}'.format('ROC',self.analysisData[6])
print '{0:10}={1:10.4f}'.format('Mmax',self.analysisData[7])
def __init__(self,costFcn,lb,ub):
""" cost function should return f,g"""
self.costFcn = costFcn
self.nEval = 0
self.penalty = 1.0e5
self.norm = Normalization(lb,ub,0,1)
