def run_cfd_wing_analysis():
Mach = 0.7
altitude = 1e4 # m
ac = DesignFormulation()
ac.load_xls('Baseline1')
ac.setup()
paths.myPaths.set_file_prefix('fw_debug')
igsPath = paths.myPaths.get_tmp_file('igs')
symCasPath = paths.myPaths.get_tmp_file('cas','_sym')
nonsymCasPath = paths.myPaths.get_tmp_file('cas','_nonsym')
create_catia_wing(ac,igsPath)
create_fw_cmesh(ac,igsPath,symCasPath, nonsymCasPath)
#os.remove(igsPath)
# under development
fc = FlightConditions(Mach, altitude)
run_wing_half(nonsymCasPath, fc)
def create_input_files():
from ucav_design_1 import DesignFormulation
# Longitudinal (half wing)
doePath = r'D:\1. Current work\2014 - UAV performance code\Results\norm_results.txt'
#DOE = read_tabulated_data_without_header('LHS_dvar9_sample30.txt')
DOE = read_tabulated_data_without_header(doePath)
ac = DesignFormulation()
ac.load_xls('Baseline1')
ac.setup()
startCase = 30
# Mach = ac.designGoals.cruiseMach
# altitude = ac.designGoals.cruiseAltitude
yplus = .5
wdir = 'D:\CFD'
alpha = [-2,0,2]
# beta = 2.0
niter = 5000
batFileLongitudinal = '%s\\batchCFD.bat'%wdir
fid = open(batFileLongitudinal,'at')
pathFluent = r'C:\Program Files\Ansys Inc\v130\fluent\ntbin\win64\fluent.exe'
for i,xnorm in enumerate(DOE):
if i>0:
name = '%s\\case%d'%(wdir,i+startCase)
caseName = 'case%d'%(i+startCase)
print name
ac.set_x(xnorm,False)
print ac.xCurrent
raw_input()
#FIXME: this part adds section for payload on top
#ac._adjust_root_airfoil()
ac.save_2d_figure('%s.png'%name)
igsPath = '%s.igs'%name
symCasPath = '%s_sym.cas'%name
nonsymCasPath = '%s_half.cas'%name
glfPath = '%s.glf'%name
#create_catia_wing(ac,igsPath)
create_fw_cmesh(ac,igsPath,symCasPath,nonsymCasPath,yplus,glfPath)
Sref = ac.wing.area/2.0
Cref = ac.wing.MAC
#Lref = ac.wing.span
ac._restore_root_airfoil()
CG = ac.get_cg()
#a = 2.0
# outPrefix = '%s\\results\\case%d_sym_a%d_b%d'%(wdir,i+1,a*100,beta*100)
# journalFileRel = 'case%d_sym_a%d_b%d.jou'%(i+1, a*100,beta*100)
# journalFile = '%s_sym_a%d_b%d.jou'%(name, a*100, beta*100)
#run_wing_half(symCasPath, outPrefix, ac.designGoals.fc, a, beta, Sref, Lref, CG, journalFile, niter)
for a in alpha:
outPrefix = '%s\\results\\%s_half_a%d'%(wdir,caseName,a*100)
journalFileRel = '%s_half_a%d.jou'%(name, a*100)
journalFile = '%s_half_a%d.jou'%(name, a*100)
run_wing_half(nonsymCasPath, outPrefix, ac.designGoals.fc, a, 0,
Sref, Cref, CG,journalFile,niter)
fid.write('\"%s\" 3ddp -t8 -i %s -wait\n'%(pathFluent, journalFileRel))
fid.close()
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()
import numpy as np
import random as rd
from ucav_design_1 import DesignFormulation
np.random.seed(10)
param_file = 'ucav_sensitivity_input.txt'
pf = read_param_file(param_file)
param_values = saltelli.sample(25, pf['num_vars'], calc_second_order = False)
scale_samples(param_values, pf['bounds'])
ac = DesignFormulation()
ac.load_xls('Baseline1')
ac.setup()
Y = np.zeros([len(param_values),9])
fid = open('SGOutput2.txt','wt')
fid.close()
for i,param in enumerate(param_values):
out = ac.run_full_analysis(param)
Y[i] = out
fid = open('SGOutput2.txt','at')
for val in out:
fid.write('%.10e '%val)
fid.write('\n')
fid.close()
def plot_results():
ac = DesignFormulation()
ac.load_xls('Baseline1')
# baseline
ac.setup()
ac.gvfmAero = True
x0 = ac.wing.x2d
y0 = ac.wing.y2d
cg0 = ac.get_cg()
xbase = ac.x0norm
ac.set_x(xbase)
ac.show_results()
print ac.get_drag()
# low fidelity optimum
xopt1 = np.array([ 0.20520747,-0.39226611,-0.47326701,-1.,0.14291925,0.98650447,
0.37346922, 0.37756372, 0.65654722])
print 'Low fidelity optimum\n==========='
ac.set_x(xopt1)
ac.show_results()
print ac.get_drag()
x1 = ac.wing.x2d
y1 = ac.wing.y2d
cg1 = ac.get_cg()
xgvfm1 = np.array([-0.10127195,-0.10127187,-0.60597138,-0.99999966,-0.71421434,0.97300896, 1.00000803, 0.57455958,0.3130853])
xgvfm2 = np.array([-0.04819471,-0.04819471,-0.59713618,-0.99999966,-1.,0.94601792,1.00000803,0.81889676,-0.3738294])
xgvfm4 = np.array([-0.10676065, -0.10676065, -0.61007048, -1.00003353, -0.57133293, 0.9857291, 1.00000803, 0.56576939, 0.08997523])
print np.linalg.norm(xgvfm1-xgvfm2)
ac.set_x(xgvfm4)
print ac.get_cg()
print ac.wing.area
print ac.wing.MAC
print ac.wing.span
ac.show_results()
print ac.get_drag()
x3 = ac.wing.x2d
y3 = ac.wing.y2d
cg3 = ac.get_cg()
fig = plt.figure(1)
ax1 = fig.add_subplot(111)
ax1.hold(True)
ax1.axis('equal')
ax1.plot(x0,y0,'ko-',linewidth=2)
ax1.plot(x1,y1,'b^:',linewidth=2)
ax1.plot(x3,y3,'rs--',linewidth=2)
#plt.plot(x2,y2,'k-')
ax1.plot(0,-cg0[0],'ko')
ax1.plot(0,-cg1[0],'b^')
ax1.plot(0,-cg3[0],'rs')
ax1.legend(['Baseline','Low-fi optimum','GVFM optimum'])
#plt.plot(0,-cg2[0],'ko')
plt.show()
