def get_cls(coords):
xf = XFoil()
xf.print = False
cl_s = []
for coord in coords:
cl = get_cl(coord, xf)
cl_s.append(cl)
return np.array(cl_s)
def get_cl(coord, xf=None, angle=5):
if xf is None:
xf = XFoil()
xf.print = False
xf.Re = 3e6
xf.max_iter = 100
datax, datay = coord.reshape(2, -1)
xf.airfoil = Airfoil(x=datax, y=datay)
c = xf.a(angle)
cl= c[0]
return cl
def initialize(self):
super().initialize()
self.options.declare("print", default=False, types=bool)
xf = XFoil()
xf.print = False
self.options.declare("_xf", default=xf, types=XFoil, allow_none=True)
self.options.declare("_pool",
default=ThreadPool(processes=1),
types=ThreadPool,
allow_none=True)
self.recording_options["options_excludes"] = ["_xf", "_pool"]
def evaluate(self,individual):
DELTA = 1e10
#----------------------------------
#遺伝子に基づいて新翼型を生成
#----------------------------------
#遺伝子に基づきスプライン翼型を作成
x = individual[:int(len(individual)/2)]
x.insert(0,1.0)
x.insert(int(len(x)/2)+1,0.0)
x.append(1.0)
y = individual[int(len(individual)/2):]
if not (all([u - d > 0 for u, d in zip(y[:int(len(y)/2)], y[int(len(y)/2):])]) or all([u - d < 0 for u, d in zip(y[:int(len(y)/2)], y[int(len(y)/2):])])):
print("crossed")
return [DELTA*10]*self.NOBJ
y.insert(0,0.0)
y.insert(int(len(y)/2)+1,0.0)
y.append(0.0)
newdat = fc.spline_foil(x, y, 200)
shape_dat = fc.shape_dat([[a, b] for a, b in zip(newdat[0][::-1], newdat[1][::-1])])
#翼型の形に関する情報を取得する
foil_para = fc.get_foil_para(shape_dat)
mt, mta, mc, mca, s, crossed, bd, bt, bc, smooth, td = foil_para
# mt: 最大翼厚(百分率)
# mta: 最大翼厚位置(百分率)
# mc: 最大キャンバー(百分率)
# mca: 最大きゃんばー位置(百分率)
# s: 翼型の下面における、最大y座標-最小y座標
# crossed: 翼型が交差しているならTrue,それ以外ならFalse
# bd: 翼型の粗さ(大きいほど粗い)
# bt: 翼厚分布の粗さ(大きいほど粗い)
# bc: キャンバー分布の粗さ(大きいほど粗い)
# smooth: 無視
# td: 翼厚分布
if crossed:
print("crossed_a")
return [DELTA*10]*self.NOBJ
else:
print("hi_a")
#新しい翼型をAerofoilオブジェクトに適用
datx = np.array(newdat[0][::-1])
daty = np.array(newdat[1][::-1])
newfoil = Airfoil(x = datx, y = daty)
#翼型の形に関する拘束条件
penalty = 0
if not all([t >= 0.0035 for t in td[10:80]]):
penalty += 100 * (sum([abs(t - 0.0035)*10 for t in td[15:85] if t - 0.0035 < 0]))
if not all([t <= 0.015 for t in td[:15]]):
penalty += 100 * (sum([abs(t - 0.015)*10 for t in td[:15] if t > 0.015]))
if mta > 0.4:
penalty += 100 * (mta - 0.4)
if mc < 0.0:
penalty += 100 * (-mc)
if datx[0] > 1.002 or datx[0] < 0.998:
print("invalid foil")
return [DELTA*10]*self.NOBJ
#----------------------------------
#新翼型の解析
#----------------------------------
try:
xf = XFoil()
#レイノルズ数の設定
xf.airfoil = newfoil
xf.Re = self.re
xf.print = False
xf.max_iter = 40
#xf.polar = "polar" + id
#境界要素法計算時1ステップにおける計算回数
#xf.repanel(n_nodes = 180)
#計算結果格納
#result = xf.OneAlpha()
cl, cd, cm, cp = xf.a(5.0)
#----------------------------------
#目的値
#----------------------------------
if cl >= 0:
obj1 = 1/cl
else:
obj1 = self.delta
obj2 = cd
except Exception as e:
obj1,obj2=[DELTA]*self.NOBJ
traceback.print_exc()
if (np.isnan(obj1)):
obj1 = DELTA
if (np.isnan(obj2)):
obj2 = DELTA
return [obj1 + penalty, obj2 + penalty]
def analyze_airfoil(x,
y_u,
y_l,
cl,
rey,
mach=0,
xf=None,
pool=None,
show_output=False):
"""
Analyze an airfoil at a given lift coefficient for given Reynolds and Mach numbers using XFoil.
Parameters
----------
x : array_like
Airfoil x-coordinates
y_u, y_l : array_like
Airfoil upper and lower curve y-coordinates
cl : float
Target lift coefficient
rey, mach : float
Reynolds and Mach numbers
xf : XFoil, optional
An instance of the XFoil class to use to perform the analysis. Will be created if not given
pool : multiprocessing.ThreadPool, optional
An instance of the multiprocessing.Threadpool class used to run the xfoil_worker. Will be created if not given
show_output : bool, optional
If True, a debug string will be printed after analyses. False by default.
Returns
-------
cd, cm : float or np.nan
Drag and moment coefficients of the airfoil at specified conditions, or nan if XFoil did not run successfully
"""
# If the lower and upper curves swap, this is a bad, self-intersecting airfoil. Return 1e27 immediately.
if np.any(y_l > y_u):
return np.nan
else:
clean_xf = False
if xf is None:
xf = XFoil()
xf.print = show_output
clean_xf = True
clean_pool = False
if pool is None:
pool = ThreadPool(processes=1)
clean_pool = True
xf.airfoil = Airfoil(x=np.concatenate((x[-1:0:-1], x)),
y=np.concatenate((y_u[-1:0:-1], y_l)))
xf.Re = rey
xf.M = mach
xf.max_iter = 100
xf.n_crit = 0.1
cd, cm = pool.apply(xfoil_worker, args=(xf, cl))
if clean_xf:
del xf
if clean_pool:
del pool
return cd, cm, None if clean_xf else xf
def evaluate(individual):
global code_division
#----------------------------------
#遺伝子にも続いて新翼型を生成
#----------------------------------
#遺伝子をデコード
ratios = decoder(individual, code_division)
#遺伝子に基づき翼型を混合して、新しい翼型を作る
datlist_list = [fc.read_datfile(file) for file in datfiles]
datlist_shaped_list = [fc.shape_dat(datlist) for datlist in datlist_list]
newdat = fc.interpolate_dat(datlist_shaped_list,ratios)
#翼型の形に関する情報を取得する
#foilpara == [最大翼厚、最大翼厚位置、最大キャンバ、最大キャンバ位置、S字の強さ]
foil_para = fc.get_foil_para(newdat)
#新しい翼型をAerofoilオブジェクトに適用
datx = np.array([ax[0] for ax in newdat])
daty = np.array([ax[1] for ax in newdat])
newfoil = Airfoil(x = datx, y = daty)
mt, mta, mc, mca, s = foil_para
#----------------------------------
#翼の形に関する拘束条件
#----------------------------------
penalty = 0
print('===================')
if(mc<0):
print("out of the border")
print("reverse_cmaber")
penalty -= mc
if(mt<0.08):
print("out of the border")
print("too_thin")
penalty += 0.08-mt
if(mt>0.11):
print("out of the border")
print("too_fat")
penalty += mt-0.11
#if(foil_para[4]>0.03):
# print("out of the border")
# print("peacock")
# print('===================')
# return (1.0+(foil_para[4]-0.03),)*NOBJ
if(mta<0.23):
print("out of the border")
print("Atama Dekkachi!")
penalty += 0.23 - mta
if(mta>0.3):
print("out of the border")
print("Oshiri Dekkachi!")
penalty += mta - 0.3
#----------------------------------
#新翼型の解析
#----------------------------------
xf = XFoil()
xf.airfoil = newfoil
#レイノルズ数の設定
xf.Re = 1.5e5
#境界要素法計算時1ステップにおける計算回数
xf.max_iter = 60
#座標整形
xf.repanel(n_nodes = 300)
xf.print = False
#計算結果格納
a, cl, cd, cm, cp = xf.cseq(0.4, 1.1, 0.1)
lr = [l/d for l, d in zip(cl,cd)]
#----------------------------------
#目的値
#----------------------------------
try:
#揚抗比の逆数を最小化
obj1 = 1/lr[1]
#揚抗比のピークを滑らかに(安定性の最大化)
maxlr = max(lr)
maxlr_index = lr.index(maxlr)
obj2 = abs(maxlr - lr[maxlr_index+1])
#下面の反りを最小化(製作再現性の最大化)
obj3 = foil_para[4]
except Exception as e:
obj1,obj2,obj3=[1.0]*NOBJ
traceback.print_exc()
if (np.isnan(obj1) or obj1 > 1):
obj1 = 1
if (np.isnan(obj2) or obj2 > 1):
obj2 = 1
if (np.isnan(obj3) or obj3 > 1):
obj3 = 1
obj1 += penalty
obj2 += penalty
obj3 += penalty
print("individual",individual)
print("evaluate",obj1,obj2,obj3)
print("max_thickness",foil_para[0])
print("at",foil_para[1])
print("max_camber",foil_para[2])
print("at",foil_para[3])
print("S",foil_para[4])
print('===================')
return [obj1, obj2, obj3]
if not use_dataset:
npz = np.load(input_path)
labels = npz[npz.files[0]]
coords = npz[npz.files[1]]
else:
perfs_npz = np.load("./dataset/standardized_perfs.npz")
coords_npz = np.load("./dataset/standardized_coords.npz")
coords = coords_npz[coords_npz.files[0]]
coord_mean = coords_npz[coords_npz.files[1]]
coord_std = coords_npz[coords_npz.files[2]]
perfs = perfs_npz[perfs_npz.files[0]]
perf_mean = perfs_npz[perfs_npz.files[1]]
perf_std = perfs_npz[perfs_npz.files[2]]
xf = XFoil()
xf.print = False
cnt = 0
print("start calculating!")
start = time.time()
coords = coords*coord_std+coord_mean if use_dataset else coords
for label, coord in zip(labels, coords):
cl = get_cl(xf, coord)
if not np.isnan(cl):
cnt+=1
if type(label) is np.float64:
label = str(round(label, 3))
else:
label = str(round(label[0],3))
print("label: {0}, cl: {1}".format(label, cl))
end = time.time()
def feature_xfoil(cst_u,
cst_l,
t,
Minf: float,
Re,
AoA,
n_crit=0.1,
fname='feature-xfoil.txt'):
'''
Evaluate by xfoil and extract features.
Inputs:
---
cst-u, cst-l: list of upper/lower CST coefficients of the airfoil. \n
t: airfoil thickness or None \n
Minf: free stream Mach number for wall Mach number calculation \n
Re, AoA (deg): flight condition (s), float or list, for Xfoil \n
n_crit: critical amplification ratio for transition in xfoil \n
fname: output file name. If None, then no output \n
### Dependencies: cst-modeling3d, xfoil
'''
from cst_modeling.foil import cst_foil
from xfoil import XFoil
from xfoil.model import Airfoil
#TODO: Build foil
#! 201 is the maximum amount of points that xfoil can handle
#! tail = 0.001 is to avoid point overlap
xx, yu, yl, t0, R0 = cst_foil(201, cst_u, cst_l, x=None, t=t, tail=0.001)
#! xfoil do not support leading edge of (0,0) on both upper and lower surface
x = np.array(list(reversed(xx[1:])) + xx[1:])
y = np.array(list(reversed(yu[1:])) + yl[1:])
foil = Airfoil(x, y)
#TODO: Xfoil
xf = XFoil()
xf.print = False
xf.airfoil = foil
xf.max_iter = 40
#* Transition by power law
xf.n_crit = n_crit
#TODO: Xfoil calculation
if not isinstance(Re, list):
Re = [Re]
AoA = [AoA]
n = len(Re)
for i in range(n):
xf.reset_bls()
if Re[i] is not None:
xf.Re = Re[i]
cl, cd, cm, cp = xf.a(AoA[i])
x, cp = xf.get_cp_distribution()
print(xf.Re, AoA[i], cl)
#* Extract features
fF = PhysicalXfoil(Minf, AoA[i], Re[i])
fF.setdata(x, y, cp)
fF.extract_features()
#* Output
if fname is None:
continue
if i == 0:
f = open(fname, 'w')
else:
f = open(fname, 'a')
f.write('\n')
f.write('%10s %15.6f \n' % ('Minf', Minf))
f.write('%10s %15.6f \n' % ('AoA', AoA[i]))
f.write('%10s %15.6f \n' % ('Re', Re[i] / 1e6))
f.write('%10s %15.6f \n' % ('CL', cl))
f.write('%10s %15.6f \n' % ('Cd', cd))
f.write('%10s %15.6f \n' % ('Cm', cm))
f.close()
fF.output_features(fname=fname, append=True)
def evaluate(self, individual):
#解析が発散した際の評価値
DELTA = 1e10
#----------------------------------
#遺伝子に基づいて新翼型を生成
#----------------------------------
#遺伝子をデコード
ratios = self.decoder(individual, self.code_division)
#遺伝子に基づき翼型を混合して、新しい翼型を作る
datlist_list = [fc.read_datfile(file) for file in self.datfiles]
datlist_shaped_list = [
fc.shape_dat(datlist) for datlist in datlist_list
]
newdat = fc.interpolate_dat(datlist_shaped_list, ratios)
#翼型の形に関する情報を取得する
mt, mta, mc, mca, s, crossed, bd, bt, bc, smooth, td = fc.get_foil_para(
newdat)
#新しい翼型をAerofoilオブジェクトに適用
datx = np.array([ax[0] for ax in newdat])
daty = np.array([ax[1] for ax in newdat])
newfoil = Airfoil(x=datx, y=daty)
#----------------------------------
#翼の形に関する拘束条件
#----------------------------------
penalty = 0
#キャンバに関する拘束条件
if (mc < 0):
penalty -= mc
#最大翼厚に関する拘束条件
if (mt < 0.08):
penalty += 0.08 - mt
if (mt > 0.11):
penalty += mt - 0.11
#最大翼厚位置に関する拘束条件
if (mta < 0.23):
penalty += 0.23 - mta
if (mta > 0.3):
penalty += mta - 0.3
#----------------------------------
#新翼型の解析
#----------------------------------
xf = XFoil()
xf.airfoil = newfoil
#レイノルズ数の設定
xf.Re = self.re
#境界要素法計算時1ステップにおける計算回数
xf.max_iter = 60
xf.print = False
#計算結果格納
a, cl, cd, cm, cp = xf.cseq(0.4, 1.1, 0.1)
#----------------------------------
#目的値
#----------------------------------
try:
#揚抗比の逆数を最小化
obj1 = 1 / lr[1]
#揚抗比のピークを滑らかに(安定性の最大化)
maxlr = max(lr)
maxlr_index = lr.index(maxlr)
obj2 = abs(maxlr - lr[maxlr_index + 1])
#下面の反りを最小化(製作再現性の最大化)
obj3 = s
except Exception as e:
obj1, obj2, obj3 = [DELTA] * self.NOBJ
traceback.print_exc()
if (np.isnan(obj1) or obj1 > 1):
obj1 = DELTA
if (np.isnan(obj2) or obj2 > 1):
obj2 = DELTA
if (np.isnan(obj3) or obj3 > 1):
obj3 = DELTA
obj1 += penalty
obj2 += penalty
obj3 += penalty
return [obj1, obj2, obj3]
