def hello():
x = request.args.get('x')
y = request.args.get('y')
Re = float(request.args.get('Re'))
M = float(request.args.get('M'))
Alpha = float(request.args.get('Alpha'))
x = x.split()
y = y.split()
ctrlX = [float(ele) for ele in x]
ctrlY = [float(ele) for ele in y]
bezierX, bezierY = airfoil(ctrlX, ctrlY, 16)
xf = XFoil()
xf.Re = Re
xf.M = 0
xf.max_iter = 100
xf.airfoil = Airfoil(np.array(bezierX), np.array(bezierY))
aero = xf.a(Alpha)
xcp, cp = xf.get_cp_distribution()
y = savgol_filter(cp, 5, 2)
for i in range(30):
y = savgol_filter(y, 5, 2)
LD = aero[0] / aero[1]
vol = PolyArea(bezierX, bezierY)
print(len(xcp))
return jsonify(result=str(round(aero[0], 3)) + " " +
str(round(aero[1], 3)) + " " + str(round(aero[2], 3)) +
" " + str(round(LD, 2)) + " " + str(round(vol, 3)),
xcp=xcp.tolist(),
cp=y.tolist())
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 get_torque(angular_velocity):
torque_sum_small = 0
torque_sum_large = 0
w = angular_velocity
for key, value in dfdict.items():
value["blade_velocity"] = value['r_position'] * w
value["relative_velocity"] = round(
math.sqrt(value["blade_velocity"]**2 + value["wind_velocity"]**2),
2)
value["arctan"] = math.degrees(
math.atan2(value["wind_velocity"], value["blade_velocity"]))
aoa = round(value["arctan"] - value["pitch_angle"], 2)
value["angle_of_attack"] = aoa
re_n = round(
value["relative_velocity"] * value["chord_length"] / 0.00001511, 3)
value["Reynolds_number"] = re_n
xf = XFoil()
if key < 13:
xf.airfoil = naca6409
else:
xf.airfoil = naca2412
xf.Re = re_n
xf.max_iter = 100
xf.n_crit = 9.00
xf.xtr = [1.00, 1.00]
xf.M = 0
value["Cl"], value["Cd"], value["Cm"], value["Cp"] = xf.a(aoa)
force_reference = 0.5 * density * value["relative_velocity"]**2
if math.isnan(value["Cl"]):
value["torque"] = 0
else:
lift = value["Cl"] * force_reference * 0.0125 * value[
'chord_length']
drag = value["Cd"] * force_reference * 0.0125 * value[
'chord_length']
value["torque"] = value["r_position"] * (
lift * math.sin(math.radians(value["pitch_angle"])) -
drag * math.cos(math.radians(value["pitch_angle"])))
if key < 13:
torque_sum_small += value["torque"]
else:
pass
if key > 0:
torque_sum_large += value["torque"]
else:
pass
df2 = pd.DataFrame.from_dict(dfdict, orient="index")
df_collection.append(df2)
torque_sum_avg = 0.5 * (torque_sum_small + torque_sum_large)
return torque_sum_avg
def total_dict(angular_velocity):
torque_sum = 0
w = angular_velocity
for key, value in dfdict.items():
value["blade_velocity"] = value['r_position'] * w
value["relative_velocity"] = round(
math.sqrt(value["blade_velocity"]**2 + value["wind_velocity"]**2),
2)
value["arctan"] = math.degrees(
math.atan2(value["wind_velocity"], value["blade_velocity"]))
aoa = round(value["arctan"] - value["pitch_angle"], 1)
value["angle_of_attack"] = aoa
re_n = round(value["relative_velocity"] * value["chord_length"] /
0.00001511)
value["Reynolds_number"] = re_n
xf = XFoil()
if key < 13:
xf.airfoil = naca6409
else:
xf.airfoil = naca2412
xf.Re = round(re_n / 100) * 100
xf.max_iter = 200
xf.n_crit = 9.00
xf.xtr = [1.00, 1.00]
xf.M = 0
c_l, c_d, c_m, c_p = xf.a(aoa)
force_reference = 0.5 * density * value["relative_velocity"]**2
if math.isnan(c_l):
pass
else:
value["Cl"] = c_l
value["Cd"] = c_d
value["Cm"] = c_m
value["Cp"] = c_p
lift = c_l * force_reference * 0.0125 * value['chord_length']
drag = c_d * force_reference * 0.0125 * value['chord_length']
value["lift"] = lift
value["drag"] = drag
# value["torque"] = value["r_position"] * lift * math.sin(math.radians(value["pitch_angle"]))
torque = value["r_position"] * (
lift * math.sin(math.radians(value["pitch_angle"])) -
drag * math.cos(math.radians(value["pitch_angle"])))
value["torque"] = torque
torque_sum += torque
xf.reset_bls()
# detailed_df = pd.DataFrame.from_dict(dfdict, orient="index")
# print(detailed_df)
print(torque_sum, angular_velocity)
return dfdict, torque_sum
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]
class XFoilEnv(gym.Env):
"""
Description:
A pole is attached by an un-actuated joint to a cart, which moves along a frictionless track. The pendulum starts upright, and the goal is to prevent it from falling over by increasing and reducing the cart's velocity.
Source:
This environment corresponds to the version of the cart-pole problem described by Barto, Sutton, and Anderson
Observation:
Type: Box(4)
Num Observation Min Max
0 Cart Position -4.8 4.8
1 Cart Velocity -Inf Inf
2 Pole Angle -24 deg 24 deg
3 Pole Velocity At Tip -Inf Inf
Actions:
Type: Discrete(2)
Num Action
0 Push cart to the left
1 Push cart to the right
Note: The amount the velocity that is reduced or increased is not fixed; it depends on the angle the pole is pointing. This is because the center of gravity of the pole increases the amount of energy needed to move the cart underneath it
Reward:
Reward is 1 for every step taken, including the termination step
Starting State:
All observations are assigned a uniform random value in [-0.05..0.05]
Episode Termination:
Pole Angle is more than 12 degrees
Cart Position is more than 2.4 (center of the cart reaches the edge of the display)
Episode length is greater than 200
Solved Requirements
Considered solved when the average reward is greater than or equal to 195.0 over 100 consecutive trials.
"""
metadata = {
'render.modes': ['human', 'rgb_array'],
'video.frames_per_second' : 50
}
def __init__(self):
self.xf = XFoil()
self.min_action = np.array([0.1, 0.05, 1.0, 0.05, 0.4, 1.0, 0.0])
self.max_action = np.array([0.4, 0.4, 3.0, 3.0, 8.0, 10.0, 10.0])
''' 測試開始, 可省略測試'''
# (.01, .4), (.05, .4), (1, 3), (0.05, 3), (0.4, 8), (1, 10)
# self.xf.airfoil = naca0012
# k = [0.08813299, 0.28250898, 2.80168427, 2.56204214, 1.48703742, 8.53824561]
# k = [0.34422, 0.38976, 1.1, 2.9989, 1.6071, 9.9649]
k = [0.1584, 0.1565, 2.1241, 1.8255, 11.6983, 3.827] # org
# k = [0.1784, 0.1365, 2.1201, 1.8057, 3.8071, 11.7009]
# k = [0.1472, 0.1638, 2.1041, 1.8156, 3.8141, 11.6808]
# k = [0.1784, 0.1365, 2.1201, 1.8057, 3.8071, 11.7009]
# k = [0.1783, 0.1366, 2.1283, 1.8073, 3.8325, 11.7176]
# k = [0.25840, 0.14474, 2.22410, 1.92550, 11.59984, 3.92623]
airfoil = construct_airfoil(*k)
x, y = get_coords_plain(airfoil._spline(100))
self.xf.airfoil = Airfoil(x=x, y=y)
# test_airfoil = NACA4(2, 3, 15)
# a = test_airfoil.max_thickness()
# self.xf.airfoil = test_airfoil.get_coords()
self.xf.Re = 1e6
self.xf.M = 0.04
self.xf.print = False
cl, cd, cm, cp = self.xf.a(9)
x = np.array(x, dtype='float32')
y = np.array(y,dtype='float32')
# reward = cl/cd
reward = cl
''' 測試結束, 可省略測試'''
# cl, cd, cm, cp = self.xf.a(12.2357)
# self.action_space = spaces.Discrete(30)
self.action_space = spaces.Box(self.min_action, self.max_action, dtype=np.float32)
# high = np.array([100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0])
high = np.array([100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0])
self.observation_space = spaces.Box(-high, high, dtype=np.float32) #創建state大小(25,f22機翼,b3cl.cd.aoa)
self.seed()
self.viewer = None
self.state = None
self.steps_beyond_done = None
def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def step(self, action):
# assert self.action_space.contains(action), "%r (%s) invalid"%(action, type(action))
''' action 包含 6 個機翼形狀控制參數以及 1 個攻角'''
angular = action[6]
k = action[0:6]
'''將機翼控制座標傳入 airfoil, 並計算翼面之座標'''
airfoil = construct_airfoil(*k)
x, y = get_coords_plain(airfoil._spline(100))
'''將座標傳入 xfoil '''
self.xf.airfoil = Airfoil(x=x, y=y)
# state = self.state
self.xf.Re = 1e6
self.xf.M = 0.04
'''計算 cl, cd, cm, cp 當角度為 angular 時'''
cl, cd, cm, cp = self.xf.a(angular)
'''如果結果不穩定, 有無限大之值, 重設 state'''
if np.isnan(cl) or np.isnan(cd) or np.isnan(cm) or np.isnan(cp):
reward = -10.0
# self.state = self.reset()
done = 0
else:
'''如果結果穩定, 結束這個 weight 的計算'''
'''升力最佳或升阻比最佳在此設定'''
# reward = cl/cd
reward = cl
'''從機翼座標裡抽取 11 點當作 state'''
x1, y1 = get_coords_plain(airfoil._spline(6))
'''state : 22 個機翼形狀值, 1 個角度, 1 個 cl, cd'''
# self.state = np.append(np.append(np.append(np.append(x1, y1),angular), cl), cd)
# self.state = np.append(np.append(x1, y1),angular)
self.state = np.append(x1, y1)
done = 1
return np.array(self.state), reward, done, {}
def step1(self, action):
# assert self.action_space.contains(action), "%r (%s) invalid"%(action, type(action))
angular = action[6]
k = action[0:6]
airfoil = construct_airfoil(*k)
x, y = get_coords_plain(airfoil._spline(100))
x1, y1 = get_coords_plain(airfoil._spline(6))
self.xf.airfoil = Airfoil(x=x, y=y)
# state = self.state
self.xf.Re = 1e6
self.xf.M = 0.04
cl, cd, cm, cp = self.xf.a(angular)
if np.isnan(cl) or np.isnan(cd) or np.isnan(cm) or np.isnan(cp):
# reward = np.nan
reward = -10
# self.state = self.reset()
done = 0
else:
# reward = cl/cd
reward = cl
done = 1
# self.state = np.append(np.append(np.append(np.append(x1, y1),angular), cl), cd)
# self.state = np.append(np.append(x1, y1),angular)
self.state = np.append(x1, y1)
return np.array(self.state), reward, done, x, y
def reset(self):
# (.01, .4), (.05, .4), (1, 3), (0.05, 3), (0.4, 8), (1, 10)
# 0.08813299, 0.28250898, 2.80168427, 2.56204214, 1.48703742, 8.53824561
'''為了避免 state 有無窮大的值, 所以設定decays範圍'''
# decays = [1.0, 0.5, 0.25, 0.125, 0.0625]
decays = [1.0, 0.999, 0.995, 0.99, 0.95, 0.9, 0.5]
for decay in decays:
tmp1 = self.np_random.uniform(low=-1.0, high=1.0, size=(7,))
# tmp = tmp * [0.39, 0.35, 2.0, 2.95, 7.6, 9, 10] + [0.01, 0.05, 1, 0.05, 0.4, 1, 0]
# tmp = tmp * [0.01, 0.1, 0.5, 0.5, 0.1, 1.0, 5] + [0.08813299, 0.28250898, 2.50168427, 2.56, 1.487, 8.54, 0]
# k = [0.1584, 0.1565, 2.1241, 1.8255, 3.827, 11.6983]
'''從標準NACA5410開始找'''
tmp1 = tmp1 * decay
tmp = tmp1 * [0.12, 0.12, 0.12, 0.12, 0.12, 0.12, 5] + [0.1584, 0.1565, 2.1241, 1.8255, 11.6983, 3.827, 6]
airfoil = construct_airfoil(*tmp)
x, y = get_coords_plain(airfoil._spline(100))
self.xf.airfoil = Airfoil(x=x, y=y)
self.xf.Re = 1e6
self.xf.M = 0.04
cl, cd, cm, cp = self.xf.a(tmp[6])
if not np.isnan(cl):
break
x, y = get_coords_plain(airfoil._spline(6))
self.xf.Re = 1e6
self.xf.M = 0.04
# self.state = np.append(np.append(np.append(np.append(x, y), tmp1[6]), cl), cd)
# self.state = np.append(np.append(x, y), tmp1[6])
self.state = np.append(x, y)
self.steps_beyond_done = None
return np.array(self.state)
def render(self, mode='human'):
return None
def close(self):
if self.viewer:
self.viewer.close()
self.viewer = None
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)
#TODO: Xfoil
xf = XFoil()
xf.print = False
xf.max_iter = 40
xf.airfoil = foil
xf.xtr = [0.0, 0.0]
Minf = 0.2
AoA = 8.0
Re = 1e7
fname = 'feature-xfoil.txt'
xf.M = Minf
xf.Re = Re
cl, cd, cm, cp = xf.a(AoA)
x, cp = xf.get_cp_distribution()
with open(fname, 'w') as f:
f.write('%10s %15.6f \n'%('Minf', Minf))
f.write('%10s %15.6f \n'%('AoA', AoA))
f.write('%10s %15.6f \n'%('Re', Re/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))
fF = PhysicalXfoil(Minf, AoA, Re)
fF.setdata(x,y,cp)
fF.extract_features()
fF.output_features(fname=fname, append=True)