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 alpha_inv_analysis(airfoil, alpha_i, alpha_f, alpha_step, max_iter, id):
"""Inviscid analysis over range of angle of attacks."""
# Initializes airfoil and assigns NACA
xf = XFoil()
xf.naca(airfoil)
xf.max_iter = max_iter
# Collects values
a, cl, cd, cm, cp = xf.aseq(alpha_i, alpha_f, alpha_step)
x, cp_0 = xf.get_cp_distribution()
# Plots all the data
plot(a, cl, cd, cm, cp, x, cp_0, id)
def cl_visc_analysis(airfoil, cl_i, cl_f, cl_step, re, mach, max_iter, id):
"""Viscous analysis over range of lift coefficients."""
# Initializes airfoil and assigns NACA
xf = XFoil()
xf.naca(airfoil)
xf.max_iter = max_iter
xf.Re = re
xf.M = mach
# Collects values
a, cl, cd, cm, cp = xf.cseq(cl_i, cl_f, cl_step)
x, cp_0 = xf.get_cp_distribution()
# Plots all the data
plot(a, cl, cd, cm, cp, x, cp_0, id)
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)
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)
t1 = time.perf_counter()