def test_get_time_averaged_values(self):
"""Test function `get_time_averaged_values`."""
dim = 3
# Load forces from file.
filepath1 = self.datadir / f'forces{dim}d-single-0.txt'
filepath2 = self.datadir / f'forces{dim}d-single-5.txt'
t, fx, fy, fz = petibmpy.read_forces(filepath1, filepath2)
# Compute time-averaged value in one direction.
fx1, = petibmpy.get_time_averaged_values(t, fx)
self.assertAlmostEqual(fx1, numpy.mean(fx), places=7)
# Compute time-averaged value for each direction.
fx1, fy1, fz1 = petibmpy.get_time_averaged_values(t, fx, fy, fz)
self.assertAlmostEqual(fx1, numpy.mean(fx), places=7)
self.assertAlmostEqual(fy1, numpy.mean(fy), places=7)
self.assertAlmostEqual(fz1, numpy.mean(fz), places=7)
# Compute averaged values providing larger time interval.
time_limits = (-1.0, 100.0)
fx1, fy1, fz1 = petibmpy.get_time_averaged_values(t,
fx,
fy,
fz,
limits=time_limits)
self.assertAlmostEqual(fx1, numpy.mean(fx), places=7)
self.assertAlmostEqual(fy1, numpy.mean(fy), places=7)
self.assertAlmostEqual(fz1, numpy.mean(fz), places=7)
# Compute averaged values providing restricted time interval.
time_limits = (5.0, 6.0)
fx1, fy1, fz1 = petibmpy.get_time_averaged_values(t,
fx,
fy,
fz,
limits=time_limits)
self.assertAlmostEqual(fx1, 0.55)
self.assertAlmostEqual(fy1, 1.55)
self.assertAlmostEqual(fz1, 2.55)
# Check if runtime error is raised when wrong time limits are set.
time_limits = (5.5, 5.5) # 5.5 is not a saved time value
with self.assertRaises(RuntimeError):
fx1, = petibmpy.get_time_averaged_values(t, fx, limits=time_limits)
def get_stats(solution, limits=(0, numpy.infty)):
"""Compute mean and rms values of the force coefficients."""
means = Stats(*petibmpy.get_time_averaged_values(*solution, limits=limits))
rms = Stats(*petibmpy.get_rms_values(*solution, limits=limits))
return means, rms
rho = 1.0
U_inf = 1.0
R = 0.5
A = numpy.pi * R**2
coeff = 1 / (0.5 * rho * U_inf**2 * A)
# Load forces from file and compute force coefficients.
filepath = datadir / 'forces-0.txt'
t, fx, fy, fz = petibmpy.read_forces(filepath)
cd, cl, cz = petibmpy.get_force_coefficients(fx, fy, fz, coeff=coeff)
clz = numpy.sqrt(cl**2 + cz**2)
# Compute the time-averaged force coefficients.
time_limits = (200.0, 250.0)
cd_mean, clz_mean = petibmpy.get_time_averaged_values(t, cd, clz,
limits=time_limits)
print('Time-averaged force coefficients:\n')
print(f'* <CD> = {cd_mean:0.4f}')
print(f'* <sqrt(CL^2 + CZ^2)> = {clz_mean:0.4f}')
print(f'\n(Time limits: {time_limits})')
# Plot history of the force coefficients.
pyplot.rc('font', family='serif', size=14)
fig, ax = pyplot.subplots(figsize=(6.0, 4.0))
ax.set_xlabel('Non-dimensional time')
ax.set_ylabel('Force coefficients')
ax.plot(t, cd, label='$C_D$')
ax.plot(t, clz, label='$\sqrt{C_L^2 + C_z^2}$')
ax.legend(frameon=False)
ax.set_xlim(200.0, 250.0)
import petibmpy
simudir = pathlib.Path(__file__).absolute().parents[1]
# Read 3D forces and convert to force coefficients.
filepath = simudir / 'output' / 'forces-0.txt'
t, fx, fy, fz = petibmpy.read_forces(filepath)
rho, u_inf = 1.0, 1.0 # density and freestream speed
dyn_pressure = 0.5 * rho * u_inf**2 # dynamic pressure
c = 1.0 # chord length
Lz = 3.2 * c # spanwise length
coeff = 1 / (dyn_pressure * c * Lz) # scaling factor for force coefficients
cd, cl, cz = petibmpy.get_force_coefficients(fx, fy, fz, coeff=coeff)
cd_avg, cl_avg = petibmpy.get_time_averaged_values(t,
cd,
cl,
limits=(40.0, 80.0))
# Read 2D forces and convert to force coefficients.
rootdir = simudir.parent
simudir2d = rootdir / 'snake2d2k35'
filepath = simudir2d / 'output' / 'forces-0.txt'
t2, fx2, fy2 = petibmpy.read_forces(filepath)
coeff = 1 / (dyn_pressure * c)
cd2, cl2 = petibmpy.get_force_coefficients(fx2, fy2, coeff=coeff)
cd2_avg, cl2_avg = petibmpy.get_time_averaged_values(t2,
cd2,
cl2,
limits=(40.0, 80.0))
cd_reldiff = (cd2_avg - cd_avg) / cd_avg * 100.0
cl_reldiff = (cl2_avg - cl_avg) / cl_avg * 100.0
return v3 / numpy.linalg.norm(v3)
# Set simulation directory and data directory.
simudir = pathlib.Path(__file__).absolute().parents[1]
datadir = simudir / 'output'
# Create the wing kinematics.
wing = rodney.WingKinematics(Re=200.0, St=0.6, psi=110.0, nt_period=2000)
# Compute the cycle-averaged thrust.
filepath = datadir / 'forces-0.txt'
t, fx, _, _ = petibmpy.read_forces(filepath)
thrust = -fx # switch from drag to thrust
time_limits = (4 * wing.T, 5 * wing.T) # interval to consider for average
thrust_avg, = petibmpy.get_time_averaged_values(t, thrust, limits=time_limits)
# Compute the cycle-averaged thrust coefficient.
rho, U_inf, A_plan = (getattr(wing, name)
for name in ('rho', 'U_inf', 'A_plan'))
scale = 1 / (0.5 * rho * U_inf**2 * A_plan)
ct, = petibmpy.get_force_coefficients(thrust, coeff=scale)
ct_avg, = petibmpy.get_time_averaged_values(t, ct, limits=time_limits)
# Load original boundary coordinates from file.
filepath = simudir / 'wing.body'
wing.load_body(filepath, skiprows=1)
# Compute surface area associated with each Lagrangian marker.
ds = wing.A_plan / wing.size
import petibmpy
show_figure = True # display the Matplotlib figure
save_figure = True # save the Matplotlib figure as PNG
rootdir = pathlib.Path(__file__).absolute().parents[1]
# Load forces and compute mean values for each angle of inclination.
time_limits = (15.0, 20.0)
angles = numpy.arange(0, 90 + 1, 10, dtype=numpy.int32)
cd, cl = [], []
for angle in angles:
simudir = rootdir / f'aoa{angle}'
filepath = simudir / 'output' / 'forces-0.txt'
t, fx, fy, _ = petibmpy.read_forces(filepath)
fx_mean, fy_mean = petibmpy.get_time_averaged_values(t,
fx,
fy,
limits=time_limits)
cd.append(fx_mean)
cl.append(fy_mean)
# Load experimental data from Taira et al. (2007).
datadir = rootdir.parents[2] / 'data'
filepath = datadir / 'taira_et_al_2007_flatplateRe100AR2_cd_exp.dat'
with open(filepath, 'r') as infile:
cd_taira_exp = numpy.loadtxt(infile, unpack=True)
filepath = datadir / 'taira_et_al_2007_flatplateRe100AR2_cl_exp.dat'
with open(filepath, 'r') as infile:
cl_taira_exp = numpy.loadtxt(infile, unpack=True)
# Load numerical data from Taira et al. (2007).
filepath = datadir / 'taira_et_al_2007_flatplateRe100AR2_cd_num.dat'
