def random_samples_profiles(n):
w = np.linspace(0, .5, 2)
x = np.linspace(-50., 20., 100)
P = CBEMClampedFiberSP()
spirrid = SPIRRID(q = P,
sampling_type = 'LHS',
evars = dict(w = w,
x = x),
tvars = dict(Ll = Ll,
Lr = Lr,
tau = RV('uniform', 0.0, .2),
l = RV('uniform', 5.0, 15.0),
A_f = Af,
E_f = Ef,
theta = RV('uniform', 0.0, .02),
xi = xi,#RV('weibull_min', scale = 0.0179, shape = 5, n_int = 10),
phi = phi,
E_m = Em,
A_m = Am,
Nf = Nf
),
n_int = 20)
for i in range(n):
if i == n - 1:
plt.plot(x, P(0.0, x, *spirrid.get_samples(n)[:, i]),
color = 'black', label = 'random filament response')
plt.plot(x, P(0.0, x, *spirrid.get_samples(n)[:, i]), color = 'black')
plt.plot(x, spirrid.mu_q_arr[1, :], lw = 4, color = 'black', ls = '--',
label = 'normalized yarn repsonse')
#plt.xlabel( '$\mathrm{position}{[mm]}$', fontsize = 24 )
#plt.ylabel( '$\mathrm{force} \, P_\mathrm{y}/N_\mathrm{f} \mathrm{[N]}$', fontsize = 24 )
#plt.title( '$\mathrm{yarn \, crack \, bridge}$' , fontsize = 20 )
plt.xticks(fontsize = 20)
plt.yticks(fontsize = 20)
plt.legend(loc = 'lower right')
plt.ylim(0, 0.35)
plt.show()
def random_samples_Pw(n):
w = np.linspace(0, 1.7, 300)
P = CBEMClampedFiber()
spirrid = SPIRRID(q = P,
sampling_type = 'LHS',
evars = dict(w = w
),
tvars = dict(Ll = 50.,
Lr = 20.,
tau = RV('uniform', 0.05, .15),
l = RV('uniform', 5.0, 10.0),
A_f = Af,
E_f = Ef,
theta = RV('uniform', 0.0, .02),
xi = RV('weibull_min', scale = 0.017, shape = 5, n_int = 10),
phi = phi,
E_m = Em,
A_m = 50.,
Nf = 1700.
),
n_int = 20)
for i in range(n):
if i == n - 1:
plt.plot(w, P(w, *spirrid.get_samples(n)[:, i]),
color = 'black', label = 'random filament response')
plt.plot(w, P(w, *spirrid.get_samples(n)[:, i]), color = 'black')
plt.plot(w, spirrid.mu_q_arr, lw = 4, color = 'black', ls = '--',
label = 'normalized yarn repsonse')
plt.xlabel('$\mathrm{crack width} \, w \mathrm{[mm]}$', fontsize = 24)
plt.ylabel('$\mathrm{force} \, P_\mathrm{y,0}/N_\mathrm{f} \mathrm{[N]}$', fontsize = 24)
plt.xticks(fontsize = 20)
plt.yticks(fontsize = 20)
#plt.title( '$\mathrm{yarn \, crack \, bridge}$' , fontsize = 20 )
plt.legend(loc = 'best')
plt.show()
