from matplotlib import pyplot as plt
from anaflow import ext_thiem_3d, ext_grf_steady
from anaflow.tools.coarse_graining import K_CG
rad = np.geomspace(0.05, 4) # radius from the pumping well in [0, 4]
r_ref = 2.0 # reference radius
var = 0.5 # variance of the log-transmissivity
len_scale = 10.0 # correlation length of the log-transmissivity
KG = 1e-4 # the geometric mean of the transmissivity
anis = 0.7 # aniso ratio
rate = -1e-4 # pumping rate
head1 = ext_thiem_3d(rad, r_ref, KG, var, len_scale, anis, 1, rate)
head2 = ext_grf_steady(rad,
r_ref,
K_CG,
rate=rate,
cond_gmean=KG,
var=var,
len_scale=len_scale,
anis=anis)
plt.plot(rad, head1, label="Ext Thiem 3D")
plt.plot(rad, head2, label="grf(K_CG)", linestyle="--")
plt.xlabel("r in [m]")
plt.ylabel("h in [m]")
plt.legend()
plt.tight_layout()
plt.show()
# -*- coding: utf-8 -*-
import numpy as np
from matplotlib import pyplot as plt
from anaflow import ext_grf, ext_grf_steady, grf
time = 1e4 # time point for steady state
rad = np.geomspace(0.1, 10) # radius from the pumping well in [0, 4]
r_ref = 10.0 # reference radius
K = 1e-4 # the geometric mean of the transmissivity
rate = -1e-4 # pumping rate
dim = 1.5 # using a fractional dimension
head1 = ext_grf_steady(rad, r_ref, K, dim=dim, rate=rate)
head2 = ext_grf(time, rad, [1e-4], [K], [0, r_ref], dim=dim, rate=rate)
head3 = grf(time, rad, 1e-4, K, dim=dim, rate=rate)
head3 -= head3[-1] # quasi-steady
plt.plot(rad, head1, label="Ext GRF steady")
plt.plot(rad, head2, label="Ext GRF (t={})".format(time), linestyle="--")
plt.plot(rad,
head3,
label="GRF quasi-steady (t={})".format(time),
linestyle=":")
plt.xlabel("r in [m]")
plt.ylabel("h in [m]")
plt.legend()
plt.tight_layout()
plt.show()
# calculate a disk-distribution of "trans" by calculating harmonic means
R_part = specialrange_cut(r_well, r_bound, parts, cut_off)
K_part = annular_hmean(cond,
R_part,
ann_dim=dim,
K_far=K_far,
K_well=K_well,
len_scale=len_scale)
S_part = np.full_like(K_part, S)
# calculate transient and steady heads
head1 = ext_grf(time, rad, S_part, K_part, R_part, dim=dim, rate=rate)
head2 = ext_grf_steady(rad,
r_bound,
cond,
dim=dim,
rate=-1e-4,
K_far=K_far,
K_well=K_well,
len_scale=len_scale)
# plotting
gs = gridspec.GridSpec(2, 1, height_ratios=[1, 3])
ax1 = plt.subplot(gs[0])
ax2 = plt.subplot(gs[1], sharex=ax1)
time_ticks = []
for i, step in enumerate(time):
label = "Transient" if i == 0 else None
ax2.plot(rad, head1[i], label=label, color="C" + str(i))
time_ticks.append(head1[i][-1])
ax2.plot(rad, head2, label="Steady", color="k", linestyle=":")
# -*- coding: utf-8 -*-
import numpy as np
from matplotlib import pyplot as plt
from anaflow import ext_thiem_2d, ext_grf_steady
from anaflow.tools.coarse_graining import T_CG
rad = np.geomspace(0.05, 4) # radius from the pumping well in [0, 4]
r_ref = 2.0 # reference radius
var = 0.5 # variance of the log-transmissivity
len_scale = 10.0 # correlation length of the log-transmissivity
TG = 1e-4 # the geometric mean of the transmissivity
rate = -1e-4 # pumping rate
head1 = ext_thiem_2d(rad, r_ref, TG, var, len_scale, rate)
head2 = ext_grf_steady(rad, r_ref, T_CG, rate=rate, trans_gmean=TG, var=var, len_scale=len_scale)
plt.plot(rad, head1, label="Ext Thiem 2D")
plt.plot(rad, head2, label="grf(T_CG)", linestyle="--")
plt.xlabel("r in [m]")
plt.ylabel("h in [m]")
plt.legend()
plt.tight_layout()
plt.show()
sol.trans(rad_lin),
linewidth=1,
color="w",
alpha=0.6)
axis[i][0].set_ylim([K_well - 0.15 * K_diff, K_far + 0.15 * K_diff])
axis[i][0].set_title(sol.label)
# timesteps
head1 = ext_grf(time,
rad,
sol.s_part,
sol.t_part,
sol.r_part,
K_well=sol.t_w,
dim=dim,
rate=rate)
head2 = ext_grf_steady(rad, r_bound, sol.trans, dim=dim, rate=rate)
for k, step in enumerate(time):
axis[i][1].plot(rad,
head1[k],
dashes=dashes(i=k + 1, max_n=9),
alpha=1.,
label=time_labels[k],
linewidth=3,
color="k")
axis[i][1].plot(rad,
head2,
label="steady state",
linewidth=2.5,
color="C1",
alpha=1,
zorder=-10)