def test_tang_and_onitsuka_one():
"""tang_and_onitsuka_vert_and_radial
vertical and radial consolidation (no well resitance)
H=1
kv=kh=10, mv=1, gamw=10
dTv=kvref/mvref/gamw/H**2 = 1
#re=0.5, rw = 0.03, n = 16.6667, mu = 2.074475589, etref = 3.856396307
#dTh = 2*khref/mvref/gamw/mu = 3.856396307
"""
t = np.array([
1.00000000e-03, 2.00000000e-03, 3.00000000e-03, 4.00000000e-03,
5.00000000e-03, 6.00000000e-03, 7.00000000e-03, 8.00000000e-03,
9.00000000e-03, 1.00000000e-02, 2.00000000e-02, 3.00000000e-02,
4.00000000e-02, 5.00000000e-02, 6.00000000e-02, 7.00000000e-02,
8.00000000e-02, 9.00000000e-02, 1.00000000e-01, 1.10000000e-01,
1.20000000e-01, 1.30000000e-01, 1.40000000e-01, 1.50000000e-01,
1.60000000e-01, 1.70000000e-01, 1.80000000e-01, 1.90000000e-01,
2.00000000e-01, 2.10000000e-01, 2.20000000e-01, 2.30000000e-01,
2.40000000e-01, 2.50000000e-01, 2.60000000e-01, 2.70000000e-01,
2.80000000e-01, 2.90000000e-01, 3.00000000e-01, 3.10000000e-01,
3.20000000e-01, 3.30000000e-01, 3.40000000e-01, 3.50000000e-01,
3.60000000e-01, 3.70000000e-01, 3.80000000e-01, 3.90000000e-01,
4.00000000e-01, 4.10000000e-01, 4.20000000e-01, 4.30000000e-01,
4.40000000e-01, 4.50000000e-01, 4.60000000e-01, 4.70000000e-01,
4.80000000e-01, 4.90000000e-01, 5.00000000e-01, 5.10000000e-01,
5.20000000e-01, 5.30000000e-01, 5.40000000e-01, 5.50000000e-01,
5.60000000e-01, 5.70000000e-01, 5.80000000e-01, 5.90000000e-01,
6.00000000e-01, 6.10000000e-01, 6.20000000e-01, 6.30000000e-01,
6.40000000e-01, 6.50000000e-01, 6.60000000e-01, 6.70000000e-01,
6.80000000e-01, 6.90000000e-01, 7.00000000e-01, 7.10000000e-01,
7.20000000e-01, 7.30000000e-01, 7.40000000e-01, 7.50000000e-01,
7.60000000e-01, 7.70000000e-01, 7.80000000e-01, 7.90000000e-01,
8.00000000e-01, 8.10000000e-01, 8.20000000e-01, 8.30000000e-01,
8.40000000e-01, 8.50000000e-01, 8.60000000e-01, 8.70000000e-01,
8.80000000e-01, 8.90000000e-01, 9.00000000e-01, 9.10000000e-01,
9.20000000e-01, 9.30000000e-01, 9.40000000e-01, 9.50000000e-01,
9.60000000e-01, 9.70000000e-01, 9.80000000e-01, 9.90000000e-01,
1.00000000e+00, 1.01000000e+00
])
avp = 100 * np.array([[
0.00324696, 0.00641694, 0.00953238, 0.0126017, 0.01562987, 0.01862029,
0.02157548, 0.02449743, 0.02738778, 0.03024788, 0.05738761, 0.0822719,
0.10525907, 0.12658293, 0.1464181, 0.16490438, 0.18215844, 0.19828034,
0.21335753, 0.22746753, 0.24067983, 0.25305715, 0.26465659, 0.27553032,
0.25547838, 0.23790104, 0.22198642, 0.2074141, 0.19398549, 0.18155873,
0.17002455, 0.15929482, 0.14929611, 0.13996587, 0.13124986, 0.12310046,
0.11547534, 0.10833658, 0.10164995, 0.12563221, 0.14689894, 0.16627677,
0.18410003, 0.20058033, 0.21587175, 0.23009504, 0.2433491, 0.25571746,
0.26727216, 0.27807632, 0.28818593, 0.29765116, 0.30651729, 0.31482546,
0.29236538, 0.27252759, 0.25449115, 0.2379271, 0.22262886, 0.20844708,
0.19526545, 0.18298923, 0.1715388, 0.1608458, 0.15085055, 0.14150028,
0.13274787, 0.1245509, 0.11687089, 0.10967276, 0.10292438, 0.09659617,
0.09066084, 0.08509314, 0.07986962, 0.0749685, 0.07036946, 0.06605359,
0.06200322, 0.05820182, 0.05463397, 0.05128519, 0.04814195, 0.04519158,
0.04242218, 0.03982263, 0.03738247, 0.03509191, 0.03294176, 0.0309234,
0.02902874, 0.02725019, 0.02558063, 0.02401338, 0.02254216, 0.02116109,
0.01986464, 0.01864762, 0.01750516, 0.01643271, 0.01542596, 0.01448089,
0.01359372, 0.0127609, 0.01197911, 0.01124522, 0.01055628, 0.00990956,
0.00930246, 0.00873255
]])
z = np.array([
0., 0.11111111, 0.22222222, 0.33333333, 0.44444444, 0.55555556,
0.66666667, 0.77777778, 0.88888889, 1.
])
por = np.array([[0., 0., 0.], [10.62834433, 5.71540426, 0.79195768],
[18.10955225, 11.14818494, 1.55981113],
[23.22767635, 16.0566849, 2.2801995],
[26.62643019, 20.26892536, 2.93122316],
[28.80909111, 23.69187844, 3.49311208],
[30.15548187, 26.3014876, 3.94882356],
[30.93852215, 28.11965758, 4.28455203],
[31.33977648, 29.18687894, 4.49013755],
[31.4624026, 29.5381209, 4.55936353]])
# por = 100 * TERZ1D_POR
# avp = 100 * TERZ1D_AVP
settle = (np.interp(t, [0, 0.15, 0.3, 0.45, 4], [0.0, 50, 50, 100, 100]) -
avp)
H = 1
# z = np.linspace(0, H,40)
# t = np.linspace(0,1,100)
kv, kh, ks, kw = (10, 10, 10, 1e7)
mv = 1
gamw = 10
rw, rs, re = (0.03, 0.03, 0.5)
drn = 1
surcharge_vs_time = ((0, 0.15, 0.3, 0.45, 100.0), (0, 50, 50.0, 100.0,
100.0))
tpor = t[np.array([20, 60, 90])]
nterms = 20
por_, avp_, settle_ = tangandonitsuka2000(
z=z,
t=t,
kv=kv,
kh=kh,
ks=ks,
kw=kw,
mv=mv,
gamw=gamw,
rw=rw,
rs=rs,
re=re,
H=H,
drn=drn,
surcharge_vs_time=surcharge_vs_time,
tpor=tpor,
nterms=nterms)
# plt.figure()
# plt.plot(por, z,'b-*', label='expected')
# plt.plot(por_, z, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t,settle[0],'b-*', label='expected')
# plt.plot(t, settle_, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t, avp[0],'b-*', label='expected')
# plt.plot(t, avp_, 'r-+', label='calculated')
# plt.legend()
# plt.show()
assert_allclose(avp_,
avp[0],
atol=1e-3,
err_msg=("Fail. test_tang_and_onitsuka_one, avp, "))
assert_allclose(por_,
por,
atol=1e-2,
err_msg=("Fail. test_tang_and_onitsuka_one, por, "))
assert_allclose(settle_,
settle[0],
atol=1e-3,
err_msg=("Fail. test_tang_and_onitsuka_one, settle, "))
def test_tang_and_onitsuka_one():
"""tang_and_onitsuka_vert_and_radial
vertical and radial consolidation (no well resitance)
H=1
kv=kh=10, mv=1, gamw=10
dTv=kvref/mvref/gamw/H**2 = 1
#re=0.5, rw = 0.03, n = 16.6667, mu = 2.074475589, etref = 3.856396307
#dTh = 2*khref/mvref/gamw/mu = 3.856396307
"""
t = np.array([ 1.00000000e-03, 2.00000000e-03, 3.00000000e-03,
4.00000000e-03, 5.00000000e-03, 6.00000000e-03,
7.00000000e-03, 8.00000000e-03, 9.00000000e-03,
1.00000000e-02, 2.00000000e-02, 3.00000000e-02,
4.00000000e-02, 5.00000000e-02, 6.00000000e-02,
7.00000000e-02, 8.00000000e-02, 9.00000000e-02,
1.00000000e-01, 1.10000000e-01, 1.20000000e-01,
1.30000000e-01, 1.40000000e-01, 1.50000000e-01,
1.60000000e-01, 1.70000000e-01, 1.80000000e-01,
1.90000000e-01, 2.00000000e-01, 2.10000000e-01,
2.20000000e-01, 2.30000000e-01, 2.40000000e-01,
2.50000000e-01, 2.60000000e-01, 2.70000000e-01,
2.80000000e-01, 2.90000000e-01, 3.00000000e-01,
3.10000000e-01, 3.20000000e-01, 3.30000000e-01,
3.40000000e-01, 3.50000000e-01, 3.60000000e-01,
3.70000000e-01, 3.80000000e-01, 3.90000000e-01,
4.00000000e-01, 4.10000000e-01, 4.20000000e-01,
4.30000000e-01, 4.40000000e-01, 4.50000000e-01,
4.60000000e-01, 4.70000000e-01, 4.80000000e-01,
4.90000000e-01, 5.00000000e-01, 5.10000000e-01,
5.20000000e-01, 5.30000000e-01, 5.40000000e-01,
5.50000000e-01, 5.60000000e-01, 5.70000000e-01,
5.80000000e-01, 5.90000000e-01, 6.00000000e-01,
6.10000000e-01, 6.20000000e-01, 6.30000000e-01,
6.40000000e-01, 6.50000000e-01, 6.60000000e-01,
6.70000000e-01, 6.80000000e-01, 6.90000000e-01,
7.00000000e-01, 7.10000000e-01, 7.20000000e-01,
7.30000000e-01, 7.40000000e-01, 7.50000000e-01,
7.60000000e-01, 7.70000000e-01, 7.80000000e-01,
7.90000000e-01, 8.00000000e-01, 8.10000000e-01,
8.20000000e-01, 8.30000000e-01, 8.40000000e-01,
8.50000000e-01, 8.60000000e-01, 8.70000000e-01,
8.80000000e-01, 8.90000000e-01, 9.00000000e-01,
9.10000000e-01, 9.20000000e-01, 9.30000000e-01,
9.40000000e-01, 9.50000000e-01, 9.60000000e-01,
9.70000000e-01, 9.80000000e-01, 9.90000000e-01,
1.00000000e+00, 1.01000000e+00])
avp = 100*np.array([[ 0.00324696, 0.00641694, 0.00953238, 0.0126017 , 0.01562987,
0.01862029, 0.02157548, 0.02449743, 0.02738778, 0.03024788,
0.05738761, 0.0822719 , 0.10525907, 0.12658293, 0.1464181 ,
0.16490438, 0.18215844, 0.19828034, 0.21335753, 0.22746753,
0.24067983, 0.25305715, 0.26465659, 0.27553032, 0.25547838,
0.23790104, 0.22198642, 0.2074141 , 0.19398549, 0.18155873,
0.17002455, 0.15929482, 0.14929611, 0.13996587, 0.13124986,
0.12310046, 0.11547534, 0.10833658, 0.10164995, 0.12563221,
0.14689894, 0.16627677, 0.18410003, 0.20058033, 0.21587175,
0.23009504, 0.2433491 , 0.25571746, 0.26727216, 0.27807632,
0.28818593, 0.29765116, 0.30651729, 0.31482546, 0.29236538,
0.27252759, 0.25449115, 0.2379271 , 0.22262886, 0.20844708,
0.19526545, 0.18298923, 0.1715388 , 0.1608458 , 0.15085055,
0.14150028, 0.13274787, 0.1245509 , 0.11687089, 0.10967276,
0.10292438, 0.09659617, 0.09066084, 0.08509314, 0.07986962,
0.0749685 , 0.07036946, 0.06605359, 0.06200322, 0.05820182,
0.05463397, 0.05128519, 0.04814195, 0.04519158, 0.04242218,
0.03982263, 0.03738247, 0.03509191, 0.03294176, 0.0309234 ,
0.02902874, 0.02725019, 0.02558063, 0.02401338, 0.02254216,
0.02116109, 0.01986464, 0.01864762, 0.01750516, 0.01643271,
0.01542596, 0.01448089, 0.01359372, 0.0127609 , 0.01197911,
0.01124522, 0.01055628, 0.00990956, 0.00930246, 0.00873255]])
z = np.array(
[ 0. , 0.11111111, 0.22222222, 0.33333333, 0.44444444,
0.55555556, 0.66666667, 0.77777778, 0.88888889, 1. ])
por = np.array(
[[ 0. , 0. , 0. ],
[ 10.62834433, 5.71540426, 0.79195768],
[ 18.10955225, 11.14818494, 1.55981113],
[ 23.22767635, 16.0566849 , 2.2801995 ],
[ 26.62643019, 20.26892536, 2.93122316],
[ 28.80909111, 23.69187844, 3.49311208],
[ 30.15548187, 26.3014876 , 3.94882356],
[ 30.93852215, 28.11965758, 4.28455203],
[ 31.33977648, 29.18687894, 4.49013755],
[ 31.4624026 , 29.5381209 , 4.55936353]])
# por = 100 * TERZ1D_POR
# avp = 100 * TERZ1D_AVP
settle = (np.interp(t,[0,0.15,0.3,0.45,4], [0.0,50,50,100,100]) - avp)
H = 1
# z = np.linspace(0, H,40)
# t = np.linspace(0,1,100)
kv, kh, ks, kw = (10, 10, 10, 1e7)
mv=1
gamw = 10
rw, rs, re = (0.03, 0.03, 0.5)
drn = 1
surcharge_vs_time = ((0,0.15, 0.3, 0.45,100.0), (0,50,50.0,100.0,100.0))
tpor = t[np.array([20,60,90])]
nterms = 20
por_, avp_, settle_ = tangandonitsuka2000(z=z, t=t, kv=kv, kh=kh, ks=ks, kw=kw, mv=mv, gamw=gamw, rw=rw, rs=rs, re=re, H=H,
drn=drn, surcharge_vs_time=surcharge_vs_time,
tpor=tpor, nterms=nterms)
# plt.figure()
# plt.plot(por, z,'b-*', label='expected')
# plt.plot(por_, z, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t,settle[0],'b-*', label='expected')
# plt.plot(t, settle_, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t, avp[0],'b-*', label='expected')
# plt.plot(t, avp_, 'r-+', label='calculated')
# plt.legend()
# plt.show()
assert_allclose(avp_, avp[0], atol=1e-3,
err_msg = ("Fail. test_tang_and_onitsuka_one, avp, "
))
assert_allclose(por_, por, atol=1e-2,
err_msg = ("Fail. test_tang_and_onitsuka_one, por, "
))
assert_allclose(settle_, settle[0], atol=1e-3,
err_msg = ("Fail. test_tang_and_onitsuka_one, settle, "
))
def test_tang_and_onitsuka_well_resistance():
"""tang_and_onitsuka_vert_and_radial
vertical and radial consolidation (no well resitance)
H=1
kv=kh=10, ks=3,kh=1 mv=1, gamw=10
dTv=kvref/mvref/gamw/H**2 = 1
#re=0.5, rw = 0.03, rs = 0.06,n = 16.6667,
"""
t = np.array([
1.00000000e-03, 2.00000000e-03, 3.00000000e-03, 4.00000000e-03,
5.00000000e-03, 6.00000000e-03, 7.00000000e-03, 8.00000000e-03,
9.00000000e-03, 1.00000000e-02, 2.00000000e-02, 3.00000000e-02,
4.00000000e-02, 5.00000000e-02, 6.00000000e-02, 7.00000000e-02,
8.00000000e-02, 9.00000000e-02, 1.00000000e-01, 1.10000000e-01,
1.20000000e-01, 1.30000000e-01, 1.40000000e-01, 1.50000000e-01,
1.60000000e-01, 1.70000000e-01, 1.80000000e-01, 1.90000000e-01,
2.00000000e-01, 2.10000000e-01, 2.20000000e-01, 2.30000000e-01,
2.40000000e-01, 2.50000000e-01, 2.60000000e-01, 2.70000000e-01,
2.80000000e-01, 2.90000000e-01, 3.00000000e-01, 3.10000000e-01,
3.20000000e-01, 3.30000000e-01, 3.40000000e-01, 3.50000000e-01,
3.60000000e-01, 3.70000000e-01, 3.80000000e-01, 3.90000000e-01,
4.00000000e-01, 4.10000000e-01, 4.20000000e-01, 4.30000000e-01,
4.40000000e-01, 4.50000000e-01, 4.60000000e-01, 4.70000000e-01,
4.80000000e-01, 4.90000000e-01, 5.00000000e-01, 5.10000000e-01,
5.20000000e-01, 5.30000000e-01, 5.40000000e-01, 5.50000000e-01,
5.60000000e-01, 5.70000000e-01, 5.80000000e-01, 5.90000000e-01,
6.00000000e-01, 6.10000000e-01, 6.20000000e-01, 6.30000000e-01,
6.40000000e-01, 6.50000000e-01, 6.60000000e-01, 6.70000000e-01,
6.80000000e-01, 6.90000000e-01, 7.00000000e-01, 7.10000000e-01,
7.20000000e-01, 7.30000000e-01, 7.40000000e-01, 7.50000000e-01,
7.60000000e-01, 7.70000000e-01, 7.80000000e-01, 7.90000000e-01,
8.00000000e-01, 8.10000000e-01, 8.20000000e-01, 8.30000000e-01,
8.40000000e-01, 8.50000000e-01, 8.60000000e-01, 8.70000000e-01,
8.80000000e-01, 8.90000000e-01, 9.00000000e-01, 9.10000000e-01,
9.20000000e-01, 9.30000000e-01, 9.40000000e-01, 9.50000000e-01,
9.60000000e-01, 9.70000000e-01, 9.80000000e-01, 9.90000000e-01,
1.00000000e+00, 1.01000000e+00
])
avp = np.array([
0.3251192, 0.64395033, 0.95850562, 1.26960208, 1.57771263, 1.88315634,
2.18616747, 2.48692752, 2.78558251, 3.08225325, 5.95702443, 8.69654156,
11.32668082, 13.86239719, 16.31378114, 18.68824032, 20.99151433,
23.22822128, 25.40218266, 27.51663094, 29.57434975, 31.57777282,
33.5290564, 35.43013355, 34.20050254, 33.13150101, 32.15237963,
31.23863743, 30.37660731, 29.55741232, 28.77479436, 28.02410789,
27.30178016, 26.60499195, 25.93147455, 25.2793733, 24.64715174,
24.03352179, 23.43739162, 25.94007901, 28.25103876, 30.44179037,
32.5375838, 34.55281498, 36.49707039, 38.37729914, 40.19881996,
41.96586156, 43.68188255, 45.34977489, 46.97200093, 48.55068966,
50.08770698, 51.58470828, 49.96092538, 48.50743959, 47.15325433,
45.87362973, 44.65466744, 43.48726638, 42.36495094, 41.28286434,
40.23722852, 39.22502451, 38.24378923, 37.29147879, 36.36637241,
35.46700242, 34.592102, 33.74056512, 32.9114156, 32.10378279,
31.31688239, 30.55000117, 29.80248479, 29.07372803, 28.363167,
27.67027278, 26.99454634, 26.33551444, 25.69272626, 25.06575072,
24.4541742, 23.85759878, 23.27564071, 22.70792921, 22.15410538,
21.61382137, 21.08673968, 20.5725325, 20.07088118, 19.5814758,
19.10401475, 18.63820438, 18.18375868, 17.74039901, 17.30785384,
16.88585849, 16.47415495, 16.07249165, 15.68062329, 15.29831065,
14.92532042, 14.56142504, 14.20640258, 13.86003653, 13.5221157,
13.19243408, 12.87079071, 12.55698954
])
z = np.array([
0., 0.11111111, 0.22222222, 0.33333333, 0.44444444, 0.55555556,
0.66666667, 0.77777778, 0.88888889, 1.
])
por = np.array([[0., 0., 0.], [12.5344118, 12.14329704, 5.47538465],
[21.7012175, 23.75366578, 10.78420577],
[28.18367646, 34.36271994, 15.76501349],
[32.61240579, 43.61300476, 20.26641576],
[35.52623862, 51.27539117, 24.15169248],
[37.36067079, 57.23734656, 27.3029355],
[38.44529388, 61.47089897, 29.62459264],
[39.00780488, 63.99300166, 31.04631827],
[39.1808269, 64.82986319, 31.52505799]])
# por = 100 * TERZ1D_POR
# avp = 100 * TERZ1D_AVP
settle = np.array([
8.21413225e-03, 2.27163394e-02, 4.14943791e-02, 6.37312486e-02,
8.89540401e-02, 1.16843663e-01, 1.47165866e-01, 1.79739150e-01,
2.14417490e-01, 2.51080087e-01, 7.09642240e-01, 1.30345844e+00,
2.00665252e+00, 2.80426947e+00, 3.68621886e+00, 4.64509301e+00,
5.67515233e+00, 6.77177872e+00, 7.93115067e+00, 9.15003572e+00,
1.04256503e+01, 1.17555605e+01, 1.31376103e+01, 1.45698664e+01,
1.57994975e+01, 1.68684990e+01, 1.78476204e+01, 1.87613626e+01,
1.96233927e+01, 2.04425877e+01, 2.12252056e+01, 2.19758921e+01,
2.26982198e+01, 2.33950081e+01, 2.40685255e+01, 2.47206267e+01,
2.53528483e+01, 2.59664782e+01, 2.65626084e+01, 2.73932543e+01,
2.84156279e+01, 2.95582096e+01, 3.07957495e+01, 3.21138517e+01,
3.35029296e+01, 3.49560342e+01, 3.64678467e+01, 3.80341384e+01,
3.96514508e+01, 4.13168918e+01, 4.30279991e+01, 4.47826437e+01,
4.65789597e+01, 4.84152917e+01, 5.00390746e+01, 5.14925604e+01,
5.28467457e+01, 5.41263703e+01, 5.53453326e+01, 5.65127336e+01,
5.76350491e+01, 5.87171357e+01, 5.97627715e+01, 6.07749755e+01,
6.17562108e+01, 6.27085212e+01, 6.36336276e+01, 6.45329976e+01,
6.54078980e+01, 6.62594349e+01, 6.70885844e+01, 6.78962172e+01,
6.86831176e+01, 6.94499988e+01, 7.01975152e+01, 7.09262720e+01,
7.16368330e+01, 7.23297272e+01, 7.30054537e+01, 7.36644856e+01,
7.43072737e+01, 7.49342493e+01, 7.55458258e+01, 7.61424012e+01,
7.67243593e+01, 7.72920708e+01, 7.78458946e+01, 7.83861786e+01,
7.89132603e+01, 7.94274675e+01, 7.99291188e+01, 8.04185242e+01,
8.08959853e+01, 8.13617956e+01, 8.18162413e+01, 8.22596010e+01,
8.26921462e+01, 8.31141415e+01, 8.35258450e+01, 8.39275083e+01,
8.43193767e+01, 8.47016894e+01, 8.50746796e+01, 8.54385750e+01,
8.57935974e+01, 8.61399635e+01, 8.64778843e+01, 8.68075659e+01,
8.71292093e+01, 8.74430105e+01
])
H = 1
# z = np.linspace(0, H,40)
# t = np.linspace(0,1,100)
kv, kh, ks, kw = (10, 10, 3, 1)
mv = 1
gamw = 10
rw, rs, re = (0.03, 0.06, 0.5)
drn = 1
surcharge_vs_time = ((0, 0.15, 0.3, 0.45, 100.0), (0, 50, 50.0, 100.0,
100.0))
tpor = t[np.array([20, 60, 90])]
nterms = 20
por_, avp_, settle_ = tangandonitsuka2000(
z=z,
t=t,
kv=kv,
kh=kh,
ks=ks,
kw=kw,
mv=mv,
gamw=gamw,
rw=rw,
rs=rs,
re=re,
H=H,
drn=drn,
surcharge_vs_time=surcharge_vs_time,
tpor=tpor,
nterms=nterms)
# plt.figure()
# plt.plot(por, z,'b-*', label='expected')
# plt.plot(por_, z, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t,settle,'b-*', label='expected')
# plt.plot(t, settle_, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t, avp,'b-*', label='expected')
# plt.plot(t, avp_, 'r-+', label='calculated')
# plt.legend()
# plt.show()
assert_allclose(
avp_,
avp,
atol=1e-3,
err_msg=("Fail. test_tang_and_onitsuka_well_resistance, avp, "))
assert_allclose(
por_,
por,
atol=1e-2,
err_msg=("Fail. test_tang_and_onitsuka_well_resistance, por, "))
assert_allclose(
settle_,
settle,
atol=1e-3,
err_msg=("Fail. test_tang_and_onitsuka_well_resistance, settle, "))
def test_tang_and_onitsuka_well_resistance():
"""tang_and_onitsuka_vert_and_radial
vertical and radial consolidation (no well resitance)
H=1
kv=kh=10, ks=3,kh=1 mv=1, gamw=10
dTv=kvref/mvref/gamw/H**2 = 1
#re=0.5, rw = 0.03, rs = 0.06,n = 16.6667,
"""
t = np.array([ 1.00000000e-03, 2.00000000e-03, 3.00000000e-03,
4.00000000e-03, 5.00000000e-03, 6.00000000e-03,
7.00000000e-03, 8.00000000e-03, 9.00000000e-03,
1.00000000e-02, 2.00000000e-02, 3.00000000e-02,
4.00000000e-02, 5.00000000e-02, 6.00000000e-02,
7.00000000e-02, 8.00000000e-02, 9.00000000e-02,
1.00000000e-01, 1.10000000e-01, 1.20000000e-01,
1.30000000e-01, 1.40000000e-01, 1.50000000e-01,
1.60000000e-01, 1.70000000e-01, 1.80000000e-01,
1.90000000e-01, 2.00000000e-01, 2.10000000e-01,
2.20000000e-01, 2.30000000e-01, 2.40000000e-01,
2.50000000e-01, 2.60000000e-01, 2.70000000e-01,
2.80000000e-01, 2.90000000e-01, 3.00000000e-01,
3.10000000e-01, 3.20000000e-01, 3.30000000e-01,
3.40000000e-01, 3.50000000e-01, 3.60000000e-01,
3.70000000e-01, 3.80000000e-01, 3.90000000e-01,
4.00000000e-01, 4.10000000e-01, 4.20000000e-01,
4.30000000e-01, 4.40000000e-01, 4.50000000e-01,
4.60000000e-01, 4.70000000e-01, 4.80000000e-01,
4.90000000e-01, 5.00000000e-01, 5.10000000e-01,
5.20000000e-01, 5.30000000e-01, 5.40000000e-01,
5.50000000e-01, 5.60000000e-01, 5.70000000e-01,
5.80000000e-01, 5.90000000e-01, 6.00000000e-01,
6.10000000e-01, 6.20000000e-01, 6.30000000e-01,
6.40000000e-01, 6.50000000e-01, 6.60000000e-01,
6.70000000e-01, 6.80000000e-01, 6.90000000e-01,
7.00000000e-01, 7.10000000e-01, 7.20000000e-01,
7.30000000e-01, 7.40000000e-01, 7.50000000e-01,
7.60000000e-01, 7.70000000e-01, 7.80000000e-01,
7.90000000e-01, 8.00000000e-01, 8.10000000e-01,
8.20000000e-01, 8.30000000e-01, 8.40000000e-01,
8.50000000e-01, 8.60000000e-01, 8.70000000e-01,
8.80000000e-01, 8.90000000e-01, 9.00000000e-01,
9.10000000e-01, 9.20000000e-01, 9.30000000e-01,
9.40000000e-01, 9.50000000e-01, 9.60000000e-01,
9.70000000e-01, 9.80000000e-01, 9.90000000e-01,
1.00000000e+00, 1.01000000e+00])
avp = np.array(
[ 0.3251192 , 0.64395033, 0.95850562, 1.26960208,
1.57771263, 1.88315634, 2.18616747, 2.48692752,
2.78558251, 3.08225325, 5.95702443, 8.69654156,
11.32668082, 13.86239719, 16.31378114, 18.68824032,
20.99151433, 23.22822128, 25.40218266, 27.51663094,
29.57434975, 31.57777282, 33.5290564 , 35.43013355,
34.20050254, 33.13150101, 32.15237963, 31.23863743,
30.37660731, 29.55741232, 28.77479436, 28.02410789,
27.30178016, 26.60499195, 25.93147455, 25.2793733 ,
24.64715174, 24.03352179, 23.43739162, 25.94007901,
28.25103876, 30.44179037, 32.5375838 , 34.55281498,
36.49707039, 38.37729914, 40.19881996, 41.96586156,
43.68188255, 45.34977489, 46.97200093, 48.55068966,
50.08770698, 51.58470828, 49.96092538, 48.50743959,
47.15325433, 45.87362973, 44.65466744, 43.48726638,
42.36495094, 41.28286434, 40.23722852, 39.22502451,
38.24378923, 37.29147879, 36.36637241, 35.46700242,
34.592102 , 33.74056512, 32.9114156 , 32.10378279,
31.31688239, 30.55000117, 29.80248479, 29.07372803,
28.363167 , 27.67027278, 26.99454634, 26.33551444,
25.69272626, 25.06575072, 24.4541742 , 23.85759878,
23.27564071, 22.70792921, 22.15410538, 21.61382137,
21.08673968, 20.5725325 , 20.07088118, 19.5814758 ,
19.10401475, 18.63820438, 18.18375868, 17.74039901,
17.30785384, 16.88585849, 16.47415495, 16.07249165,
15.68062329, 15.29831065, 14.92532042, 14.56142504,
14.20640258, 13.86003653, 13.5221157 , 13.19243408,
12.87079071, 12.55698954])
z = np.array(
[ 0. , 0.11111111, 0.22222222, 0.33333333, 0.44444444,
0.55555556, 0.66666667, 0.77777778, 0.88888889, 1. ])
por = np.array(
[[ 0. , 0. , 0. ],
[ 12.5344118 , 12.14329704, 5.47538465],
[ 21.7012175 , 23.75366578, 10.78420577],
[ 28.18367646, 34.36271994, 15.76501349],
[ 32.61240579, 43.61300476, 20.26641576],
[ 35.52623862, 51.27539117, 24.15169248],
[ 37.36067079, 57.23734656, 27.3029355 ],
[ 38.44529388, 61.47089897, 29.62459264],
[ 39.00780488, 63.99300166, 31.04631827],
[ 39.1808269 , 64.82986319, 31.52505799]])
# por = 100 * TERZ1D_POR
# avp = 100 * TERZ1D_AVP
settle = np.array(
[ 8.21413225e-03, 2.27163394e-02, 4.14943791e-02,
6.37312486e-02, 8.89540401e-02, 1.16843663e-01,
1.47165866e-01, 1.79739150e-01, 2.14417490e-01,
2.51080087e-01, 7.09642240e-01, 1.30345844e+00,
2.00665252e+00, 2.80426947e+00, 3.68621886e+00,
4.64509301e+00, 5.67515233e+00, 6.77177872e+00,
7.93115067e+00, 9.15003572e+00, 1.04256503e+01,
1.17555605e+01, 1.31376103e+01, 1.45698664e+01,
1.57994975e+01, 1.68684990e+01, 1.78476204e+01,
1.87613626e+01, 1.96233927e+01, 2.04425877e+01,
2.12252056e+01, 2.19758921e+01, 2.26982198e+01,
2.33950081e+01, 2.40685255e+01, 2.47206267e+01,
2.53528483e+01, 2.59664782e+01, 2.65626084e+01,
2.73932543e+01, 2.84156279e+01, 2.95582096e+01,
3.07957495e+01, 3.21138517e+01, 3.35029296e+01,
3.49560342e+01, 3.64678467e+01, 3.80341384e+01,
3.96514508e+01, 4.13168918e+01, 4.30279991e+01,
4.47826437e+01, 4.65789597e+01, 4.84152917e+01,
5.00390746e+01, 5.14925604e+01, 5.28467457e+01,
5.41263703e+01, 5.53453326e+01, 5.65127336e+01,
5.76350491e+01, 5.87171357e+01, 5.97627715e+01,
6.07749755e+01, 6.17562108e+01, 6.27085212e+01,
6.36336276e+01, 6.45329976e+01, 6.54078980e+01,
6.62594349e+01, 6.70885844e+01, 6.78962172e+01,
6.86831176e+01, 6.94499988e+01, 7.01975152e+01,
7.09262720e+01, 7.16368330e+01, 7.23297272e+01,
7.30054537e+01, 7.36644856e+01, 7.43072737e+01,
7.49342493e+01, 7.55458258e+01, 7.61424012e+01,
7.67243593e+01, 7.72920708e+01, 7.78458946e+01,
7.83861786e+01, 7.89132603e+01, 7.94274675e+01,
7.99291188e+01, 8.04185242e+01, 8.08959853e+01,
8.13617956e+01, 8.18162413e+01, 8.22596010e+01,
8.26921462e+01, 8.31141415e+01, 8.35258450e+01,
8.39275083e+01, 8.43193767e+01, 8.47016894e+01,
8.50746796e+01, 8.54385750e+01, 8.57935974e+01,
8.61399635e+01, 8.64778843e+01, 8.68075659e+01,
8.71292093e+01, 8.74430105e+01])
H = 1
# z = np.linspace(0, H,40)
# t = np.linspace(0,1,100)
kv, kh, ks, kw = (10, 10, 3, 1)
mv=1
gamw = 10
rw, rs, re = (0.03, 0.06, 0.5)
drn = 1
surcharge_vs_time = ((0,0.15, 0.3, 0.45,100.0), (0,50,50.0,100.0,100.0))
tpor = t[np.array([20,60,90])]
nterms = 20
por_, avp_, settle_ = tangandonitsuka2000(z=z, t=t, kv=kv, kh=kh, ks=ks, kw=kw, mv=mv, gamw=gamw, rw=rw, rs=rs, re=re, H=H,
drn=drn, surcharge_vs_time=surcharge_vs_time,
tpor=tpor, nterms=nterms)
# plt.figure()
# plt.plot(por, z,'b-*', label='expected')
# plt.plot(por_, z, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t,settle,'b-*', label='expected')
# plt.plot(t, settle_, 'r-+', label='calculated')
# plt.legend()
#
# plt.figure()
# plt.plot(t, avp,'b-*', label='expected')
# plt.plot(t, avp_, 'r-+', label='calculated')
# plt.legend()
# plt.show()
assert_allclose(avp_, avp, atol=1e-3,
err_msg = ("Fail. test_tang_and_onitsuka_well_resistance, avp, "
))
assert_allclose(por_, por, atol=1e-2,
err_msg = ("Fail. test_tang_and_onitsuka_well_resistance, por, "
))
assert_allclose(settle_, settle, atol=1e-3,
err_msg = ("Fail. test_tang_and_onitsuka_well_resistance, settle, "
))
