def test_positive_friction(self):
chamfered_qc = bearing.chamfer_positive_friction(
self.gef.df.qc.values, self.gef.df.depth.values)
# pile tip level
ptl = nap_to_depth(self.gef.zid, -13.5)
tipping_point = nap_to_depth(self.gef.zid, -2.1)
idx_ptl = np.argmin(np.abs(self.gef.df.depth.values - ptl))
idx_tp = np.argmin(np.abs(self.gef.df.depth.values - tipping_point))
s = slice(idx_tp, idx_ptl)
f = bearing.positive_friction(self.gef.df.depth.values[s],
chamfered_qc[s], 0.25 * 4, 0.01)
# d-foundation result is 1375, we have 1371. Small difference due to chamfering method. We chamfer better ;)
deviation = abs(1 - 1375 / (f.sum() * 1000))
self.assertTrue(deviation < 1e-2)
self.assertEqual(f.sum(), 1.3710468170000003)
if SHOW_PLOTS:
# show chamfer line
fig = self.gef.plot(show=False)
fig.axes[0].plot(chamfered_qc[s],
self.gef.df.depth[s],
color="red")
fig.axes[0].hlines(ptl, 0, chamfered_qc.max())
fig.axes[0].hlines(tipping_point, 0, chamfered_qc.max())
plt.show()
def test_pile_tip_resistance(self):
f = partial(
bearing.compute_pile_tip_resistance,
qc=self.gef.df.qc.values,
depth=self.gef.df.depth.values,
d_eq=1.13 * 0.25,
alpha=0.7,
beta=1,
s=1,
area=0.25**2,
return_q_components=True,
)
rb, qc_1, qc_2, qc_3 = f(nap_to_depth(self.gef.zid, -3.5))
self.assertAlmostEqual(rb, 0.2575636376096491)
self.assertAlmostEqual(qc_1, 10.33309298245614)
self.assertAlmostEqual(qc_2, 5.92369298245614)
self.assertAlmostEqual(qc_3, 3.645944736842105)
rb, qc_1, qc_2, qc_3 = f(nap_to_depth(self.gef.zid, -12))
self.assertAlmostEqual(rb, 0.9375)
self.assertAlmostEqual(qc_1, 27.906636363636366)
self.assertAlmostEqual(qc_2, 21.714000000000002)
self.assertAlmostEqual(qc_3, 21.2664298245614)
def estimate_water_pressure(cpt, soil_properties=None):
"""
Estimate water pressure. If u2 is in CPT measurements, it is returned.
Otherwise it computes a water pressure by assuming a rising pressure over depth.
Parameters
----------
cpt : pygef.ParseCPT
soil_properties : pd.DataFrame
Merged soil properties w/ pygef.ParseCPT.
Returns
-------
u2 : np.array[float]
Water pressure over depth.
"""
if soil_properties is None:
soil_properties = cpt.df
if "u2" in cpt.df.columns:
u2 = soil_properties.u2.values
elif cpt.groundwater_level is not None:
water_depth = nap_to_depth(cpt.zid, cpt.groundwater_level)
u2 = (soil_properties.depth - water_depth) * WATER_PRESSURE
u2[u2 < 0] = 0
else:
u2 = soil_properties.depth * WATER_PRESSURE
return u2
def estimate_water_pressure(cpt, soil_properties=None):
"""
Estimate water pressure. If u is in CPT measurements, it is returned.
Otherwise it computes a water pressure by assuming a rising pressure over depth.
Parameters
----------
cpt : pygef.ParseCPT
soil_properties : pd.DataFrame
Merged soil properties w/ pygef.ParseCPT.
Returns
-------
u : np.array[float]
Water pressure over depth.
"""
if soil_properties is None:
soil_properties = cpt.df
if "u" in cpt.df.columns:
u = soil_properties.u.values
elif cpt.groundwater_level is not None:
water_depth = nap_to_depth(cpt.zid, cpt.groundwater_level)
u = (soil_properties.depth - water_depth) * WATER_PRESSURE
u[u < 0] = 0
else:
u = soil_properties.depth * WATER_PRESSURE
warnings.warn(
"Water level not available in CPT. anaPile set the water level implicitly"
)
return u
def test_find_last_sand_layer(self):
df = soil.join_cpt_with_classification(self.gef, self.layer_table)
ptl = nap_to_depth(self.gef.zid, -13.5)
idx_ptl = np.argmin(np.abs(self.gef.df.depth.values - ptl))
self.assertTrue(
soil.find_last_negative_friction_tipping_point(
df.depth.values[:idx_ptl], df.soil_code[:idx_ptl]),
3.848,
)
def _set_ptl(self, pile_tip_level):
"""
Set pile tip level property.
Parameters
----------
pile_tip_level : float
Depth value wrt NAP.
Returns
-------
None
"""
self.pile_tip_level = nap_to_depth(self.cpt.zid, pile_tip_level)
# find the index of the pile tip
self._idx_ptl = np.argmin(
np.abs(self.cpt.df.depth.values - self.pile_tip_level))
def test_negative_friction(self):
layer_table = pd.read_csv("files/d_foundation_layer_table.csv")
self.gef.groundwater_level = 1
df = soil.join_cpt_with_classification(self.gef, layer_table)
tipping_point = nap_to_depth(self.gef.zid, -2.1)
idx_tp = np.argmin(np.abs(self.gef.df.depth.values - tipping_point))
s = slice(0, idx_tp - 1)
if SHOW_PLOTS:
# show chamfer line
fig = self.gef.plot(show=False)
fig.axes[0].plot(df.qc.values[s], df.depth.values[s], color="red")
fig.axes[0].hlines(tipping_point, 0, df.qc.values[s].max())
plt.show()
f = bearing.negative_friction(df.depth.values[s],
df.grain_pressure.values[s], 0.25 * 4,
df.phi.values[s])
deviation = abs(1 - 19.355 / (f.sum() * 1000))
self.assertTrue(deviation < 1e-2)
from anapile.geo import soil
import pandas as pd
import numpy as np
# read cpt and layers
gef = ParseGEF("../tests/files/example.gef")
layer_table = pd.read_csv("../tests/files/layer_table.csv")
# we know the groundwater level is 1 m NAP
gef.groundwater_level = 1
# backfill cpt values with soil parameters
df = soil.join_cpt_with_classification(gef, layer_table)
# pile tip level -13.5 m
ptl = nap_to_depth(gef.zid, -13.5)
pile_width = 0.25
circum = pile_width * 4
# find the index of the pile tip
idx_ptl = np.argmin(np.abs(gef.df.depth.values - ptl))
ptl_slice = slice(0, idx_ptl)
# assume the tipping point is on top of the sand layers.
tipping_point = soil.find_last_negative_friction_tipping_point(
df.depth.values[ptl_slice], df.soil_code[ptl_slice])
idx_tp = np.argmin(np.abs(df.depth.values - tipping_point))
negative_friction_slice = slice(0, idx_tp)
negative_friction = (bearing.negative_friction(