def setup_and_run_fdm(gridpar, k, rch, axis=1):
Lx, wx, Ly, wy, D, d = gridpar
x = np.linspace(-Lx, Lx, int(2 * Lx / wx) + 1)
y = np.linspace(-Ly, Ly, int(2 * Ly / wy) + 1)
z = np.linspace(-D, D, int(2 * D / d) + 1)
gr = mfgrid.Grid(x, y, z)
K = gr.const(k)
FH = gr.const(0.)
FQ = gr.Volume * rch
IBOUND = gr.const(1)
if axis == 0:
IBOUND[[0, -1], :, :] = -1
elif axis == 1:
IBOUND[:, [0, -1], :] = -1
elif axis == 2:
IBOUND[:, :, [0, -1]] = -1
else:
print("axis must be 0, 1, or 2, not {}".format(axis))
# Solve for the heads:
Out = fdm.fdm3(gr, (K, K, K), FQ, FH, IBOUND)
return Out, gr, IBOUND
def setup_and_run_fdm(gridpar, k, Q):
Lx, wx, Ly, wy, D, d = gridpar
x = np.linspace(-Lx, Lx, int(2 * Lx / wx) + 1)
y = np.linspace(-Ly, Ly, int(2 * Ly / wy) + 1)
z = np.linspace(-D, D, int(2 * D / d) + 1)
gr = mfgrid.Grid(x, y, z)
K = gr.const(k) # * np.random.rand(gr.Nod).reshape(gr.shape)
FH = gr.const(0.)
FQ = gr.const(0.)
IBOUND = gr.const(1)
IBOUND[[0, -1], :, :] = -1
IBOUND[:, [0, -1], :] = -1
IBOUND[:, :, [0, -1]] = -1
icx, icy, icz = gr.ixyz(0., 0., 0.)
FQ[icy, icx, icz] = Q
# Solve for the heads:
Out = fdm.fdm3(gr, (K, K, K), FQ, FH, IBOUND)
return Out, gr, IBOUND
def set_up_and_run_fdm(gridpar, k, hbound, axis=None):
Lx, wx, Ly, wy, D, d = gridpar
x = np.linspace(-Lx, Lx, int(2 * Lx / wx) + 1)
y = np.linspace(-Ly, Ly, int(2 * Ly / wy) + 1)
z = np.linspace(-D , D, int(2 * D / d) + 1)
gr = mfgrid.Grid(x, y, z)
K = gr.const(k) # * np.random.rand(gr.Nod).reshape(gr.shape)
FH = gr.const(0.)
FQ = gr.const(0.)
IBOUND = gr.const(1)
if axis == 0:
IBOUND[[0, -1], :, :] = -1
FH[0, :, :] = hbound[0]
FH[-1, :,:] = hbound[1]
elif axis == 1:
IBOUND[:,[0, -1], :] = -1
FH[:, 0, :] = hbound[0]
FH[:, -1, :] = hbound[1]
elif axis == 2:
IBOUND[:, :, [0, -1]] = -1
FH[:, :, 0] = hbound[0]
FH[:, :, -1] = hbound[1]
else:
print("axis must be 0, 1, or to, not {}".format(axis))
raise ValueError()
# Solve for the heads:
Out = fdm.fdm3(gr, (K, K, K), FQ, FH, IBOUND)
return Out, gr, IBOUND
def example_De_Glee():
"""Axial symmetric example, well in semi-confined aquifer (De Glee case)
De Glee was a Dutch engineer/groundwater hydrologist and later the
first director of the water company of the province of Groningen.
His PhD (1930) solved the axial symmetric steady state flow to a well
in a semi confined aquifer using the Besselfunctions of the second kind,
known as K0 and K1.
The example computes the heads in the regional aquifer below a semi confining
layer with a fixed head above. It uses two model layers a confining one in
which the heads are fixed and a semi-confined aquifer with a prescribed
extraction at r=r0. If r0>>0, both K0 and K1 Bessel functions are needed.
The grid is signaled to use inteprete the grid as axially symmetric.
"""
K0 = lambda x: scipy.special.kn(0, x
) # Bessel function second kind, order 0
K1 = lambda x: scipy.special.kn(1, x
) # Bessel function second kind, order 1
Q = -1200.0 # m3/d, well extraction
r0 = 100. # m, well radius
R = 2500. # m, outer radius of model
d = 10. # m, thickness of confining top layer
D = 50. # m, thickness of regional aquifer
c = 250 # d, vertical resistance of confining top layer
k1 = d / c # m/d conductivity of confining top layer
k2 = 10. # m/d conductivity of regional aquifer
kD = k2 * D # m2/d, transmissivity of regional aquifer
lam = np.sqrt(kD * c) # spreading length of regional aquifer
r = np.hstack((r0 + 0.001, np.logspace(np.log10(r0), np.log10(R),
41))) # distance to well center
y = None # dummy, ignored because problem is axially symmetric
z = np.array([0, -d,
-d - D]) # m, elevation of tops and bottoms of model layers
gr = mfgrid.Grid(r, y, z, axial=True) # generate grid
FQ = gr.const(0.)
FQ[-1, 0, 0] = Q # m3/d fixed flows
IH = gr.const(0.) # m, initial heads
IBOUND = gr.const(1)
IBOUND[0, :, :] = -1 # modflow like boundary array
K = gr.const([k1 / 2., k2]) # full 3D array of conductivities
Out = fdm3(gr, K, FQ, IH, IBOUND) # run model
plt.figure()
plt.setp(plt.gca(), 'xlabel', 'r [m]', 'ylabel', 'head [m]',\
'title', 'De Glee, well extraction, axially symmetric', 'xscale', 'log', 'xlim', [1.0, R])
plt.plot(gr.xm, Out.Phi[-1, 0, :], 'ro-', label='fdm3')
plt.plot(gr.x,
Q / (2 * np.pi * kD) * K0(gr.x / lam) / (r0 / lam * K1(r0 / lam)),
'bx-',
label='analytic')
plt.legend()
def set_up_and_run_fdm(gridpar, k, Q, well_axis):
Lx, wx, Ly, wy, D, d = gridpar
x = np.linspace(-Lx, Lx, int(2 * Lx / wx) + 1)
y = np.linspace(-Ly, Ly, int(2 * Ly / wy) + 1)
z = np.linspace(-D , D, int(2 * D / d) + 1)
gr = mfgrid.Grid(x, y, z)
K = gr.const(k) # * np.random.rand(gr.Nod).reshape(gr.shape)
FH = gr.const(0.)
FQ = gr.const(0.)
# Cell indices of center of model: hard wired here
x0, y0, z0 = 0., 0., 0.
icx, icy, icz = gr.ixyz(x0, y0, z0)
# Covner to int to prevent shape errors with FQ below
icx = int(icx); icy=int(icy); icz=int(icz)
if well_axis == 2: # i.e. z
# screen in z direction, flow in xy plane
IBOUND = gr.const(1)
IBOUND[[0,-1], :, :] = -1
IBOUND[:, [0,-1], :] = -1
FQ[icy, icx, :] = Q * gr.dz / np.sum(gr.dz)
elif well_axis == 0: # i.e. y
# screen in x direction, flow in zx plane
IBOUND = gr.const(1)
IBOUND[:, [0,-1], :] = -1
IBOUND[:, :, [0,-1]] = -1
FQ[:, icx, icz] = Q * gr.dy / np.sum(gr.dy)
elif well_axis == 1: # i.e. x
# screen in y direction, flow in yz plane
IBOUND = gr.const(1)
IBOUND[[0,-1], :, :] = -1
IBOUND[:, :, [0,-1]] = -1
FQ[icy, :, icz] = Q * gr.dx / np.sum(gr.dx)
else:
print("well_axis must be 0, 1, or 2, not {}".format(well_axis))
# Solve for the heads:
Out = fdm.fdm3(gr, (K, K, K), FQ, FH, IBOUND)
return Out, gr, IBOUND
def example_mazure():
"""1D flow in semi-confined aquifer example
Mazure was Dutch professor in the 1930s, concerned with leakage from
polders that were pumped dry. His situation is a cross section perpendicular
to the dike of a regional aquifer covered by a semi-confining layer with
a maintained head in it. The head in the regional aquifer at the dike was
given as well. The head obeys the following analytical expression
phi(x) - hp = (phi(0)-hp) * exp(-x/lam), lam = sqrt(kDc)
To compute we use 2 model layers and define the values such that we obtain
the Mazure result.
"""
x = np.hstack((0.001, np.linspace(0., 2000., 101))) # column coordinates
y = np.array([-0.5, 0.5]) # m, model is 1 m thick
d = 10. # m, thickness of confining top layer
D = 50. # m, thickness of regional aquifer
z = np.array([0, -d, -d - D]) # tops and bottoms of layers
gr = mfgrid.Grid(x, y, z, axial=False)
c = 250 # d, vertical resistance of semi-confining layer
k1 = d / c # m/d conductivity of the top layer
k2 = 10. # m/d conductivity of the regional aquifer
kD = k2 * D # m2/d, transmissivity of regional aquifer
K = gr.const([k1 / 2.,
k2]) # k1 = 0.5 d/c because conductance from layer center
FQ = gr.const(0) # prescribed flows
s0 = 2.0 # head in aquifer at x=0
IH = gr.const(0)
IH[:, 0, -1] = s0 # prescribed heads
IBOUND = gr.const(1)
IBOUND[:, :, 0] = -1
IBOUND[:, 0, -1] = -1
out = fdm.fdm3(gr, K, FQ, IH, IBOUND) # compute heads, run model
numerical = out.Phi[0, :, -1]
analytic = vanMarzure(s0, kD, c, gr.xm)
#==============================================================================
# plt.figure()
# plt.setp(plt.gca(), 'xlabel','x [m]', 'ylabel', 'head [m]', 'title', 'Mazure 1D flow')
# plt.plot(gr.xm, numerical, 'ro-', label='fdm3') # numeric solution
# plt.plot(gr.xm, analytic ,'bx-', label='analytic') # analytic solution
# plt.legend()
#
#==============================================================================
return numerical, analytic, out
def setupAndRunFDM_model(gridpar, k, hbound):
Lx, wx, Ly, wy, D, d = gridpar
hW, hE, hN, hS, hT, hB = hbound
x = np.linspace(-Lx, Lx, int(2 * Lx / wx) + 1)
y = np.linspace(-Ly, Ly, int(2 * Ly / wy) + 1)
z = np.linspace(0, -D, int(D / d) + 1)
gr = mfgrid.Grid(x, y, z)
K = gr.const(k) # * np.random.rand(gr.Nod).reshape(gr.shape)
FH = gr.const(0.)
FQ = gr.const(0.)
IBOUND = gr.const(1)
if not (hW is None):
IBOUND[:, 0, :] = -1
FH[:, 0, :] = hW
if not hE is None:
IBOUND[:, -1, :] = -1
FH[:, -1, :] = hE
if not hN is None:
IBOUND[0, :, :] = -1
FH[0, :, :] = hN
if not hS is None:
IBOUND[-1, :, :] = -1
FH[-1, :, :] = hS
if not hT is None:
IBOUND[:, :, 0] = -1
FH[:, :, 0] = hT
if not hB is None:
IBOUND[:, :, -1] = -1
FH[:, :, -1] = hB
# Solve for the heads:
Out = fdm.fdm3(gr, (K, K, K), FQ, FH, IBOUND)
return Out, gr, IBOUND
def normGrid(gr):
up = np.arange(0., gr.Nx + 1)
vp = np.arange(0., gr.Ny + 1)
wp = np.arange(0., gr.Nz + 1)
return mfgrid.Grid(up, vp, wp)
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 14 18:03:45 2016
@author: Theo
"""
#from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
import numpy as np
import mfgrid
fig = plt.figure()
ax1 = fig.add_subplot(111, projection='3d')
Np = 11
x = np.arange(Np, dtype=float)
y = np.arange(Np, dtype=float)
z = np.arange(Np, dtype=float)
gr = mfgrid.Grid(x, y, z)
gr.plot_grid3d('gbr', alpha=0.5)
plt.show()
def setUp(self):
global gr, grn, tol, xTest, yTest,\
xp, yp, zp, xpm, ypm, zpm,\
up, vp, wp, upm, vpm, wpm,\
U, iu, V, iv, W, iw, mustSkip
mustSkip = False
tol = 1e-5
digits = int(abs(np.log10(tol)))
x = np.array(
[0, 6, 3.000001, -2, -1e-6, 3e-6, 4.00001, 7, 8, 11, -3, -4])
y = x[:]
xTest = np.unique(np.round(x, digits))
yTest = xTest[::-1]
Nx = len(np.unique(np.round(np.array(x), digits))) - 1
Ny = len(np.unique(np.round(np.array(y), digits))) - 1
# Generate a full fledged Z array with different Z in ever iy,ix
# combination
z = np.arange(5) * -10
Z = np.ones((Ny, Nx, 1)) * z.reshape((1, 1, len(z)))
Z = Z * (np.random.rand(len(z)) + 0.5).reshape((1, 1, len(z)))
min_dz = 0.1
gr = mfgrid.Grid(x, y, Z, min_dz=min_dz, tol=tol)
Nz = gr.Nz
grn = gr.norm_grid()
Lam = lambda a, b: np.hstack((np.array(a), np.array(b)))
"""
# Generate trial points that include all special cases like
# points outside the model, points at grid lines and points
# at the boundary edges of the model, next to ordinary
# points falling within model cells.
"""
# outside and inside the model
up = np.array([])
vp = np.array([])
wp = np.array([])
up = Lam(up, -0.5 + np.array([0., 1., 0., 0., 1., 1., 0., 1.]))
vp = Lam(vp, -0.5 + np.array([0., 0., 1., 0., 1., 0., 1., 1.]))
wp = Lam(wp, -0.5 + np.array([0., 0., 0., 1., 0., 1., 1., 1.]))
up = Lam(up, Nx - 0.5 + np.array([0., 1., 0., 0., 1., 1., 0., 1.]))
vp = Lam(vp, Ny - 0.5 + np.array([0., 0., 1., 0., 1., 0., 1., 1.]))
wp = Lam(wp, Nz - 0.5 + np.array([0., 0., 0., 1., 0., 1., 1., 1.]))
# points on grid lines, including all corner cases
up = Lam(up, [0., 1., 0., 0., 1., 1., 0., 1.])
vp = Lam(vp, [0., 0., 1., 0., 1., 0., 1., 1.])
wp = Lam(wp, [0., 0., 0., 1., 0., 1., 1., 1.])
up = Lam(up, Nx - np.array([0., 1., 0., 0., 1., 1., 0., 1.]))
vp = Lam(vp, Ny - np.array([0., 0., 1., 0., 1., 0., 1., 1.]))
wp = Lam(wp, Nz - np.array([0., 0., 0., 1., 0., 1., 1., 1.]))
# not at grid lines, i.e. ordinary points
up = Lam(up,
np.pi / 10. * Nx + np.array([0., 1., 0., 0., 1., 1., 0., 1.]))
vp = Lam(vp,
np.pi / 10. * Ny + np.array([0., 0., 1., 0., 1., 0., 1., 1.]))
wp = Lam(wp,
np.pi / 10. * Nz + np.array([0., 0., 0., 1., 0., 1., 1., 1.]))
# convert these ponts to grid coordinates
xp, yp, zp = gr.uvw2xyz(up, vp, wp)
# verify by showing the location of these points in the two grids
U, iu = gr.U(xp)
V, iv = gr.V(yp)
W, iw = gr.W(xp, yp, zp)
up = gr.up(xp)
vp = gr.vp(yp)
wp = gr.wp(xp, yp, zp)
import numpy as np import matplotlib.pylab as plt import mfgrid import fdm import mfpath import pdb axial = False Q = -2400 if axial else -240. # m3/d if axial else m2/ por = 0.35 # [-], effective porosity xGr = np.logspace(-1, 4, 51) xGr = np.linspace(0, 2000, 101) yGr = np.array([-0.5, 0.5]) zGr = np.array([0., -5, -50, -60, -100]) gr = mfgrid.Grid(xGr, yGr, zGr, axial) IBOUND = gr.const(1) IBOUND[:, :, 0] = -1 # head in top confining unit fixed k = gr.const(np.array([0.01, 10., 0.01, 20.])) FH = gr.const(0.) FQ = gr.const(0.) FQ[0, 0, 1] = Q # insecond layer # run flow model Out = fdm.fdm3(gr, (k, k, k), FQ, FH, IBOUND) Psi = fdm.psi(Out.Qx) #pdb.set_trace()