Computational Seismology
Finite Element Method - Static Elasticity This notebook is part of the supplementary material to Computational Seismology: A Practical Introduction, Oxford University Press, 2016.

## Basic Equations¶

Static elasticity can be considered a particular case derived from the elastic wave equation when the displacement does not depend on time, i.e $\partial_t^2 u(x,t) = 0$. Under this assumption and departing from the 1D elastic wave equation, the differential equation turns into the Poisson equation

\begin{equation} -\mu \partial_x^2 u = f, \end{equation}

where $\mu$ is the shear modulus for a homogeneous media, $u$ is the displacement field, and $f$ is the external force. The solution for this problems is found after bringing this equation into its weak form, applying the free boundary condition, and using the Galerkin principle with a suitable basis. Then, the displacement defined in a discrete set of points $x_i$ is given as the solution of a system of N equations, with

\begin{equation} \mathbf{u} = (\mathbf{K}^{T})^{-1} \mathbf{f} \end{equation}

where $\mathbf{K}$ is the stiffness matrix. For an elastic physical system with constant shear modulus $\mu$ and uniform element size $h$, it is given as

\begin{equation} K_{ij} = \frac{\mu}{h} \begin{pmatrix} 1 & -1 & & & \\ -1 & 2 & -1 & & \\ & & \ddots & & \\ & & -1 & 2 & -1 \\ & & & -1 & 1 \end{pmatrix} \end{equation}

The purpose of this notebook is to illustrate how the problem of static elasticity is solved with the finite- element method. We also compare the solution using finite - differences, the so-called relaxation method given by (derivation in the book):

\begin{equation} u_{i}^{k+1} = \dfrac{u_{i}^{k+1} + u_{i}^{k+1}}{2} + \dfrac{h^2}{2 \mu}f_i \end{equation}
In :
# Import all necessary libraries, this is a configuration step for the exercise.
# Please run it before the simulation code!
import numpy as np
import matplotlib
# Show Plot in The Notebook
matplotlib.use("nbagg")
import matplotlib.pyplot as plt


### Finite - Element solution¶

In :
# ---------------------------------------------------------------
# Initialization of setup
# ---------------------------------------------------------------
nx = 20              # Number of boundary points
u  = np.zeros(nx)    # Solution vector
f  = np.zeros(nx)    # Source vector
mu = 1               # Constant shear modulus

# Element boundary points
x = np.linspace(0, 1, nx)  # x in [0,1]
h = x - x            # Constant element size

# ---------------------------------------------------------------
# Assemble stiffness matrix K_ij (Eq 6.30)
# ---------------------------------------------------------------
K = np.zeros((nx, nx))
for i in range(1, nx-1):
for j in range(1, nx-1):
if i == j:
K[i, j] = 2*mu/h
elif i == j + 1:
K[i, j] = -mu/h
elif i + 1 == j:
K[i, j] = -mu/h
else:
K[i, j] = 0

# ---------------------------------------------------------------
# Souce term is a spike at i = 3*nx/4
f[int(3*nx/4)] = 1

# Boundary condition at x = 0
u = 0.15 ; f = u/h

# Boundary condition at x = 1
u[nx-1] = 0.05 ; f[nx-2] = u[nx-1]/h

# ---------------------------------------------------------------
# Finite element solution. (Eq 6.19)
# ---------------------------------------------------------------
u[1:nx-1] = np.linalg.inv(K[1:nx-1, 1:nx-1]) @ np.transpose(f[1:nx-1])

# ---------------------------------------------------------------
# Plotting section
# ---------------------------------------------------------------
xfe = u
plt.plot(x, xfe, color='r', lw=2, label='Finite elements')
plt.title('Static Elasticity', size=16)
plt.ylabel('Displacement $u(x)$', size=16)
plt.xlabel('Position $x$', size=16)
plt.axis([0, 1, 0.04, .28])
plt.legend()
plt.grid(True)
plt.show()


### Finite - Difference solution¶

In :
# Poisson's equation with relaxation method
# ---------------------------------------------------------------
nt = 500     # Number of time steps
iplot = 20   # Snapshot frequency

# non-zero boundary conditions
u  = np.zeros(nx)   # set u to zero
du = np.zeros(nx)   # du/dx
f  = np.zeros(nx)   # forcing

f[int(3*nx/4)] = 1./h

xfd = np.arange(0, nx)*h

# ---------------------------------------------------------------
# Initialize animated plot
# ---------------------------------------------------------------
plt.figure(figsize=(8,6))

line1 = plt.plot(x, xfe, color='r', lw=2, label='FE')
line2 = plt.plot(xfd, u, color='k', ls='-.', label='FD relaxation')
plt.title('Static Elasticity with relaxation method', size=16)
plt.ylabel('Displacement, $u$', size=16)
plt.xlabel('Position, $x$', size=16)
plt.legend(loc=4)
plt.grid(True)

plt.ion()   # set interective mode
plt.show()
# ---------------------------------------------------------------
for it in range(nt):
# Calculate the average of u (omit boundaries)
for i in range(1, nx-1):
du[i] =u [i+1] + u[i-1]
u = 0.5*( f*h**2/mu + du )
u = 0.15    # Boundary condition at x=0
u[nx-1] = 0.05 # Boundary condition at x=1
fd = u

# --------------------------------------
# Animation plot. Display both solutions
if not it % iplot:
for l in line2:
l.remove()
del l
line1 = plt.plot(x, xfe, color='r', lw=2)
line2 = plt.plot(xfd, fd, color='k', ls='-.')
plt.gcf().canvas.draw()

In [ ]: