This notebook is based on the paper A new discontinuous Galerkin spectral element method for elastic waves with physicaly motivaled numerical fluxes. Published in the 13th International Conference on Mathematical and Numerical Aspects of Wave Propagation.
- Kenneth Duru
- Ashim Rijal (@ashimrijal)
- Sneha Singh
To begin, consider the domain
The sub-domains are governed by the source-free elastic wave equation in a heterogeneous 1D medium is
\begin{align}
\rho^{\pm}(x)\partial_t v^{\pm}(x,t) -\partial_x \sigma^{\pm}(x,t) & = 0\
\frac{1}{\mu^{\pm}(x)}\partial_t \sigma^{\pm}(x,t) -\partial_x v^{\pm}(x,t) & = 0
\end{align}
Here, the field variables and material parameters in the sub-domains $ \Omega_{\pm}$ with the superscripts
The interface at
\begin{align} \text{force balance}: \quad &\sigma^{-} = \sigma^{+} = \sigma, \nonumber \ \text{fricition law}: \quad &\sigma = \sigma_{n}\frac{f\left(\left|[![ v ]!]\right|,\psi\right)}{\left|[![ v ]!]\right|}[![ v ]!] \end{align}
Here,
At the external boundaries $ x = 0, x = L$ we pose the general well-posed linear boundary conditions
\begin{equation} \begin{split} B_0(v, \sigma, Z_{s}, r_0): =\frac{Z_{s}}{2}\left({1-r_0}\right){v} -\frac{1+r_0}{2} {\sigma} = 0, \quad \text{at} \quad x = 0, \ B_L(v, \sigma, Z_{s}, r_n): =\frac{Z_{s}}{2} \left({1-r_n}\right){v} + \frac{1+r_n}{2}{\sigma} = 0, \quad \text{at} \quad x = L. \end{split} \end{equation}
with the reflection coefficients
Note that at
We define the mechanical energy in each subdomain by
\begin{equation} E^{\pm}(t) = \frac{1}{2}\int_{\Omega_{\pm}}{\left({\rho^{\pm}(x)} |v^{\pm}(x, t)|^2 + \frac{1}{\mu^{\pm}(x)}|\sigma^{\pm}(x, t)|^2\right) dx}. \end{equation}
The elastic wave equation with the frictional interface condition, satisfies the energy balance
\begin{equation} \frac{d \left(E^-(t)+E^+(t)\right)}{dt} = -\sigma [![ v]!] -v^-(0, t)\sigma^-(0, t) + v^+(L, t)\sigma^+(L, t),\le 0. \end{equation}
With the above friction law the first term in the right hand side of the energy rate,
We will design a provably stable DGSEM obeying the energy balance at the discrete level.
- Discretize the spatial domain
$x$ into$K$ elements and denote the${k}^{th}$ element$e^k = [x_{k}, x_{k+1}]$ and the element width $\Delta{x}k = x{k+1}-x_{k}$. Consider two adjacent elements$e^k = [x_{k}, x_{k+1}]$ and$e^{k+1} = [x_{k+1}, x_{k+2}]$ with an interface at$x_{k+1}$ . At the internal non-frictional interfaces we pose the physical conditions for a locked interface
\begin{align} \text{force balance}: \quad &\sigma^{-} = \sigma^{+} = \sigma, \nonumber \ \text{no slip}: \quad & [![ v]!] = 0 \end{align}
where
-
Within the element derive the weak form of the equation by multiplying both sides by an arbitrary test function and integrating over the element.
-
Next map the
$e^k = [x_{k}, x_{k+1}]$ to a reference element$\xi = [-1, 1]$ -
Inside the transformed element
$\xi \in [-1, 1]$ , approximate the solution and material parameters by a polynomial interpolant, and write \begin{equation} v^k(\xi, t) = \sum_{j = 1}^{N+1}v_j^k(t) \mathcal{L}j(\xi), \quad \sigma^k(\xi, t) = \sum{j = 1}^{N+1}\sigma_j^k(t) \mathcal{L}_j(\xi), \end{equation}
\begin{equation} \rho^k(\xi) = \sum_{j = 1}^{N+1}\rho_j^k \mathcal{L}j(\xi), \quad \mu^k(\xi) = \sum{j = 1}^{N+1}\mu_j^k \mathcal{L}_j(\xi), \end{equation}
where $ \mathcal{L}_j$ is the $j$th interpolating polynomial of degree
The interpolating nodes
\begin{equation} \sum_{i = 1}^{N+1} f(\xi_i)w_i \approx \int_{-1}^{1}f(\xi) d\xi, \end{equation}
where
-
At the element boundaries
$\xi = \pm 1$ , we generate transformed hat-variables$\widehat{v}^{k}(\pm 1, t)$ ,$\widehat{\sigma}^{k}(\pm 1, t)$ by solving a Riemann problem and constraining the solutions against interface and boundary conditions. These hat-variables encode the solutions of the IBVP at the element boundaries. For non-linear friction laws we must solve a non-linear algebraic problem to compute hat-variables at the element boundaries. Once the hat-variables are computed we communicate them to the element by penalizing hat variables against the incoming characteristics only. This gives the numerical fluctuations$F^k(-1, t)$ and$G^k(1, t)$ at the element boundaries. -
Finally, the flux fluctuations are appended to the semi-discrete PDE with special penalty weights and we have
\begin{equation} \begin{split} \frac{d \boldsymbol{v}^k( t)}{ d t} &= \frac{2}{\Delta{x}k} W^{-1}({\boldsymbol{\rho}}^{k})\left(Q \boldsymbol{\sigma}^k( t) - \boldsymbol{e}{1}F^k(-1, t)- \boldsymbol{e}_{N+1}G^k(1, t)\right), \end{split} \end{equation}
\begin{equation} \begin{split} \frac{d \boldsymbol{\sigma}^k( t)}{ d t} &= \frac{2}{\Delta{x}k} W^{-1}(1/{\boldsymbol{\mu}^{k}})\left(Q \boldsymbol{v}^k( t) + \boldsymbol{e}{1}\frac{1}{Z_{s}^{k}(-1)}F^k(-1, t)- \boldsymbol{e}{N+1}\frac{1}{Z{s}^{k}(1)}G^k(1, t)\right), \end{split} \end{equation}
where \begin{align} \boldsymbol{e}{1} = [ \mathcal{L}1(-1), \mathcal{L}2(-1), \dots, \mathcal{L}{N+1}(-1) ]^T, \quad \boldsymbol{e}{N+1} = [ \mathcal{L}1(1), \mathcal{L}2(1), \dots, \mathcal{L}{N+1}(1) ]^T, \end{align} and \begin{align} G^k(1, t):= \frac{Z{s}^{k}(1)}{2} \left(v^{k}(1, t)-\widehat{v}^{k}(1, t) \right) + \frac{1}{2}\left(\sigma^{k}(1, t)- \widehat{\sigma}^{k}(1, t)\right), \end{align} \begin{align} F^{k}(-1, t):= \frac{Z{s}^{k}(-1)}{2} \left(v^{k}(-1, t)-\widehat{v}^{k}(-1, t) \right) - \frac{1}{2}\left(\sigma^{k}(-1, t)- \widehat{\sigma}^{k}(-1, t)\right). \end{align}
And the weighted elemental mass matrix
\begin{align} W_{ij}(a) = \sum_{m = 1}^{N+1} w_m \mathcal{L}i(\xi_m) {\mathcal{L}j(\xi_m)} a(\xi_m), \quad Q{ij} = \sum{m = 1}^{N+1} w_m \mathcal{L}_i(\xi_m) {\mathcal{L}_j^{\prime}(\xi_m)}. \end{align}
- Time extrapolation can be performed using any stable time stepping scheme like Runge-Kutta or ADER scheme.This notebook implements both Runge-Kutta and ADER schemes for solving the elastic wave equation in a hoterogeneous medium with a nonlinear frictional interface, modeled by a linear friction law (LN), slip-weakening friction law (SW) or the rate-and-state friction law (RS).
**** Exercises****
- In this notebook we use linear, slip-weakening and rate-and-state friction laws. First choose the linear friction law. Initially the friction coefficient, alpha, is set to 1e1000000. What happens if you change that value to 0.1?
- Now change the frinction law to be slip-weakening. Run the simulation keeping the Tau_0 = 81.24+0.1*0.36, initial load, as it is. What happens if we decrease the initial load below 81.24?
- Change the friction law to be rate-and-state and run the simulation. Observe time evolution of slip-rate, stress on fault and slip.
- Change the time-integrator from RK to ADER. Observe if there are changes in the solution or the CFL number. Vary the polynomial order N.
# Parameters initialization and plotting the simulation
import Lagrange
import numpy as np
import timeintegrate
import quadraturerules
import specdiff
import utils
import matplotlib.pyplot as plt
#plt.switch_backend("TkAgg") # plots in external window
plt.switch_backend("nbagg") # plots within this notebook# Initialization and computation
# Tic
iplot = 10
# At the moment, keep the length of the two domain the same
# Ahysical domain x = [ax, bx] (km)
# For the first domain
ax_1 = 0.0
bx_1 = 30.0
# Physical domain x = [ax, bx] (km)
# For the second domain
ax_2 = bx_1
bx_2 = 60.0
# Choose quadrature rules and the corresponding nodes
# We use Gauss-Legendre-Lobatto (Lobatto) or Gauss-Legendre (Legendre) quadrature rule.
#node = 'Lobatto'
node = 'Legendre'
if node not in ('Lobatto', 'Legendre'):
print('quadrature rule not implemented. choose node = Legendre or node = Lobatto')
exit(-1)
# polynomial degree N: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
N = 5 # Lagrange polynomial degree
NP = N+1 # quadrature nodes per element
if N < 1 or N > 12:
print('polynomial degree not implemented. choose N>= 1 and N <= 12')
exit(-1)
# degrees of freedom to resolve the wavefield
deg_of_freedom1 = 301 # for first domain
deg_of_freedom2 = 301 # for second domain
# estimate the number of elements needed for a given polynomial degree and degrees of freedom
num_element1 = round(deg_of_freedom1/NP) # for first domain
num_element2 = round(deg_of_freedom2/NP) # for second domain
# Initialize the mesh
y_1 = np.zeros(NP*num_element1)
y_2 = np.zeros(NP*num_element2)
# Generate num_element dG elements in the interval [ax, bx]
x0_1 = np.linspace(ax_1,bx_1,num_element1+1)
dx_1 = np.diff(x0_1) # element sizes
x0_2 = np.linspace(ax_2,bx_2,num_element2+1)
dx_2 = np.diff(x0_2) # element sizes
# Generate Gauss quadrature nodes (psi): [-1, 1] and weights (w)
if node == 'Legendre':
GL_return = quadraturerules.GL(N)
psi = GL_return['xi']
w = GL_return['weights'];
if node == 'Lobatto':
gll_return = quadraturerules.gll(N)
psi = gll_return['xi']
w = gll_return['weights']
# Use the Gauss quadrature nodes (psi) generate the mesh (y)
for i in range (1,num_element1+1):
for j in range (1,(N+2)):
y_1[j+(N+1)*(i-1)-1] = dx_1[i-1]/2.0 * (psi[j-1] + 1.0) +x0_1[i-1]
for i in range (1,num_element2+1):
for j in range (1,(N+2)):
y_2[j+(N+1)*(i-1)-1] = dx_2[i-1]/2.0 * (psi[j-1] + 1.0) +x0_2[i-1]
deg_of_freedom1 = len(y_1) #same for both the domains
deg_of_freedom2 = len(y_2) #same for both the domains
# generate the spectral difference operator (D) in the reference element: [-1, 1]
D = specdiff.derivative_GL(N, psi, w)
# Boundary condition reflection coefficients
r0 = 0.0 # r=0:absorbing, r=1:free-surface, r=-1: clamped,
rn = 0.0 # r=0:absorbing, r=1:free-surface, r=-1: clamped,
# Initialize the wave-fields
L_1 = 0.5*(bx_1-ax_1)
L_2 = 0.5*(bx_2-ax_2)
delta_1 = 0.01*(bx_1-ax_1)
delta_2 = 0.01*(bx_2-ax_2)
x0_1 = 0.5*(bx_1+ax_1)
x0_2 = 0.5*(bx_2+ax_2)
# Material parameters
c1s = 3.464 + 0.0*np.sin(2.0*np.pi*y_1) # shear wave speed (km/s)
rho1 = 2.67 + 0.0*y_1 # density (g/cm^3)
mu1 = rho1 * c1s**2 # shear modulus (GPa)
Z1s = rho1*c1s # shear impedance
c2s = 3.464 + 0.0*y_2 # shear wave speed (km/s)
rho2 = 2.67 + 0.0*y_2 # density (g/cm^3)
mu2 = rho2 * c2s**2 # shear modulus (GPa)
Z2s = rho2*c2s # shear impedance
# Choose friction law: fric_law
# We use linear (LN: T = alpha*v, alpha >=0)
# Slip-weakening (SW)
# Rate-and-state friction law (RS)
fric_law = 'RS'
if fric_law not in ('LN', 'SW', 'RS'):
print('friction law not implemented. choose fric_law = SW or fric_law = LN')
exit(-1)
if fric_law in ('LN'):
alpha = 1e1000000 # initial friction coefficient
S = 0.0 # initial slip (in m)
Tau_0 = 81.24+1*0.36 # initial load (81.24 in MPa), slight increase will unlock the fault
W = 0.0
u_1 = np.exp(-(y_1-x0_1)**2/delta_1) # Gaussian
u_2 = 1/np.sqrt(2.0*np.pi*delta_2**2)*np.exp(-(y_2-x0_2)**2/(2.0*delta_2**2)) # Gaussian
if fric_law in ('SW'):
alpha = 1e1000000 # initial friction coefficient
S = 0.0 # initial slip (in m)
Tau_0 = 81.24+0.1*0.36 # initial load (81.24 in MPa), slight increase will unlock the fault
W = 0.0
u_1 = 0.0*np.exp(-(y_1-x0_1)**2/delta_1) # Gaussian
u_2 = 0.0/np.sqrt(2.0*np.pi*delta_2**2)*np.exp(-(y_2-x0_2)**2/(2.0*delta_2**2)) # Gaussian
if fric_law in ('RS'):
alpha = 1e1000000 # initial friction coefficient
S = 0.0 # initial slip (in m)
Tau_0 = 81.24+0.1*0.36 # initial load (81.24 in MPa), slight increase will unlock the fault
W = 0.4367
u_1 = 0.0*np.exp(-(y_1-x0_1)**2/delta_1) # Gaussian
u_2 = 0.0/np.sqrt(2.0*np.pi*delta_2**2)*np.exp(-(y_2-x0_2)**2/(2.0*delta_2**2)) # Gaussian
u_1 = np.transpose(u_1)
v_1 = np.transpose(u_1)
u_2 = np.transpose(u_2)
v_2 = np.transpose(u_2)
# Time stepping parameters
cfl = 0.5 # CFL number
dt = (cfl/(max(max(c1s),max(c2s))*(2*N+1)))*min(min(dx_1), min(dx_2)) # time-step (s)
t = 0.0 # initial time
Tend = 3.0 # final time (s)
n = 0 # counter
Vd = [0]
Sd = [Tau_0]
T = [t]
Slip = [0]
# Initialize animated plot
f1, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex='col', sharey='row',figsize=(10,7))
line1 = ax1.plot(y_1, u_1,'r')
line2 = ax2.plot(y_2, u_2,'r')
line3 = ax3.plot(y_1, v_1,'r')
line4 = ax4.plot(y_2, v_2,'r')
ax1.set_ylabel('velocity [m/s]')
ax3.set_ylabel('stress [Mpa]')
ax3.set_xlabel('X [m]')
ax4.set_xlabel('X [m]')
ax3.set_xlim([ax_1, bx_1])
ax4.set_xlim([ax_2,bx_2])
f1.subplots_adjust(wspace=0)
plt.ion()
plt.show()
time_integrator = 'ADER'
for t in utils.drange (dt,Tend+dt,dt):
n = n+1
if time_integrator in ('ADER'):
ADER_Wave_1D_GL_return = timeintegrate.ADER_Wave_1D_GL(u_1,v_1,u_2,v_2,S,W,D,NP,num_element1,\
num_element2,dx_1,dx_2,w,psi,t,r0,rn,dt,\
rho1,mu1,rho2,mu2,alpha,Tau_0,fric_law)
u_1 = ADER_Wave_1D_GL_return['Hu_1']
v_1 = ADER_Wave_1D_GL_return['Hv_1']
u_2 = ADER_Wave_1D_GL_return['Hu_2']
v_2 = ADER_Wave_1D_GL_return['Hv_2']
S = ADER_Wave_1D_GL_return['H_d']
W = ADER_Wave_1D_GL_return['H_psi']
if time_integrator in ('RK'):
RK4_Wave_1D_GL_return = timeintegrate.ADER_Wave_1D_GL(u_1,v_1,u_2,v_2,S,W,D,NP,num_element1,\
num_element2,dx_1,dx_2,w,psi,t,r0,rn,dt,\
rho1,mu1,rho2,mu2,alpha,Tau_0,fric_law)
u_1 = RK4_Wave_1D_GL_return['Hu_1']
v_1 = RK4_Wave_1D_GL_return['Hv_1']
u_2 = RK4_Wave_1D_GL_return['Hu_2']
v_2 = RK4_Wave_1D_GL_return['Hv_2']
S = RK4_Wave_1D_GL_return['H_d']
W = RK4_Wave_1D_GL_return['H_psi']
Vd.append(np.abs(u_1[-1]-u_2[0]))
Sd.append(v_2[0]+1.0*Tau_0)
T.append(t)
Slip.append(S)
# Update plot
if n % iplot == 0:
for l in line1:
l.remove()
del l
for l in line2:
l.remove()
del l
for l in line3:
l.remove()
del l
for l in line4:
l.remove()
del l
# Display lines
line1 = ax1.plot(y_1, u_1, 'r')
line2 = ax2.plot(y_2, u_2, 'r')
line3 = ax3.plot(y_1, Tau_0+v_1, 'r')
line4 = ax4.plot(y_2, Tau_0+v_2, 'r')
plt.gcf().canvas.draw()
plt.ioff()
plt.show()
<Figure size 432x288 with 0 Axes>
# Plotting time evolution of slip-rate, stress on the fault and slip
plt.figure(figsize=(10,7))
plt.subplot(3,1,1)
plt.plot(T,Vd,'r-')
plt.title('time evolution of slip rate')
plt.ylabel('slip-rate [m/s]')
plt.xlabel('time [s]')
plt.ylim([0, 8])
plt.subplot(3,1,2)
plt.plot(T, Sd, 'r-')
plt.title('time evolution of stress on the fault')
plt.ylabel('stress on the fault [MPa]')
plt.xlabel('time [s]')
plt.ylim([40, 83])
plt.subplot(3,1,3)
plt.plot(T, Slip, 'b-')
plt.xlabel('time [s]')
plt.ylabel('slip [m]')
plt.title('time evolution of slip')
plt.tight_layout()
plt.show()