File: slip.tex

package info (click to toggle)
python-escript 5.6-10
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 144,304 kB
  • sloc: python: 592,074; cpp: 136,909; ansic: 18,675; javascript: 9,411; xml: 3,384; sh: 738; makefile: 207
file content (191 lines) | stat: -rw-r--r-- 8,206 bytes parent folder | download | duplicates (3)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright (c) 2003-2018 by The University of Queensland
% http://www.uq.edu.au
%
% Primary Business: Queensland, Australia
% Licensed under the Apache License, version 2.0
% http://www.apache.org/licenses/LICENSE-2.0
%
% Development until 2012 by Earth Systems Science Computational Center (ESSCC)
% Development 2012-2013 by School of Earth Sciences
% Development from 2014 by Centre for Geoscience Computing (GeoComp)
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\section{Slip on a Fault}\label{Slip CHAP}
\begin{figure}[ht]
\centerline{\includegraphics{Slip1}}
\caption{Domain $\Omega=[0,1]^2$ with a vertical fault of length $0.5$.}
\label{fig:slip.1}
\end{figure}
%
In this example we illustrate how to calculate the stress distribution around
a fault\index{fault} in the Earth's crust caused by a slip\index{slip} through
an earthquake.

To simplify the presentation we assume a simple domain $\Omega=[0,1]^2$ with
a vertical fault in its center as illustrated in \fig{fig:slip.1}.
We assume that the slip distribution $s_{i}$ on the fault is known.
We want to calculate the distribution of the displacements $u_{i}$\index{displacement}
and stress $\sigma_{ij}$\index{stress} in the domain.
Further, we assume an isotropic, linear elastic material model of the form
\begin{eqnarray} \label{Slip  stress}
\sigma_{ij} & = & \lambda u_{k,k} \delta_{ij} + \mu ( u_{i,j} + u_{j,i})
\end{eqnarray}
where $\lambda$ and $\mu$ are the Lam\'e coefficients\index{Lam\'e coefficients}
and $\delta_{ij}$ denotes the Kronecker symbol\index{Kronecker symbol}.
On the boundary the normal stress is given by
\begin{eqnarray} \label{Slip natural fault}
\sigma_{ij}n_{j}=0
\end{eqnarray}
and normal displacements are set to zero:
\begin{eqnarray} \label{Slip constraint}
u_{i}n_{i} =0
\end{eqnarray}
The stress needs to fulfill the momentum equation\index{momentum equation}
\begin{eqnarray}\label{Slip general problem}
- \sigma_{ij,j}=0
\end{eqnarray}
This problem is very similar to the elastic deformation problem presented in \Sec{ELASTIC CHAP}.
However, we need to address an additional challenge: the displacement
$u_{i}$ is in fact discontinuous across the fault, but we are in the
lucky situation that we know the jump of the displacements across the fault.
This is in fact the given slip $s_{i}$.
So we can split the total distribution $u_{i}$ into a component
$v_{i}$ which is continuous across the fault and the known slip $s_{i}$
\begin{eqnarray}\label{Slip Split}
u_{i} = v_{i} + \frac{1}{2} s^{\pm}_{i}
\end{eqnarray}
where $s^{\pm}=s$ when right of the fault and $s^{\pm}=-s$ when left of the fault.
We assume that $s^{\pm}=0$ when sufficiently away from the fault.

We insert this into the stress definition in \eqn{Slip stress}
\begin{eqnarray} \label{Slip stress split}
\sigma_{ij} & = &
\sigma^c_{ij} +
\frac{1}{2} \sigma^s_{ij}
\end{eqnarray}
 with
\begin{eqnarray} \label{Slip stress split 1}
\sigma^c_{ij} = \lambda v_{k,k} \delta_{ij} + \mu ( v_{i,j} + v_{j,i})
\end{eqnarray}
and
\begin{eqnarray} \label{Slip stress split 2}
\sigma^s_{ij} = \lambda s^{\pm}_{k,k} \delta_{ij} + \mu ( s^{\pm}_{i,j} + s^{\pm}_{j,i}).
\end{eqnarray}
In fact, $\sigma^s_{ij}$ defines a stress jump across the fault.
An easy way to construct this function is to use a function $\chi$ which is
$1$ on the right and $-1$ on the left side from the fault.
One can then set
\begin{eqnarray} \label{Slip  stress split 23 }
\sigma^s_{ij} = \chi \cdot  ( \lambda s_{k,k} \delta_{ij} + \mu ( s_{i,j} + s_{j,i}) )
\end{eqnarray}
assuming that $s$ is extended by zero away from the fault.
After inserting \eqn{Slip stress split} into (\ref{Slip general problem}) we
get the differential equation\index{momentum equation}
\begin{eqnarray}\label{Slip general problem 2 }
- \sigma^c_{ij,j}=\frac{1}{2} \sigma^s_{ij,j}
\end{eqnarray}
Together with the definition (\ref{Slip stress split 1}) we have a
differential equation for the continuous function $v_i$.
Notice that the boundary condition (\ref{Slip constraint}) and (\ref{Slip natural fault})
transfer to $v_i$ and $\sigma^c_{ij}$ as $s$ is zero away from the fault.
In \Sec{ELASTIC CHAP} we have discussed how this problem is solved using
the \LinearPDE class. We refer to this section for further details.

To define the fault we use the \class{FaultSystem} class introduced in \Sec{Fault System}.
The following statements define a fault system \var{fs} and add the fault \var{1} to the system:
\begin{python}
  fs=FaultSystem(dim=2)
  fs.addFault(fs.addFault(V0=[0.5,0.25], strikes=90*DEG, ls=0.5, tag=1)
\end{python}
The fault added starts at point $(0.5,0.25)$ has length $0.5$ and points north.
The main purpose of the \class{FaultSystem} class is to define a
parameterization of the fault using a local coordinate system.
One can inquire the class to get the range used to parameterize a fault.
\begin{python}
  p0,p1 = fs.getW0Range(tag=1)
\end{python}
Typically \var{p0} is equal to zero while \var{p1} is equal to the length of the fault.
The parameterization is given as a mapping from a set of local coordinates
onto a parameter range (in our case the range \var{p0} to \var{p1}).
For instance, to map the entire domain \var{mydomain} onto the fault one can
use
\begin{python}
  x = mydomain.getX()
  p,m = fs.getParametrization(x, tag=1)
\end{python}
Of course there is the problem that not all locations are on the fault.
For those locations which are on the fault \var{m} is set to 1, otherwise 0 is used.
So on return the values of \var{p} define the value of the fault parameterization
(typically the distance from the starting point of the fault along the fault)
where \var{m} is positive.
On all other locations the value of \var{p} is undefined.
Now \var{p} can be used to define a slip distribution on the fault via
\begin{python}
  s = m*(p-p0)*(p1-p)/((p1-p0)/2)**2*slip_max*[0.,1.]
\end{python}
Notice the factor \var{m} which ensures that \var{s} is zero away from the fault.
It is important that the slip is zero at the ends of the faults.

We can now put all components together to get the script:
\begin{python}
  from esys.escript import *
  from esys.escript.linearPDEs import LinearPDE
  from esys.escript.models import FaultSystem
  from esys.finley import Rectangle
  from esys.weipa import saveVTK
  from esys.escript.unitsSI import DEG

  #... set some parameters ...
  lam=1.
  mu=1
  slip_max=1.
  mydomain = Rectangle(l0=1.,l1=1.,n0=16, n1=16)  # n1 needs to be a multiple of 4!
  # .. create the fault system
  fs=FaultSystem(dim=2)
  fs.addFault(V0=[0.5,0.25], strikes=90*DEG, ls=0.5, tag=1)
  # ... create a slip distribution on the fault
  p, m=fs.getParametrization(mydomain.getX(), tag=1)
  p0,p1= fs.getW0Range(tag=1)
  s=m*(p-p0)*(p1-p)/((p1-p0)/2)**2*slip_max*[0.,1.]
  # ... calculate stress according to slip:
  D=symmetric(grad(s))
  chi, d=fs.getSideAndDistance(D.getFunctionSpace().getX(), tag=1)
  sigma_s=(mu*D+lam*trace(D)*kronecker(mydomain))*chi
  #... open symmetric PDE ...
  mypde=LinearPDE(mydomain)
  mypde.setSymmetryOn()
  #... set coefficients ...
  C=Tensor4(0., Function(mydomain))
  for i in range(mydomain.getDim()):
    for j in range(mydomain.getDim()):
       C[i,i,j,j]+=lam
       C[j,i,j,i]+=mu
       C[j,i,i,j]+=mu
  # ... fix displacement in normal direction
  x=mydomain.getX()
  msk=whereZero(x[0])*[1.,0.] + whereZero(x[0]-1.)*[1.,0.] \
     +whereZero(x[1])*[0.,1.] + whereZero(x[1]-1.)*[0.,1.]
  mypde.setValue(A=C, X=-0.5*sigma_s, q=msk)
  #... solve pde ...
  mypde.getSolverOptions().setVerbosityOn()
  v=mypde.getSolution()
  # .. write the displacement to file:
  D=symmetric(grad(v))
  sigma=(mu*D+lam*trace(D)*kronecker(mydomain))+0.5*sigma_s
  saveVTK("slip.vtu", disp=v+0.5*chi*s, stress=sigma)
\end{python}
The script creates the file \file{slip.vtu} which contains the total
displacements and stress.
These values are stored as cell-centered data.
%
\begin{figure} [ht]
\centerline{\includegraphics[width=\figwidth]{Slip2}}
\caption{Total Displacement after the slip event}
\label{fig:slip.2}
\end{figure}
%
See \fig{fig:slip.2} for a visualization of the result.