Transcript PREDICTING THE GROUND MOTION: TWO DIFFERENT POINTS …

FINITE FAULT MODELING OF STRONG GROUND
MOTIONS USING AN EMPIRICAL GREEN’S
FUNCTION APPROACH
Case Study: 26 September 1997, 09:40GMT, Mw= 6.0 Colfiorito
Earthquake (Italy)
Laura Scognamiglio
ISTANBUL
JANUARY 2005
OBJECTIVES
The purpose of this study is to test the ground motion synthesis
methodology outlined by Hutchings and Wu (1990) and further
developed by Hutchings et al. (1991, 1994), and verify its capacity of
being used as a predicting tool in strong ground motion seismology as
developed by Hutchings (1991) and Hutchings et al. (1996).
The earthquake chosen for this test is the 26 September 1997, 09:40,
Mw=6.0 Colfiorito Earthquake (Italy).
METHOD
This methodology consists in computing synthetic ground motion solving the
discretized representation relation:
Slip function
N
 i Ai S (t i ) i
i 1
M 0ei
un ( X , t)  
Radial distance between
the Target event hypo. and
the elemental source.

i 
en  X , t i  


V

i
Rupture
surface
EGF
for
element
Scalar seismic moment of
the source event
The
earthquake
is
synthesized
by
discretizing a potential fault rupture
surface in N elemental areas Ai small
enough to model continuous rupture up to
highest frequency of interest, then all
available recordings of effectively impulsive
point source events are used as EGF for
each elemental area, convolved with a slip
function and interpolated to model a
continuous rupture.
the
Rupture
velocity
ith
COOK BOOK: how computing synthetic
seismograms with EGF
The FIRST STEP consists in selecting a data-base of small earthquakes to be
used as EGF. These events need to be generated by the same fault of the target
event and to have same focal mechanism. Seismic moment and corner
frequency of the events should be evaluated if not available.
The SECOND STEP consists in constructing the rupture scenarios for the
evaluation of the synthetic seismograms. These scenarios consist in a preferred
number of faulting model defined by: strike, dip, slip vector, rupture area, rupture
and healing velocity (rise times), roughness, hypocenter, and number and
location of large asperities. Moment remains fixed. The parameters are varied
about a preferred value and selected by a Monte Carlo pick using a triangular
distribution.
Rupture Parameters
Slip function: Kostrov with healing. The slip shape is approximated as a ramp.
Slip distribution: varies on the fault following the Kostrov slip function. It has
variable rise time and slip amplitude on the fault, but constant stress drop. This
results in a different value of slip for each small element due also to the
location respect to the hypo and the edges.
Rise time: rupture initiates at the arrival time of the rupture front, and
continues until the shortest time for the rupture front to reach a fault edge, and
for a healing phase to travel back to the point at the healing velocity.
Rupture velocity: from 0.75 to 1.0 times the shear wave velocity
Healing velocity: from 0.8 to 1.0 times the rupture velocity.
Asperities: small areas of high slip and high stress drop. Circular in shape,
diameter between 0.2 and 0.8 times the fault width, area between 10% to 50%
of the total fault area. They are not allowed to overlap.
Roughness: is the % of the rupture surface for which the rise time is shortened
to be between 0.1 to 0.9 times that the original value (delay in the rupture
initiation). Areas of roughness have corresponding high stress drop.
Moment: is constrained and depends on the magnitude of the earthquake to
synthesize. In the asperities M is randomly selected for obtaining slip at least
twice the average slip of background rupture.
Hypocenter: at least 0.2km from the edge, and constrained in the lower half of
the fault.
COOK BOOK: how computing synthetic
seismograms with EGF
THIRD STEP, computing synthetic seismograms.
The empirical Green’s function are:
• deconvolved from their source function;
• normalized by the M0 ;
• interpolated to provide the point source contribution to all elemental source
areas along a discretized fault surface area (interpolation is performed by
correcting for attenuation, 1/R, and P and S-wave arrival times due to
differences in source distance);
• convolved with analytical slip function;
• time delayed to simulate rupture velocity and
• summed to compute synthetic seismograms.
DATA ANALYSES AND VALIDATION PROCEDURE
1.
I have collected small earthquakes recorded by the same stations that
recorded the Colfiorito Earthquake and occurred on the same fault;
2.
I have evaluated seismic moment and corner frequency of these events;
3.
I have constructed rupure scenarios to simulate the Colfiorito Earthquake
rupture and I have calculate synthetic seismograms for each scenarios at
each station.
then, I have carried out a validation procedure based on two analyses:
4.
a FORWARD MODELING analysis to find whether one of the synthetic
seismograms obtained match the Colfiorito observed time histories;
5.
a PREDICTION TOOL analysis to develop a range of possible ground
motions and see if the actual ground motion recordings fall within the range
predicted.
DATA-SET
39
events
recorded
during
the
sequence.
These
events
have
hypocenter reliable to the main event
fault and are recorded in the same
location where the main shock was.
REPRODUCING THE COLFIORITO EARTHQUAKE
COLFIORITO
EARTHQUAKE
Constructing 30 Rupture Scenarios……..
Fault Parameters
Time, GMT
970926 09:40
a
Latitude (degrees)
43.030
a
Longitude (degrees)
12.862
a
Depth (km)
5.7
b
M0 (N·m)
1.2x1018
b
Mw
6.0
b
Strike (degrees)
144
b
Dip (degrees)
42
b
Rake (degrees)
280
c
Length (km)
12
c
Width (km)
10
c
Displacement (m)
0.37
c
Top of the rupture surface (km)
0.65
c,d
Rupture Velocity (km/s)
2.6
a, Deschamps et al. 2000; b, Ekström et
al., 1998. c, Zollo et al., 1999; d, Pino &
Mazza, 2000.
stkk
dpp
rec22
rh22
rec11
rh11
Models fault rupture parameters
dip (dpp)
strike (stkk)
Rake
hypo latitude
hypo longitude
hypo depth
depth of hazard surface
width hazard surface (dppdis)
length hazard surface (rh11+rh22)
rupture surface geometry
width rupture surface (rec22)
length rupture surface (rec11)
min and max displacement
seismic moment (M0)
rupture velocity (Vr)
healing velocity (Vh)
slip function
number of asperities
Roughness
small elements area
40º ± 0.5º
148º ± 5º
270º ± 20º
43.03º
12.87º
5.7 km
.65 ± .5 km
11.5 ± .5 km
rh11=13.0 ± .5 km
rh22=2.0 ± .5 km
rectangle
12.0 ± .001 km
10.0 ± .001 km
10-80 cm
1.2x1025 dyne·cm
2.6 km/s
0.8 Vr
Kostrov with healing
0-7
0-50%
0.001 km2
REPRODUCING THE COLFIORITO EARTHQUAKE
rupture scenario
CLF001
Target event
hypocenter
Rupture
surface
Asperities
The scenarios differ essentially for the asperities
number and the % of roughness.
MODEL
asperities
rgh (%)
CLF0 0 1
CLF0 0 2
CLF0 0 3
CLF0 0 4
CLF0 0 5
CLF0 0 6
CLF0 0 7
CLF0 0 8
CLF0 0 9
CLF0 1 0
0 1,0 2
1
1
1
1
1
1
0 1,0 2,0 3
none
1
33
0
10
10
25
0
20
0
33
50
Mo(x1026dyne·c
m)
0.0 4 4
0.1 0 3
0.0 4 2
0.0 7 9
0.0 8 9
0.0 5 8
0.0 6 4
0.0 3 1
0.1 2 0
0.0 1 6
mo1
mo2
0.0 2 5 0.0 5 1
0.0 1 7
0.0 7 8
0.0 4 1
0.0 3 1
0.0 6 2
0.0 5 6
0.0 2 9 0.0 3 2
0.1 0 4
mo3
0.0 2 8
st k
dp
sv
1 5 0.9
147
1 4 5.9
1 4 6.7
1 4 5.7
149
1 4 7.4
1 4 7.4
1 4 7.9
1 4 8.5
4 0.5
3 9.5
3 8.3
4 0.3
3 7.6
3 9.3
4 1.8
3 8.7
3 9.9
3 6.7
2 6 3.7
2 7 3.8
2 6 5.5
2 8 2.3
2 7 3.3
2 7 3.9
2 6 4.7
2 7 3.5
2 5 6.4
2 7 9.3
REPRODUCING THE COLFIORITO EARTHQUAKE
COMPARISON IN THE SPECTRA RESPONSE DOMAIN
For each model at each station, synthetic seismograms were calculated, then
absolute acceleration response spectra (AAR) and the pseudo velocity response
spectra (PSV) were evaluated and compared with the Colfiorito Earthquake
response spectra.
REPRODUCING THE COLFIORITO EARTHQUAKE
FITTING PROCEDURE
For evaluating if at least one of the 30 rupture scenarios is able to reproduce
the Colfiorito Earthquake, the comparison between real and the synthetic
seismograms was carried out on 10 different ground motion parameter: Arias
duration, energy duration, Arias intensity, energy integral, peak acceleration,
peak velocity, peak displacement, absolute acceleration response, Fourier
spectra, and cross-correlation (Anderson, 2003).
For each estimate is given a
value of 0 to 10, so that the
final score is between 0 and
100, with the latter being a
perfect fit.
CLF011
CLF021
REPRODUCING THE COLFIORITO EARTHQUAKE
Waveforms comparison
The scoring evaluation provides that the most likely scenarios of what likely
occurred during the Colfiorito Earthquake are CLF011 and CLF021
MODEL asperities
CLF011
01,02
CLF021
01,02
rgh
(% )
0
10
Mo(x1026dyne·cm)
0.061
0.079
mo1
0.018
0.026
mo2
0.041
0.015
mo3
stk
dp
sv
147.6 41.1 278.8
146.8 38.2 265
If the source parameters are relatively well known, the ground motion
synthesis methodology, here investigated, is reasonably able to
reproduce the rupture process and consequently the real seismogram.
PREDICTING TOOL
Strong Ground Motion “Prediction” Analysis
I tried to establish the potential of this empirical Green’s function synthesis
approach as a prediction tool in strong ground motion seismology.
Constructing 100 rupture scenarios
No previous information available on
the Colfiorito Earthquake was used
in calculating the rupture scenarios.
I started from:
• a normal fault in Apennine
direction (NNW-SSE);
• with dip coherent with the range
showed by Umbria-Marche normal
faults (Barchi et al., 2000),
• and fault dimension related with
the magnitude of the earthquake to
reproduce.
Models rupture fault parameters
dip (dpp)
strike (stkk)
Rake
depth of hazard surface
hypocentral coordinates
width hazard surface (dppdis)
length hazard surface (rh11+rh22)
rupture surface geometry
major axis (aa1)
minor axis (bb1)
min and max displacement
seismic moment (M0)
rupture velocity (Vr)
healing velocity (Vh)
slip function
number of asperities
Roughness
small elements area
35º ± 15º
150º ± 20º
270º ± 20º
2 ± 2 km
free to vary
11.5 ± 2 km
rh11=13.0 ± 2 km
rh22=2.0 ± 2 km
ellipse
11.0 ± 5.5 km
9.50 ± 4.25 km
10-80 cm
1.2x1025 dyne·cm
0.75-1.0 Vs km/s
0.8-1.0 Vr
Kostrov with healing
0-7
0-50%
0.001 km2
THEN I EVALUATED SYNTHETIC SEISMOGRAMS FOR EACH MODEL AT EACH
STATION AND I VERIFIED THAT COLFIORITO EARTHQUAKE FALLS IN
BETWEEN THE RANGE PREDICTED.
PREDICTING TOOL
COMPARISON IN THE SPECTRA RESPONSE DOMAIN
Almost all the models are comprised between one standard deviation of the mean
for the three stations.
ASSI: AAR and PSV fit quite well the Colfiorito shape spectra in all the frequency
band. Colfiorito earthquake lies close to the average curve.
COLF and NOCR spectra show a quite good fit until 0.3-0.4 s, for lower period the
predicted ground motion overestimate the real one.
PREDICTING TOOL
Number of rupture scenarios
For verifying the choice of using just 100 scenarios by randomly varying each
parameter, that we assume uniformly distributed over its own allowed range
and uncorrelated with the others, I plot the evolution of the AAR mean and one
standard deviation as the number of scenarios increases.
MEAN OF “AAR” AT 1 Hz
The average and its uncertainty start to
stabilize after 30 models. The 1-bound
decreases from 0.2 after 10 scenarios to 0.06
after 100 scenarios, meaning that the
uncertainty is reduced to 30 % of its original
value. This plot shows that 100 scenarios are
sufficient to span the variability in strong
ground
motion
due
to
the
source
uncertainties.
RESULTS and CONCLUSIONS
The purpose of this study was to test the ground motion synthesis
methodology outlined by Hutchings and Wu (1990) for verifying its
capability of being used as a predicting tool in strong ground motion
seismology. The validation procedure was carried out on the 26
September 1997, Mw 6.0 Colfiorito Earthquake.
1.
The “forward modeling” analysis results demonstrate that this
strong ground motion synthesis methodology is a technique
capable, once the scenarios are well constrained by independent
information, to reproduce reasonably well the observed records;
2.
comparing the Colfiorito spectra (AAR and PSV) with spectra
calculated from 100 rupture scenarios, constructed without
including any knowledge of the source characteristics, emerges that
it is possible to make reasonable strong ground motion
“predictions” even without having a priori knowledge of the fault
characteristics, by running enough models.
THE END!!!!
RESULTS……
Synthesis of Colfiorito Earthquake
SPECTRA RESPONSE DOMAIN COMPARISON
• Colfiorito response spectra fall inside the 30 AAR’s and PSV’s calculated at
ASSI and COLF, showing the same amplitude of the average calculated for
these synthetics;
• synthetic spectra at NOCR, on average, overestimate the real ground motion.
In the range of periods analyzed here, the latter follows the curve defined by
the average minus one standard deviation;
SCORING PROCEDURE
• the quantitative matching evaluation shows that, in the thirty scenarios tried,
two combinations of source parameters give a good fit for all the three stations
(Models 011 and 021).
Strong Ground Motion “Prediction” Analysis
SPECTRA RESPONSE DOMAIN COMPARISON
•The AAR’s and the PSV’s evaluated for the synthetics waveforms at the ASSI
station site, fit quite well the shape of the real strong motion spectra, that lies
close to the average in all the frequency band;
•The AAR’s and the PSV’s obtained from the NOCR and COLF stations’
recordings fall within the range of ground motion response spectra calculated
from the synthetics seismograms until the period of 0.3-0.4 s. For period lower
than this threshold, the calculated response spectra overestimate the real ones.
REPRODUCING THE COLFIORITO EARTHQUAKE
COMPARISON IN THE RESPONSE SPECTRA DOMAIN
The RESPONSE SPECTRUM describes the maximum response of a single
degree-of-freedom (SDOF) system to a particular input motion as a
function of the natural frequency (or natural period) and the damping ratio
of the SDOF system.
It’s important to remember that:
response spectra reflect strong ground
motion characteristics indirectly, since
they are filtered by the response of the
SDOF structure;
amplitude, frequency content and
duration of the input motion all influence
the spectral values;
response spectra represent only the
maximum responses of a number of
different structures.
Larry
ALMA MATER STUDIORUM
Dipartimento di Fisica dell’Università
degli Studi di Bologna
Dottorato in Geofisica, XVI ciclo
PREDICTING THE GROUND MOTION:
TWO DIFFERENT POINTS OF VIEW
Laura Scognamiglio
OBJECTIVES
The intention of this dissertation is to look into the empirical
and semi-empirical approach for estimating strong ground
motion.
The two different methods were investigated for understanding
their potentials for being used in the evaluation of the
earthquake-induced ground motion:
•Regression analyses on background seismicity
•Strong ground motion evaluation with empirical Green’s
function
EARTHQUAKE GROUND MOTION ESTIMATION
TECNIQUES:
1. Theoretical evaluation
2. Semi-Empirical approach
3. Regression Techniques
Score for 100 models