Seismic microzonation and earthquake damage scenarios for urban areas


Ansal, A.; Kurtuluş, A.; Tönük, G.

Soil Dynamics and Earthquake Engineering 30(11): 1319-1328

2010


Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
SOIL
DYNAMICS
ERRIFICSJAILE
ENGINEERING
Contents
lists
available
at
ScienceDirect
Soil
Dynamics
and
Earthquake
Engineering
ELSEVIER
journal
homepage:
www.elsevier.com/locate/soildyn
Seismic
microzonation
and
earthquake
damage
scenarios
for
urban
areas
Atilla
Ansal*,
Ash
Kurtulus,
Gokce
Tontik
Bogazici
University,
Kandilli
Observatory
and
Earthquake
Research
Institute,
Cengelkoy,
34684
Istanbul,
Turkey
ARTICLE
INFO
ABSTRACT
Article
history:
Received
23
July
2009
Received
in
revised
form
29
May
2010
Accepted
12
June
2010
A
methodology
for
seismic
microzonation
and
earthquake
damage
scenarios
may
be
considered
as
composed
of
two
stages.
In
the
first
stage,
microzonation
maps
with
respect
to
estimated
earthquake
characteristics
on
the
ground
surface
are
generated
for
an
investigated
urban
area.
The
effects
of
local
geological
and
geotechnical
site
conditions
are
taken
into
account
based
on
site
characterization
with
respect
to
representative
soil
profiles
extending
down
to
the
engineering
bedrock
1D
site
response
analyses
are
performed
to
calculate
earthquake
characteristics
on
the
ground
surface
using
as
many
as
possible,
hazard
compatible
real
acceleration
time
histories.
In
the
second
stage,
vulnerability
of
buildings
and
pipeline
systems
are
estimated
based
on
site-specific
ground
motion
parameters.
A
pilot
study
is
carried
out
to
evaluate
seismic
damage
in
a
district
in
Istanbul,
Turkey.
The
results
demonstrate
the
significance
of
site
characterization
and
site
response
analysis
in
calculating
the
earthquake
characteristics
on
the
ground
surface
in
comparison
to
simplified
empirical
procedures.
©
2010
Elsevier
Ltd.
All
rights
reserved.
1.
Introduction
Seismic
microzonation
and
earthquake
loss
estimation
scenar-
ios
are
among
the
essential
tools
needed
for
city
planning,
disaster
preparedness,
risk
reduction,
hazard
mitigation
decisions,
and
urban
rehabilitation
actions
in
earthquake
prone
areas.
Loss
estimation
due
to
possible
future
earthquakes
in
an
urban
environment
is
a
very
complex
process
that
requires
detailed
building
and
lifeline
inventories,
probabilistic
or
deterministic
analyses
of
seismic
hazard
on
the
ground
surface
and
assessment
of
vulnerability
of
the
inventories
due
to
the
estimated
earth-
quake
characteristics.
There
are
basically
three
phases
that
control
the
earthquake
damage
estimation
process:
(1)
seismic
hazard
assessment
and
input
ground
motion
characteristics,
(2)
modification
of
these
input
ground
motion
due
to
site
conditions,
and
(3)
vulnerability
formulations
to
estimate
damage
distribution.
All
these
three
stages
could
play
significant
role
on
the
outcome,
depending
how they
are
evaluated.
Several
methodologies
11-5]
have
been
developed
over
the
past
years
that
take
into
account
various
aspects
of
loss
estimation
process.
However,
none
of
these
loss
estimation
methodologies
involves
detailed
analysis
of
local
site
conditions
when
predicting
ground
motion
characteristics
on
the
ground
surface.
The
methodology
proposed
in
this
work
provides
a
loss
estimation
method
that
takes
local
site
effects
into
account
by
*Corresponding
author.
E-mail
address:
ansal@boun.edu.tr
(A.
Ansal).
0267-7261/$-see
front
matter
2010
Elsevier
Ltd.
All
rights
reserved.
doi:10.1016/j.soildyn.2010.06.004
performing
large
numbers
of
1D
site
response
analyses
using
Shake91
code
16].
A
software
tool
is
developed
to
apply
this
methodology
for
damage
scenario
predictions
in
urban
areas.
In
order
to
analyze
the
complex
process
for
conducting
microzonation
with
respect
to
different
earthquake
characteristics
on
the
ground
surface
and
to
calculate
damage
distributions
within
the
investigated
urban
environment,
it
is
essential
to
utilize
a
flexible
software
package.
The
main
purpose
of
such
an
earthquake
scenario
software
tool
besides
performing
microzonation
and
earthquake
damage
scenarios
for
the
investigated
area
is
to
have
the
capability
to
conduct
parametric
studies
for
evaluating
the
range
of
variability
induced
in
these
three
stages
and
to
assess
the
significance
of
the
related
factors
in
the
estimated
final
damage
distributions.
2.
Methodology
for
microzonation
and
damage
scenarios
The
proposed
methodology
is
composed
of
two
main
phases.
The
first
phase
involves
generation
of
microzonation
maps
with
respect
to
earthquake
ground
shaking
parameters
due
to
the
selected
regional
earthquake
hazard
scenario.
In
the
second
phase,
vulnerability
of
buildings
and
pipelines
are
estimated
based
on
the
calculated
earthquake
ground
shaking
parameters.
Results
are
displayed
in
damage
distribution
maps
for
buildings
and
pipeline
systems
that
are
produced
in
GIS
environment.
The
first
step
is
to
adopt
a
grid
system
that
divides
the
investigated
urban
area
into
cells
(typically
250
m
x
250
m)
according
to
the
availability
of
geological,
geophysical,
and
geotechnical
data.
Variations
of
earthquake
shaking
parameters
0.5
0.5
1059-E
maim
MVHC90
0
I
.....
L
1°
5
"
-----
0.5
0.3
0.1
If
-0.1
0I
C
.03
-0_3
-05
0.5
0.3
0.1
-0.1
-0
.
5
05
20
-05
40
30
0
10
40
50
0
e
0.5
0.3
0
••
.0.1
0.5
5
10
13
4_5
10
N
25
35
40
TIMIE737
.0.3
-0.5
25
35
0
N
15
20
25
TOTEM
114E10
-0.1
1
-43
! I
-0.5
I
1
i I
1
1
ID
15
20
25
30
35
TIME.1.41
05
07
I-ELC18024
.
_
0.3
0.1
1-ELC270
I I ! I !
I
0.3
Jos000
1
0.1
03
-
0.1
J05090
1320
A.
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
for
bedrock
outcrop
within
the
area
are
separately
determined
for
a
specified
level
of
exceedance
probability
or
using
deterministic
simulations.
Site
characterization
is
performed
based
on
available
borings
and
other
relevant
information
by
defining
one
repre-
sentative
soil
profile
for
each
cell
with
shear
wave
velocities
extending
down
to
the
engineering
bedrock
(shear
wave
velocity,
V
s
>
750
m/s).
Site
specific
earthquake
characteristics
on
the
ground
surface
for
each
representative
soil
profile
are
calculated
using
one
dimensional
site
response
analyses,
Shake91.
Hazard
compatible
acceleration
time
histories
(in
terms
of
expected
fault
type,
fault
distance,
and
earthquake
magnitude)
are
selected
and
site
response
analyses
are
performed
for
a
selected
number
of
acceleration
time
histories.
It
was
demonstrated
by
Ansal
and
Toni
&
[7]
that
if
limited
number
of
input
acceleration
time
histories
(e.g.
3
records
as
specified
in
some
earthquake
codes)
are
used,
even
with
scaling
to
the
same
peak
ground
acceleration
(PGA)
amplitudes
for
site
response
analysis,
the
results
in
terms
of
PGA,
peak
ground
velocity
(PGV),
and
elastic
acceleration
response
spectrum
(SA)
can
be
significantly
different
for
different
sets
of
input
motion
records.
This
would
introduce
an
important
uncertainty
when
estimating
the
damage
distribution.
Therefore
to
partially
overcome
this
issue,
one
possible
option
is
to
use
as
many
acceleration
time
histories
as
possible
(e.g.
25-30)
from
the
hazard
compatible
bin
(in
terms
of
fault
type,
earthquake
magnitude,
and
epicenter
distance)
as
input
motions
for
site
response
analyses.
The
selected
time
histories
can
be
real
earthquake
acceleration
records,
or
alternatively
can
be
calculated
using
simulation
models
[8].
In
the
case
of
using
real
acceleration
time
histories,
PGA
scaling
is
adopted
as
suggested
by
Ansal
et
al.
[9]
and
Durukal
et
al.
[10].
Site
response
analyses
using
Shake91
provide
the
variations
of
PGA
and
SA
on
the
ground
surface.
Variation
of
PGV
is
determined
through
integration
of
acceleration
time
histories
on
the
ground
surface.
Average
of
all
spectral
acceleration
values
between
0.1
and
1.0
s
periods
of
the
elastic
acceleration
response
spectrum
(SA„„,
(0.1-1
s))
is
calculated
as
one
parameter
representing
earthquake
shaking
intensity
on
the
ground
surface.
Site-specific
peak
spectral
accelerations
corresponding
to
0.2
s
(SABorcherdt)
are
also
calculated
through
empirical
relationship
proposed
by
Borcherdt
[11]
using
equivalent
(average)
shear
wave
velocities
for
the
top
30
m
of
soil
profiles
(
Vs3o)•
Superposition
of
empirically
0.5
O.
5
05
0.5
La*
10614
I
4_1
41.5
-0.3
03
-0_3
-0.5
0.1
-0.1
-0.3
-05
20
25
10
15
10
IS
20
25
50
0
le
L5
20
23
0.5
0.3
0.1
-0s
0
3
0-5
Antal°
20
21
0<
0.5
0.1
0.1
-0.1
-03
A_5
375-E
'
0
1.5
20
25
05
090
10
15
la
3
0.3
-01
-
-03
A-5
0.5
0.3
0.1
4
1
4.3
-0.5
75N
LS
30
23
0.5
I
-P.-
'9
°
I
!
I
I-
-4-
i j
!
I-
i
i
1
i
10
15
10-
0.5
03
01
4.1
4.3
4.5
I062-g
10
111
,
4114".'.
L5
20
23
0
-
-0
1
4..
"
..
k
4.3
-0.5
BOL
000
-16
46,0060,0
1
:w4„.
10
20
25
33
01
-0.1
J.
-03
-
-03
0
5
1°62
"
10
13
20
25
0.5
!
ramie
'
mciro
I
1
--
05
0.3
0.3
0.1
-0.1
-03
-45
6131270
3
I
0.3
-03
GBZ000
-0.5
0.5
-0.5
15
20
10
15
20
10
L5
0
0
5
le
Fig.
1.
Acceleration
time
histories
that
are
used
as
input
motion
in
site
response
analysis.
A
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
1321
calculated
values
(i.e.
SABorcherdt)
with
those
calculated
using
Shake91
(e.g.
SA
avg
(0.1-1
s))
provides
a
general
assessment
of
the
variation
of
site
effects
and
is
used
as
a
parameter
for
microzonation
with
respect
to
ground
shaking
intensity
[12].
In
order
to
assess
seismic
vulnerability
for
buildings,
two
parameters;
site-specific
short
period
(corresponding
to
0.2
s)
and
long
period
(corresponding
to
1
s)
spectral
accelerations
are
calculated.
Site-specific
acceleration
response
spectrum
is
used
to
determine
spectral
accelerations
for
the
short
period
(S
s
)
and
for
the
long
period
(S
1
).
An
approach
is
adopted
to
determine
the
best-
fit
NEHRP
[13]
envelope
to
the
calculated
average
acceleration
response
spectra
[14].
All
the
requirements
of
the
NEHRP
design
spectra
are
applied
in
obtaining
the
short
(S
s
)
and
long
(S
1
)
period
spectral
accelerations.
The
two
independent
variables
in
the
developed
optimization
algorithm
are
S
s
and
S
i
.
The
NEHRP
design
spectrum
is
preferred
because
of
its
flexibility
in
defining
spectral
accelerations
[15].
At
this
stage,
microzonation
maps
for
the
investigated
urban
area
may
be
prepared
with
respect
to
Vs30,
NEHRP
site
classifica-
tion,
PGA,
PGV,
SA
a
v
g
(0.1-1
S
A
BOrCherdt
,
Ss,
and
S
i
.
A
map
representing
the
ground-shaking
intensity
is
prepared
where
the
estimated
relative
shaking
intensity
levels
are
based
on
the
superposition
of
two
parameters:
SA
avg
(0.1-1
s)
and
SABorcherdt•
The
approach
adopted
in
the
assessment
of
the
calculated
microzonation
maps
using
SA
avg
(0.1-1
s)
and
SAsorchardt,
involves
the
division
of
the
area
into
three
zones
as
A,
B,
and
C
[16].
Since
the
site
characterizations,
as
well
as
all
the
analysis
performed,
require
various
approximations
and
assumptions,
it
is
preferred
not
to
present
the
numerical
values
for
the
microzonation
parameters.
The
variations
of
the
parameters
are
considered
separately
and
their
frequency
distributions
are
calculated
to
determine
the
boundaries
between
the
three
zones.
The
zone
C
shows
the
most
unsuitable
33
percentile
(e.g.
high
spectral
accelerations),
zone
B
the
medium
34
percentile
and
zone
A
shows
the
most
favorable
33
percentile
(e.g.
low
spectral
accelerations).
The
final
microzonation
map
is
a
relative
map
defined
in
terms
of
three
zones
independent
of
the
absolute
values
of
the
ground
shaking
intensity.
In
the
second
phase
of
the
procedure,
vulnerability
analyses
for
building
and
pipeline
inventories
are
evaluated.
Site-specific
spectral
accelerations
S
s
and
S
i
are
used
to
assess
the
vulnerability
of
the
building
stock.
The
analytical
estimation
of
structural
damage
is
formulated
based
on
[1],
where
the
vulnerability
relationships
(also
called
fragility
curves)
are
developed
in
terms
of
spectral
displacements,
which
in
turn
are
calculated
from
the
estimated
mean
inelastic
drift
capacities
of
buildings
for
various
damage
states.
The
mean
drift
demand
of
a
typical
building
is
estimated
through
nonlinear
static
procedures
(NSPs),
which
are
based
on
performance-based
seismic
evaluation
[17-19].
NSPs
are
based
on
the
capacity
(pushover)
curve
of
the
given
building
and
the
estimation
of
the
inelastic
spectral
displacement
demand
consistent
with
the
capacity
curve.
In
spectral
displacement-based
fragility
curves,
the
horizontal
axis
represents
the
spectral
displacement
demand
and
vertical
axis
refers
to
the
cumulative
probability
of
structural
damage
reaching
or
exceeding
the
threshold
of
a
given
damage
state.
The
analytical
expression
of
each
fragility
curve
is
based
on
the
assumption
that
earthquake
damage
distribution
can
be
repre-
sented
by
a
lognormal
distribution
function
[1,20]:
P[D
>
ci
s
IS
c
id
=
0[(1/
fi
ds
)ln(S
d
i/S
d4s
)]
(1)
where
D
refers
to
the
damage,
Sdi
is
the
inelastic
spectral
displacement
demand,
Sd,d
s
represents
the
median
value
of
spectral
displacement
corresponding
to
the
threshold
of
the
damage
state,
d
s
(slight,
moderate,
extensive
or
complete),
reached,
fi
d
s
is
the
standard
deviation
of
the
natural
logarithm
of
the
spectral
displacement
corresponding
to
the
damage
state
concerned.
P
refers
to
cumulative
standard
normal
distribution
function.
Median
spectral
displacement
values
corresponding
to
each
damage
state,
Sd,d
s
,
are
estimated
in
terms
of
story
drift
ratios
specified
for
each
building
type.
On
the
other
hand,
the
standard
deviation
fid
s
is
empirically
estimated
to
cover
the
uncertainties
associated
with
the
defini-
tion
of
the
damage
level
concerned,
the
building
load
capacity,
and
the
earthquake
ground
motion
specified.
Once
median
story
drift
ratios
are
estimated
for
each
building
and
for
each
damage
state,
the
median
spectral
displacement
value,
Sd,d
s
,
for
the
fundamental
vibration
mode
is
expressed
as
Sd,ds
=
0L2DdsH
(
2
)
0
20
40
60
80
E
IS
100
O
120
140
169
180
200
Shear
Wave
Velocity
(mIsec)
0
20
40
60
80
10D
120
140
1130
180
200
Shear
Wave
Velocity
(misec)
Shear
Wave
Velocity
(m(sec)
0
CL-CH
CL-CH
20
SG-GL-S
gIN-GP
GW.GP
CL-CH
GVVT
I
GWT
40
GWT
60
SC-CL
SC-CL
SC.CL
80
aw-ap
100
Rock
GW-GP
120
Hock
140
J2
N5
160
B25
180
200
Rock
0
200
400
600
0
200
400
600
0
200
400
600
Fig.
2.
Typical
soil
profiles
and
variation
of
shear
wave
velocity
with
depth
in
Zeytinburnu.
1322
A.
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
where
Dd
s
refers
to
median
storey
drift
ratio
estimated
for
the
damage
state
concerned,
H
represents
the
total
building
height,
and
oc
2
is
the
modal
parameter
defined
as
=
1
az
/(
0
t,i
"Li)
(3)
where
O
t
,
i
represents
the
first
mode
shape
amplitude
at
the
building
top
and
L
1
denotes
the
participation
factor
of
the
same
mode.
On
the
basis
of
selected
classification
system
for
a
given
building
inventory,
the
values
considered
for
H
and
oc
2
as
well
as
the
median
values
of
story
drift
ratios
and
spectral
displacements
defined
in
accordance
with
Eq.
(2)
are
determined
for
each
damage
level
specified,
e.g.,
slight,
moderate,
extensive,
and
complete
damage
levels,
respectively.
Building
damage
is
ex-
pressed
in
terms
of
number
of
buildings
at
each
damage
state
for
each
building
type
at
each
cell
in
the
grid
system.
Vulnerability
of
pipeline
inventory
with
respect
to
wave
propagation
is
evaluated
using
site-specific
PGV
values
as
input
parameters.
Empirical
correlations
which
relate
damage
rate
to
PGV
are
employed
to
predict
damage
in
pipelines
in
terms
of
damage
rate
and
number
of
pipe
damages
at
each
cell
in
the
grid
U
ZEYTINBURNU
MUNICIPALITY
1411CROZONATION
WITH
RESPECT
TO
AVERAGE
SHEAR
WAVE
VELOCITY
200
m/s
<
Vseq
<-300
mis
m/s
<
<=
300
Vseq
400
Ws
n
600,,,1s
<
Vseq
<=50D
rr
0
0.75
1
5
Nalometers
Fig.
3.
Variation
of
average
(equivalent)
shear
wave
velocity
for
the
top
30
m
of
soil
profiles
(Voo).
Table
'1
GIG„,„„
and
damping
ratio-shear
strain
relationships
used
to
define
nonlinear
soil
properties.
Material
type
Soil
type
Reference
1
Fat
clay
(CH)
PI=60%
Vucetic
and
Dobry
[28]
2
Fat
clay
(CH)
PI=45%
Vucetic
and
Dobry
[28]
3
Lean
clay
(CL)
PI=30%
Vucetic
and
Dobry
[28]
4
Lean
clay
(CL)
PI=15%
Vucetic
and
Dobry
[28]
5
Silt
(ML-MH)
PI=10%
Darendeli
[29]
6
Sand
with
fines
(SM-SC)
Darendeli
[29]
7
Clean
sand
(SW-SP)
Seed
et
al.
[30]
8
Gravel
(GM-GC)
Seed
et
al.
[30]
9
Gravel
(GW-GM)
Menq
et
al.
[31]
10
Soft
rock
(0-6
m)
EPRI
[32]
11
Soft
rock
(6-16
m)
EPRI
[32]
12
Rock
(16-37
m)
EPRI
[32]
13
Rock
(153-305
m)
EPRI
[32]
system.
Results
from
vulnerability
analyses
are
used
to
prepare
damage
distribution
maps
for
the
buildings
and
pipelines.
3.
Pilot
study
The
methodology
is
developed
into
a
software
package
1211
to
provide
a
practical
tool
for
assessing
the
seismic
vulnerability
of
an
urban
area.
A
pilot
study
is
carried
out
using
KoeriLossV2
to
perform
a
damage
scenario
for
Zeytinburnu
district
in
Istanbul,
Turkey,
where
building
and
gas
pipeline
inventories
are
available
to
some
detail.
The
area
of
investigation
is
approximately
20
km
2
occupied
mostly
with
low-
to
mid-rise
residential
buildings.
The
available
inventory
indicated
that
natural
gas
pipeline
system
in
the
district
consists
of
steel
pipes
with
diameters
changing
between
102
and
762
mm.
3.1.
Seismic
hazard
and
site
response
analyses
A
grid
system
with
cells
of
250
m
x
250
m
is
defined
for
the
study
area.
Probabilistic
seismic
hazard
analysis
is
carried
out
to
Spectra
from
Slte
Response
Analyses
-v.
Average
Spectrum
Best-Flt
NEHRP
Envelope
Spectrum
P
I
1
!
1
t
la
i.......r.
,
...
-
.
1.
).
............-.#
s
7
.
......4-
0.01
0.10
1.00
10
00
Period
(s)
Fig.
4.
Typical
best-fit
NEHRP
envelope
spectra
fitted
to
average
elastic
acceleration
response
spectra,
in
comparison
with
the
all
acceleration
response
spectra
calculated
by
site
response
analysis.
\
ii
.
.
.
I .
.
1
20
.
5
ii
17
i
°
r:a
a
'
Peak
GrounClAcceler:ton
5
PEAK
GROUND
ACCELERATION
0.1g
<
PGA
<=
0.3g
0.3g
<
PGA
<=
0.5g
7
6.59
<
PGA
‹=
0.7g
0.7g
<
PGA
<=
0.99
0.9g
<
PGA
<=
1.1g
o
1
kilometres
Fig.
5.
Variation
of
peak
ground
acceleration
(PGA)
from
site
response
analyses.
3.5
3
0
2.5
2
8
1.5
T2
77
ct.
co
0.5
0
sr
t.
NO
Cr..WYO.:441y
PEAK
GROUND
VELOCITY
(PGV)
L
50
cm's
PGV
<=
60
crivs
PGV
<=
70
cm/s
70
cm/s
<
PGV
80
cmIs
80
emus
<
PGV
90
cmfs
90
cm/s
<
PGV
<=
100
cmfs
100
cm/s
<
PGV
<•
110
cm/s
110
cm/s
<
PGV
<=
120
cmfs
0
1
2
kilometers
Fmk
SmumlVoletkey
PEAK
GROUND
VELOCITY
(PGV)
calculated
by
HAZUS
formula
60
cmls
<
PGV
<=
70
cmfs
LI
70
cm/s
<
PGV-r=
80
cm/s
80
cmfs
<
PGV
<=
90
cm/s
la
90
cm/s
<
PGV
<=
100
cm/s
100
cmfs
<
PGV
<=110
cmfs
0
1
2
kilometers
55
5
6
Maxlmun
Iroce.O
Accoleralans
MAXIMUM
SPECTRAL
ACCELERATIONS
(SS)
E
s.c=
0.5g
7
0.5g
<
Ss
<
=
1g
lg
ss
<=
1.5g
1.5g
<
Ss
<=
2g
El
2g
<
Ss
<=
2.6g
2.5g
<
Ss
<=
3g
a
2
kilometers
Illazirmarn
Spectral
corloratlons
MAXIMUM
SPECTRA!.
ACCELERATIONS
(SS)
BASED
ON
NEHRP
AMPLIFICATION
FACTORS
0
0.5g
<
Ss
<
=
le
E
1g
<
Ss
<=
1.5g
2
kilometers
A
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
1323
evaluate
PGAs
and
spectral
accelerations
at
T=0.2
and
1
s
for
each
cell
on
the
engineering
bedrock
outcrop
122].
A
regional
time
dependent
Poisson
model
for
the
return
period
of
475
years
that
corresponds
approximately
to
10%
probability
of
exceedance
in
50
years
is
considered
in
the
analysis
123].
Twenty-four
real
acceleration
time
histories
compatible
with
the
earthquake
hazard
in
terms
of
probable
magnitude
(M=6.5-7.5),
epicenter
distance
(R=20-40
km),
and
fault
mechanism
(strike
slip)
recorded
on
stiff
site
conditions
with
average
shear
wave
velocities
(
V
530
)
larger
than
420
m/s
are
selected
as
the
probable
input
acceleration
time
histories
from
the
PEER
strong
motion
data
bank
17].
Selected
acceleration
time
histories
are
scaled
with
respect
to
PGAs
estimated
from
the
seismic
hazard
analysis
for
each
cell
before
being
used
as
outcrop
motions
in
site
response
analyses.
Scaled
time
histories
for
one
cell
are
shown
in
Fig.
1.
The
local
site
conditions
are
characterized
based
on
an
extensive
site
investigation
study
conducted
in
the
area
with
at
least
one
soil
boring
conducted
at
each
cell
location
along
with
in-
hole
PS-Logging,
surface
seismic
wave
measurements
and
laboratory
index
tests
124].
All
available
information
on
geological
and
geotechnical
conditions
is
evaluated
to
determine
one
representative
soil
profile
with
shear
wave
velocities
extending
down
to
engineering
bedrock
(V
5
>
750
m/s)
for
each
cell.
Typical
soil
profiles
obtained
for
Zeytinburnu
are
illustrated
in
Fig.
2.
The
variation
V
5
30
in
Zeytinburnu
as
determined
from
the
detailed
soil
profiles
is
shown
in
Fig.
3.
Empirical
shear
modulus
and
material
damping
ratio
curves
that
were
used
to
define
dynamic
properties
of
soil
types
are
given
in
Table
1.
Site
response
analyses
are
performed
for
24
acceleration
time
histories
for
the
representative
soil
profiles
in
each
cell
using
Shake91.
The
averages
of
24
values
of
PGA,
PGV,
and
acceleration
response
spectra
from
24
Shake91
runs
for
each
cell
are
Fig.
8.
Variation
of
peak
ground
velocity
(PGV)
by
the
Hazus
formula
using
long
Fig.
6.
Variation
of
peak
ground
velocity
(PGV)
from
site
response
analyses.
period
(T=1
s)
spectral
accelerations
(S
I
)
estimated
by
NEHRP
site
amplification
factors.
Fig.
7.
Variation
of
short
period
(T=0.2
s)
spectral
accelerations
(S
s
)
from
site
Fig.
9.
Variation
of
short
period
(T=0.2
s)
spectral
accelerations
(S
s
)
estimated
by
response
analyses.
NEHRP
site
amplification
factors.
DISTRIBUTION
OF
BUILDING
TYPES
B112,
RC
(1-4}
stories
B122,
RC
(6-8)
stories
B132,
RC
(9-more)
stories
B212,
Masonry
11-4)
stories
B222,
Masonry
16-8)
stories
°kap.
gigi
lh
irra.
4"4
1
11 3
6
"
.
1
`:t
ittif,?1,1dv"
.;
O
/1111(173:
O
OOO
g
fah.
:111.40•••••
.1
is
I
117
4
11
F
A
a
Jr
II
7,r
**
A
r
preiLL
,
ti
urn..
.41
,
"'i
ofxr:Aril
wirwsr-
-
.
1,
4
1
ritfrt
4
4
4)
14.
r
,
*
IT
."1-
71'
1
Ira
aft
.rtfell*
.
r
3
21.1
Errie1/40t.,‘
0,-*---
E
l
i
M
rItil
l
ik0
i
ft>
.
..
lava
1141
714
k
1
4
4
.
4
Vaiitt
441%61
IV
IP%
arm.
TAV
‘&
42
.-"
4
4
.
le.$1
1
=Al
°
.
g
40
0
ve..7
1
a
Iti
t
ta
*•6
4
'
--
rar
.
,**
h-rise
lE
r,
0.9
0.3
0.7
,*
.."
0.9
0.1
0.7
O
(r-
cs)
0.6
0.6
o
-rise
E
rs
0.5
0.5
DAMAGE
Stiht
LEVEL
(Pre-1980)
4
•'
>
0•
4
0.4
(Post
i
s
-1980)
0.3
(Pre-1990)
Moderate
0.3
(Post-1980)
*
0.2
t
Extensive
(Pre-1980)
-1980)
0.2
(Post
0.1
_
Complete
(Pre-1980)
-1980)
0.1
.
(Post
0
6
10
15
20
25
30
35
40
45
50
5
10
15
20
25
30
35
40
45
Spectral
Displacement
(cm)
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
50
0
5
10
15
20
25
30
35
40
45
50
Mid-r
e
1324
A.
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
determined
to
define
the
variation
of
ground
shaking
parameters
due
to
the
probabilistic
seismic
hazard
scenario.
The
short
and
long
period
spectral
accelerations
(S
s
and
S
1
)
are
obtained
through
optimization
for
the
best-fit
NEHRP
envelope
spectrum
as
shown
in
Fig.
4.
Resulting
microzonation
maps
showing
variations
of
site-
specific
PGA,
PGV,
and
S
s
values
in
Zeytinburnu
are
shown
in
Figs.
5-7,
respectively,
along
with
the
distribution
histograms.
The
variations
of
PGV
and
S
s
can
also
be
calculated
empirically
based
on
V
5
30.
S
s
and
Si
can
be
obtained
by
using
the
procedure
proposed
by
Borcherdt
[11]
as
suggested
in
NEHRP.
PGV
can
be
determined
using
Hazus
formulation
that
relates
Si
to
PGV.
Figs.
8
and
9
show
variation
of
PGV,
and
S
s
,
respectively,
as
obtained
through
NEHRP
based
empirical
procedures.
Comparisons
of
variations
presented
in
Figs.
6
and
7
with
those
given
in
Figs.
8
and
9
show
that
the
use
of
equivalent
shear
wave
velocity
to
estimate
the
effects
of
site
conditions
may
yield
very
different
S
s
and
PGV
amplitudes
that
may
not
always
be
on
the
Fig.
10.
Distribution
of
building
types
in
Zeytinburnu.
RC
frame
type
buildings
Fig.
11.
Vulnerability
relationships
for
reinforced
concrete
frame
buildings.
Building
type
Total
number
of
buildings
Damage
level
(number
of
buildings)
None
Slight
Moderate
Extensive
Collapsed
SR
NH
SR
NH
SR
NH
SR
NH
SR
NH
RC
low
rise
3394
449
534
563
854
1054
1265
729
538
599
203
RC
mid-rise
10,306
526
452
2236
3063
3707
3865
2384
1789
2083
1137
RC
high
rise
(132)
144
4
7
31
49
34
37
39
31
35
21
Masonry
low
rise
(212)
1821
238
262
359
476
444
514
357
334
423
235
Masonry
mid-rise
(222)
22
2
1
5
6 6
8
4 4
5
3
All
15,687
1219
1256
3194
4448
5245
5689
3513
2696
3145
1599
bin
32
I.
3
g
33
tadismed1iniamtoduited.
olcaupee
Buildngi
=1=I
ZEYTINBURNU
MUNICIPALITY
NUMBER
OF
COLLAPSED
BUILDINGS
BASED
ON
SITE
RESPONSE
ANALYSES
O<NCB<=1
1
<NCB<=
5
E
5
e.
NCB
<=
10
10
<
NCB
<=
20
20
<
NCB
<=
30
30
<
NCB
<=
50
50
<
NCB
<.
100
NCB
>
100
13
I I
4
5
CO,
with
DilfwmtNuirlm's
of
Col.wrsed
ElOWIng,
ZEYTINBURNU
MUNICIPALITY
NUMBER
OF
COLLAPSED
BUILDINGS
BASED
ON
NEHRP
0
<
NCB
<=
1
1
<
NCB
<=
5
L
5
<
NCB
<=
10
1
10
<
NCB
<=
20
I5
20
<
NCB
<=
30
30
<
NCB
<=
50
A
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
1325
Table
2
Damage
distribution
for
different
building
types
in
Zeytinburnu.
SR:
using
site
response
analysis;
NH:
using
NEHRP
amplification
factors.
Fig.
12.
Distribution
of
collapsed
buildings
in
Zeytinburnu
estimated
using
results
of
site
response
analyses.
Fig.
13.
Distribution
of
collapsed
buildings
in
Zeytinburnu
estimated
using
NEHRP
factors.
safe
side.
The
observed
differences
between
Figs.
6
and
8
as
well
as
between
Figs.
7
and
9
indicate
the
importance
of
methodology
employed
in
estimating
the
effects
of
site
conditions.
3.2.
Vulnerability
analyses
for
buildings
and
pipelines
A
detailed
building
inventory
from
street
surveys
for
approxi-
mately
16,000
buildings
is
considered
in
the
evaluation
of
seismic
vulnerability
of
Zeytinburnu
125].
Building
inventory
is
divided
into
groups
based
on
the
construction
type,
number
of
stories,
and
construction
year
of
buildings
126,27].
All
buildings
are
classified
according
to
a
'Bijk'
matrix
where
"
i
"
shows
the
construction
type
as:
(1)
reinforced
concrete
frame
building,
(2)
masonry
building,
(3)
reinforced
concrete
shear
wall
buildings,
and
(4)
precast
building.
The
number
of
stories
("j"
dimension
of
the
matrix)
is
defined
as:
(1)
low
rise
(1-4
stories,
including
basement),
(2)
mid-
rise
(5-8
stories,
including
basement),
and
(3)
high-rise
(8
or
more
stories,
including
basement).
The
construction
date
("k"
dimension
of
the
matrix)
is
defined
as:
(1)
construction
year:
pre-1980
and
(2)
construction
year:
post-1980.
The
building
inventory
classified
according
to
'Bijk'
matrix
in
the
town
of
Zeytinburnu
is
shown
partly
in
Fig.
10.
The
available
inventory
in
Zeytinburnu
indicates
that
almost
all
of
the
buildings
are
mid-rise
reinforced
concrete
frame
buildings.
Region-specific
vulnerability
relationships
125]
that
relate
spectral
displacements
to
building
damage
for
each
building
type
are
used
to
estimate
damage
in
Zeytinburnu.
Fig.
11
illustrates
the
displacement-based
fragility
curves
for
low-rise,
mid-rise
and
high-rise
reinforced
concrete
frame
buildings
constructed
before
and
after
1980.
The
distribution
of
number
of
buildings
at
each
damage
state
for
all
building
types
in
the
area
are
computed
and
displayed
in
maps
showing
number
of
buildings
at
each
cell
for
a
given
type
of
building
and
damage
state.
A
summary
of
all
results
from
damage
evaluation
is
presented
in
Table
2.
Numbers
of
buildings
at
each
damage
state
estimated
using
NEHRP
amplification
factors
are
also
given
in
Table
2
to
provide
direct
comparisons.
Distribution
of
total
number
of
collapsed
buildings
in
Zeytin-
burnu
obtained
using
site-specific
ground
shaking
parameters
is
shown
in
Fig.
12.
The
variation
of
number
of
collapsed
buildings
estimated
based
on
NEHRP
amplification
factors
is
given
in
Fig.
13.
ZEYTINBURNU
MUNICIPALITY
TOTAL
DAMAGE
RATIO
BASED
ON
SITE
RESPONSE
ANALYSES
Ei
0.0
=
DR;
NONE
0.0
<
DR
<=
0.25;
SLIGHT
0.25
<
DR
<=
0.50;
MODERATE
0.50
<
DR
<=
0.75;
EXTENSIVE
0.75
<
DR
<=
1.00;
COMPLETE
EL
11—MIE:
M.
7111EL_
t
-
REPAIR
RATEIrprainkrnI
REPAIR
RATE
(RR)
BY
SITE
RESPONSE
ANALYSIS
o<
RR
(repairfkm)
<=
0.5
0.5
<
RR
(repair/km)
<=
1
1
<
RR
(repairfln)
<=
2
NATURAL
GAS
STEEL
PIPELINES
0
1
2
kilometers
I
1326
A.
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319-1328
A
comparison
of
Figs.
12
and
13
clearly
indicates
that
there
are
variations
in
the
distribution
of
damage
within
the
investigated
region
which
cannot
be
detected
when
the
site
conditions
and
their
effects
are
evaluated
using
NEHRP
site
classification
and
related
amplification
coefficients.
In
order
to
demonstrate
the
extent
of
expected
damage
in
Zeytinburnu,
a
representative
damage
ratio
is
calculated
for
each
cell
by
DR
=
(0*N
tione
+
0.25*N
s
li
g
h
t
+0.50
*
Nmoderate
0.75*Nextensive
+
1*
Ncollapse)
(4)
where
N
one
,
N
ight
,
Nmoderate,
Nextensive
and
Ncoapse
are
total
number
of
buildings
(includes
all
building
types)
at
none,
slight,
moderate,
extensive
and
collapsed
damage
states,
respectively,
within
that
particular
cell.
The
variation
of
DR
in
Zeytinburnu
is
shown
in
Fig.
14.
The
natural
gas
pipeline
inventory
of
Zeytinburnu
area
is
compiled
based
on
information
provided
by
Istanbul
Gas
Distribution
Industry
and
Trade
Co.
Inc.
(iGDAS).
The
inventory
is
consisted
of
length,
diameter,
and
material
properties
of
the
main
steel
pipeline
system.
Empirical
correlations
listed
in
Table
3
that
relates
PGV
to
pipeline
damage
is
used
to
estimate
repair
rate
and
number
of
repairs
in
the
pipeline
system
due
to
wave
Fig.
14.
14.
Variation
of
total
damage
ratio
representing
the
extent
of
damage
for
all
building
types
in
Zeytinburnu.
Table
3
Empirical
pipeline
vulnerability
relations
available
in
KoeriLossV2.
Empirical
relation
Factors
Reference
RR
(repair/
PGV
(cm/s),
K:
1
if
brittle
material,
O'Rourke
km)=0.0001
*
K
*
PGV
2
'
25
K:
03
if
ductile
material
and
Ayala
[33]
RR(repair/
PGV
(finis),
K:
coefficient
depending
Eidinger
1000
ft)=0.00032
*
K
*
PGV
1
'
93
on
material
type
and
Avila
[34]
RR
(repair/
PGV
(finis),
K:
coefficient
depending
ALA
[35]
1000
ft)=0.00187
*
K
*
PGV
on
material
type
RR(repair/km)
PGV
(cm/s),
PGS=ground
strain,
K:
O'Rourke
=K
*
513
*
PGS"
9
1
if
brittle
material,
K:
0.3
if
ductile
and
material
Deyoe
[36]
Fig.
15.
Distribution
of
predicted
repair
rate
in
natural
gas
pipeline
system
in
Zeytinburnu.
propagation.
Numbers
of
expected repairs
at
each
cell
are
calculated
as
the
product
of
repair
rate
and
total
pipeline
length.
Damage
distribution
maps
showing
the
variation
of
repair
rate
is
presented
in
Fig.
15.
4.
Simplified
versus
site
response
analysis
The
comparison
between
the
spectral
accelerations
calculated
from
site
response
analyses
using
the
best
envelope
fitting
procedure
with
those
values
calculated
by
the
NEHRP
formulation
indicates
that
the
values
obtained
by
site
response
analyses
have
much
larger
scatter
as
shown
in
Fig.
16.
The
difference
in
the
data
range
is
much
more
significant
for
short
period
spectral
acceleration
values.
Larger
scatter
observed
in
the
results
obtained
from
site
response
analyses
may
be
the
indication
of
more
accurate
determination
of
site
effects.
NEHRP
site
classification
based
on
equivalent
shear
wave
velocity
yields
only
two
site
classes
in
the
case
of
Zeytinburnu.
This
is
partly
due
to
the
fact
that
shear
wave
velocity
ranges
used
in
the
NEHRP
site
classes
are
defined
within
relatively
large
ranges.
The
variability
of
the
calculated
parameters
to
be
used
for
the
vulnerability
assessment
of
the
building
stock
is
an
important
factor.
Considering
the
variability
taken
into
account
by
assigning
different
earthquake
characteristics
for
each
cell
and
the
differ-
ences
in
the
soil
profiles,
it
appears
logical
to
use
the
spectral
acceleration
values
obtained
from
site
response
analysis
for
the
vulnerability
assessment.
However,
it
is
also
possible
to
argue
that
the
sophistication
introduced
during
this
process
may
not
always
give
more
correct
or
accurate
results.
In
addition,
the
decision
of
using
one
of
the
spectral
accelerations
determined
by
best
envelope
approach
would
play
a
very
important
role
on
the
amplitude
of
the
estimated
vulnerability
of
the
building
stock.
A
similar
comparison
can
also
be
made
with
respect
to
PGV
values
that
could
be
an
important
parameter
in
estimating
damage
distribution
in
pipeline
systems.
As
can
be
seen
in
Fig.
17,
the
difference
is
significant
with
PGV
values
calculated
by
the
Hazus
formula
being
almost
always
lower
than
those
calculated
from
site
response
analysis.
"me
±Nsught±Nmoderate+Nextensive+Ncollapse)
2.5
2.0
1.5
1.0
0.5
-
0.0
0 0
0.5
1.0
1.5
2.0
2.5
Spectral
Accelerations
at
T=1
s
Sp
ec
tra
l
Acce
lera
tions
by
Site
Resp
onse
(g
)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0.0
Spectral
Accelerations
at
T=0.2
s
0.5
1.0
1.5
2.0
2.5
3.0
35
Sp
ec
tra
l
Acce
lera
tions
by
Site
Resp
onse
(g
)
150
E
2
120
0
o.
rt
o
60
to'
3
To
30
0
o.
90
0
A
Ansal
et
al.
/
Soil
Dynamics
and
Earthquake
Engineering
30
(2010)
1319
-
1328
1327
Spectral
Accelerations
by
NEHRP
(g)
Spectral
Accelerations
by
NEHRP
(g)
Fig.
16.
Correlation
between
short
and
long
period
spectral
accelerations
(S
s
and
Si)
calculated
by
site
response
analyses
and
by
using
the
empirical
approach
of
NEHRP.
0
30
60
90
120
150
PGV
calculated
by
HAZUS
formula
(cm/s)
Fig.
17.
Correlation
between
peak
ground
velocities
(PGV)
calculated
by
site
response
analyses
and
by
using
the
empirical
formulation
of
Hazus.
5.
Conclusions
A
methodology
for
performing
urban
damage
scenarios
for
buildings
and
pipeline
networks
where
local
site
conditions
are
taken
into
account
by
performing
large
number
of
'ID
site-specific
ground
response
analyses
is
presented.
The
methodology
is
developed
into
a
software
tool
and
application
to
a
district
in
Istanbul,
Turkey
demonstrated
that
there
are
significant
varia-
tions
in
the
ground
motion
parameters
within
the
investigated
region
which
cannot
be
detected
when
the
site
conditions
and
their
effects
are
evaluated
using
NEHRP
site
classification
and
related
amplification
coefficients.
Therefore,
it
appears
essential
to
perform
site
response
analyses
to
have
more
accurate
information
on
ground
shaking
characteristics
for
microzonation
and
for
the
estimation
of
seismic
damage
in
buildings
and
lifeline
systems.
Acknowledgements
The
authors
would
like
to
acknowledge
the
support
and
contributions
of
all
their
colleagues
in
the
Earthquake
Engineering
Department
of
Kandilli
Observatory
and
Earthquake
Research
Institute,
specifically
of,
Prof.
M.
Erdik,
Prof.
N.
Aydinoglu,
Prof.
E.
Durukal,
M.
Demircioglu,
Dr.
K
Sqetyan,
and
U.
Hancilar.
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