ASIAN DISASTER REDUCTION CENTER

FINAL REPORT“Earthquake Building Risk Assessmentin Sana’a City, Yemen ”

Prepared by:

Moneer Abdulla Al-Masni
Seismological and Volcanological Observatory Center (SVOC)

Ministry of Oil & Minerals

VISITING RESEARCHER (ADRC)
Aug. to Nov. 2012 (FY2012A)

1

Disclaimer
This report was compiled by an ADRC visiting researcher (VR) from ADRC member
countries.
The views expressed in the report do not necessarily reflect the views of the ADRC. The
boundaries and names shown and the designations used on the maps in the report also do
not imply official endorsement or acceptance by the ADRC.

2

or acceptance by the ADRC.

Table of Contents

1. Significant and Background
2. Aims
Aims of Research
3. Description of study ward
3-1 Geographical Location and Topography
3-2 Geology and Tectonic
3-3 Earthquakes in Yemen and Sana’a region.

4. Identified
Identified Yemenis Building Types
4-1 Un Renforcement Masonry Structures (URM)
4-2 Renforcement concrete
oncrete frame Structures (RM)
4-3 Building Distributions.
4-4 Seismic level Design in Buildings..

5. Earthquake Building Risk Assessment

5.1 Development of Earthquake Scenarios.
5.1.1 Assuming Dhamar Earthquake Scenario:
5.1.2 Assuming Dhamar Earthquake Scenario:

5.2 Deterministic Seismic Hazard Assessment
5.2.1 Soil conditions:5.2.2 Seismic ground motion model :5.2.3 Intensity Based Deterministic Earthquake Hazard
5.2.4 Site Dependent Intensities Spectral Accelerations
5.3 Building Vulnerability Assessment
5.3.1 Building Vulnerability Definitions
5.3.2 Building inventory
5.3.3 Building Damage Analysis
5.3.3.1 Spectral Displacement Based Fragility Curves
5.3.3.2

Analytical Basis of Fragility Curves

5.3.3.3

Analytical Basis of Structural Capacity

5.3.3.4

Estimation of Structural Capacity and Fragility Curves

5.3.3.5

Estimation of Spectral Displacement Demand

5.3.3.6

Damage probability of all five model building types

6. Discussion and Results of Earthquake Buildin
Building
uilding Risk Assessment
7. Appendix A

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1. Significant and Background:
Earthquakes are one of the most dangerous, destructive and unpredictable natural
hazards, which can leave everything up to a few hundred kilometers in complete
destruction in seconds.
Reducing urban earthquake risk involve three stages, evaluation, planning, andimplementation. This research focused on the risk evaluation stage which considers very
important stage for doing the next stages. As well as, this stage is necessary needed for
improvement disaster management system in Yemen which have attention only on postdisaster response.
Sana’a city in Yemen is one of the oldest cities in the worlds, which has different forms ofbuilding built with different types of materials. In the present work, the old and newforms of building construction and the building materials are used for damage analysis.
Sana’a city has high priority attention due to several considerations. It is represent thecapital of Yemen, contain one of the oldest city in the world and housed more than
1,750,000 people(Central Statistical Organization,2005).
During the last tow decades, the city has been growing and expanded by more than 3times its area in 1982, in both vertically and horizontally to provide housing, business andman-mad structures .
On the other hand, historical records mentioned that it was subjected by destructive
earthquakes in the past periods (742 BC,1644 and 1908) with equivalent magnitudes
between (M 4.0- M

6.0). As well as, it was not far from impacts of the strongest

earthquake (Mw6.2) which occurred in Dhamar in 13, Dec.,1982 ,70km south Sana’a,caused a big damage in livelihoods and property in Dhamar and large scale fractures in
Dhamar and Sana’a basins.
Further more, many of small earthquakes of magnitude less than 4.2 occurred on the
period(1995-2012) highly felt by most of peoples because, Sana’a city situated on a thick4soft alluvium sedimentary basin that acting to amplify the seismic ground motion andmake weak buildings more vulnerable to damage caused by moderate earthquakes.
For estimation the potential damage of an expected future earthquake, theoreticalestimation is performed by combining the seismic intensity distribution that is estimatedfor the adopted earthquake with the inventory of the structures and infrastructure of thecity. This combination is performed using vulnerability functions that are developed toreflect the seismic behavior of the structures and infrastructure found in the city.

2. Aims
Aims of Research:esearch:In the absence of attention to the pre-disaster planning, the current research aims toassess building damage prediction at Sana’a city by developing historical earthquake
scenarios and investigate the behavior of buildings during destructive earthquakes. As
well as to provide the a common basis for governmental and other agencies to rising the
preparedness and planning the best emergency response at city level.

3. Description of study area
3.1 Geographical Location and Topography:
Topography:
The city is situated on Sana'a basin which is considered one of the most important
deposits basins in the central highlands. The basin located at the area between( 44 º 10‵,44º 37‵E) & (15 º 10‵,15 º 28‵N) , reach to 2300m above sea level and covers an
area estimated to 3200km2. Sana'a basin is characterizing by tectonic valleys features
which is surrounded by mountains of many breaking edges, flow propellers, faults andvolcanic cones forming dikes and ash overlaying alluvial sediments. Figure.1 shows
location and (3D) view proposed by satellite image show geomorphology of Sana’a basin.

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Figure.(1) Location and (3D) view proposed by satellite image show geomorphology of Sana’a basin

3.2 Geology and Tectonic
The geology of Yemen is related to the regional geology of the Arabian Peninsula, which ispart of Arabian-Nubian plate in a structural sense. In late Pre-Cambrian, the Arabianshield joined to the African shield by plate collision. During the Paleozoic-Mesozoic time
the Pre-Cambrian basement is depressed and an extensive marine platform developed on
the northeastern part of the Arabian shield. Both the plates drifted to the north east6

closing the Tethyan seaway. In mid Tertiary period, the Afro-Arabian plate collided with
the Eurasian plate forming the Zaggros Mountains and the Iranian fold belt. At the sametime, the Arabian plate was detached from the African plate by the Aden-Red Sea rift.
The morphological features of the country, formed largely as a result of the tectonic andvolcanic activities during the Tertiary, were modified to some extent during the
Quaternary period. The overall geological structure of Yemen is dominated by the
Precambrian Arabian Shield in the western part of the country and an extensive and thickcover of Phanerozoic sub-horizontal sediments further east. Figure 2, shows generalgeological map developed on a 1:1 million scale. The geological settings of Yemen arecharacterized by the wide variety of main rock units, which range from Precambrian to
Quaternary. In the southern and western regions of Yemen, the Precambrian crystalline
basement and its older sedimentary cover are uplifted and partly exposed (Arabian
Shield-zone). The Tertiary volcanic is also associated with westerns region. Whereas theeastern part of Yemen consists mainly of Paleozoic, Mesozoic and Cenozoic sediments.
In the particular of Sana’a basin geological, there are five significant rock Formations
outcropped in the surface of Sana'a basin. The first, is Al- Tawilah (Cretaceous-Paleocene)
Sandstone formation, outcrops to the west and north east parts of the Sana’a basin. The
second, is Amran Limestone Formation, outcrops to north of Sana’a basin. The third, is
Yemen Volcanic (Tertiary Stratoid) Formation, mostly Ryolitic Yellow Tuff and Basalts,
outcrops

and widely spread in west and south east of study area. The fourth, is

Quaternary Basalt consists of massive and sheet rock outcrops in the center andnorthwest of Sana’a basin. Quaternary volcanic cones forming dikes and ash overlaying
Al-Tawila sandstone. The fifth, is Quaternary thick alluvium sediments plain, outcrops in
the middle of the basin and covered 500km2.
In respect to tectonic features in Sana`a basin,

Al- Ubaidi and Al-Kotbah

reported that three main tectonic fracture trends was
7(2003),

recorded in the basin. The firstone is NE-SW which represent the old trend and probably rejuvenated from Hajaz
Orogeny,

the second trend is NW-SE which represent the most dominant fracturesand major faults results in the formation of Jurassic basins and were accompanied withcompressional strike slip and thrust faults which rejuvenated from Najid fault system,and the third and youngest trend is E-W which coincides with the trend of the Gulf ofAden. However, the old fractures of Jurassic and Cretaceous are obscured by the youngest
trends of the Red Sea and the Gulf of Aden where all localities are highly dissected bythese two trends. Figure. 3. shows the surface lithology and structures of Sana'a basin.

Figure.(3) Geological units and Tectonic feature Map of Sana’a basin

83.3 Earthquakes in Yemen and Sana’a region.
Yemen is located in the seismically active zone between the Arabian and African tectonic
plates which are pulling apart. The
western and southern portions of
Yemen around the rifts of the Red
Sea and Gulf of Aden represented
byvolcanic

mountainsovermagmatic champers. These portions
Figure.(4)Figure.(4) Historical Earthquakes Map (742(742-1900)

are the most active seismic zones withmoderate to strange level and at risk from earthquakes. Figures.4. and 5. states historicaland recent seismicity maps respectively. Although the magnitudes of these events are
small but it is felling by peoples living in that areas due to topography and geologicalcondition of Yemen.
On 13 December 1982, a destructive earthquake rocked a large area of Dhamar provinceof Yemen, causing widespread damages and loss to the life .Figure. 5 show seismic
intensity map of Dhamar earthquake. This moderate, shallow earthquake that occurredin a densely populated region about 70 km south of Sana’a, resulted in 2,500 deaths andinjured 1,500 people and damaging more than 70,000 dwellings.

As well as, the shockwaves were perceptible as far as Jizan, Najran and Taiz, all at an average distance of 230
In particular of Sana’a seismicity , the historical records mentioned that it was subjectedby destructive earthquakes in the past

Figure.(5) Recent Earthquakes Map (1900(1900-2007)

periods (742 BC,1644 and 1908) with equivalent magnitudes (M5.0, M5.7 and M6.0)
respectively. As well as, it was not far from impacts of the strongest earthquake (Mw6.2)
which occurred in Dhamar in 13, Dec.,1982. Further more, many of small earthquakes ofmagnitude less than 4.2 occurred on the period(1995-2012) highly felt by most of peoples
94. Identification
Identification of Building Types
Types at Sana’a City :4.1 Buildings
Buildings Spatial Distribution.
The district level residential building data of Sana’a city, obtained from Central Census
Organization CCO (2004) includes general information’s about population and number ofdwellings. It is noticed that thebuilding data base inventory notaccurateenough.

number ofFor

example,dwellings includes

numberofapartments

doesn’tcontainanditgeographicallocation and age of each building.
Further more, there is no details
information on buildings materials
type and number of stories forbuildings

constructed

at

each

district level.
Therefore, for approximate analysis,
weassumeddistributionbyuniform
usingbuildingthe

only

Figure.(6Figure.(6) Distinct Building distribution map

available information of total percentage, for each building material types and stories
numbers at Sana’a basin (Amana Area) .Figure 6. building distribution map at each
district level in Sana’a basin.

4.2 Building Material type and Construction Technique :Seismic performance of a building influences by construction material and technique.
Construction technique is largely depending upon the availability of building material
10used for building construction and economic conditions of the building owner . The
socio-economic conditions of the people defines the type and construction quality of thebuilding and divided building patterns in to three types. Firstly the independent houses
which were built for residential purposes and second the group housing like apartmentswith multiple purpose use .Third industrial, office and commercial building.
Most of the buildings in Sana’a doesn’t follow any regulation and are not constructedbased on seismic design building code. For example, independent houses or
single-family-residences are built by locals who don’t involve architects and engineers andit is mostly based on traditional methods . Whereas group housing like apartmentcomplexes etc. for multiple purpose use, industrial offices and commercial building.
designed with seismic considerations and it is strong enough to resist lateral forces ofminor quakes but not strong enough and don’t meet the building standards .
Even though buildings is only planned for few floors in the initial stages , years later,
more floors are added to the same building which makes the structure weak and more
vulnerable to earthquake hazards. The dominated construction techniques used in Sana’
City are load bearing construction and RC framed construction. Table 1. shows thecommonly building materials used in construction of load bearing structure andRC framed structures at Sana’a City. A building constructed of Stone/Blok/Brick in
cement mortar will behave much better than constructed of Stone/Blok/Brick in mud
mortar.
Table 1. shows the commonly building materials used in construction
Construction

Structural

Techniqueelement

Load bearing

Stone/Blok/B

Wall materialType of

Roof material

Floor Materialmortar
Stone/Blok/Brick

Mud, cement

RBC,GI,RCC

RBC,RCC

Stone/Blok/Brick ,RCC

Cement

RCC

RCC

rick column
RC framed

RCC column,
beam

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For building types classification, the buildings with the same material andconstruction type are grouped into one class. The main classes in Sana’a as explained
below:

4.2.1 Un Rei
Reinforcement Masonry Structures (URM)
These buildings represents approximately (47 %) of Sana’a building city and constructedof stone , block ,clay or burned brick withcement or mud mortar as shown in Figure.7.
Itdoesn’thave

anyseismic

designconsiderations and therefore, it falls underpre-code category of HAZUS classifications
In Sana’a ,old heritage structures all buildings
constructed of burnet bricks and clay and arealso vulnerable to earthquake hazards.

Figure.(7) URM Masonry Building (Brick(Brick ,stone and clay

4.2.
.2..2 Reinforcement Masonry Structures (RM)
These buildings represents approximately (53%) of buildings in Sana’a city . Based on
HAZUS technical Manual prepared by FEMA(2011) the structures concrete frame buildings
with unreinforced masonry infill walls is definedas RM building class as shown in Figure.8 and 9.
The frames can be located almost anywhere in
the building. Usually the columns have theirstrong directions oriented so that some columns
act primarily in one direction while the others
act in the other directions. In these buildings,
the shear strength of the columns, after
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Figure.(8Figure.(8) RM structure , RC filled with stonecrackingofsemi-ductile

theinfill,behavior

of

may

limit

the

the

system.

Inearthquakes these building fail and lead topartial or fall collapse because of brittle failure
as

these

are

only

designedwithductileproperties. Buildings with some level of seismic
design were considered but they do not match
Figure.(9Figure.(9) RM structure , RC filled with stone

with the suitable level of building codes and therefore, were considered as low-code
category of HAZUS classifications

4..3 Building Seismic Design level :To resists the internal forces caused by earthquakes, it is helpful if the materials perform
well both in compression and in tension. Materials, which perform well only incompression, are often reinforced by other materials with good tensile strength qualities..
Unfortunately, no building codes are available for Yemen and the default was to adopt thecodes used in the USA (with the necessary modifications). As well as, impossible ofdevelopment the empirical curves for Yemenis building types, because of absent ofanalytical functions and due to lack of sufficient damage data in previous earthquakes
Therefore, this research is used the default fragility and capacity parameters that given in
HAZUS building types as alternative case following HAZUS methodology.
with consideration to procedures of Prasad et al.(2009) study for identifying and classify
the building types due to similarity between Indian and Yemeni’s building construction
and material types.
Prasad et al.(2009) compared the classified Indian building types to the HAZUS modelbuilding types

as shows in Table 2, and found out that Indian framed structures have

similarity with US buildings and can consider some of it with in low to moderate code of13the HUZUS building types. whereas, the Indian adobe and masonry building types can
not compared to any of the fragility curves that are given in default HAZUS building types
and it is considered pre-code.

Table 2. Comparison between classified Indian building types to the HAZUS model Prasad et.al.(2009)14

5. Earthquake Building Risk Assessment
Building damage caused by earthquakes contributes to disasters and causes casualties
and fires. Earthquake damage to buildings is greatly influenced by the types of buildings.
There are various ways to classify buildings, namely by materials, construction type,building age, story or height and usage, etc. It is desirable to adopt the classification basedon the factors that closely correlates to observed past damages. However, since detailedbuilding information is not available in many cases, a general classification is often used.
We used the following classification categories, adopted based on HAZUS methodology
which calculates the building damage in terms of probability of damage of particularmodel building types for each damage states. The probability of damage is calculated inrelationship with given ground motion parameters to evaluate the building performancefor a particular seismic event.
The StrucLoss 1.5 Software- developed by Earthquake and Structural Department ofGebze Institute of Technology, Turkey - is used for risk assessment analysis in Sana’a city.
The general process of damage estimation from assumed earthquake scenarios issummarized in this section and illustrated by the Figure.10. below.

Figure (10) diagram show the methodology used for risk assessment
155.1 Development of Earthquake Scenarios.
The objective of creation earthquake scenario is to describe the results of the damage
estimation in a comprehensive and easy to understand manner.
In the present research two synthetic earthquake scenarios were simulated around
Sana’a basin as shown in Figure 11. These scenarios seems to be the most important due
to their reoccurrence interval for such an event is every hundred to thousand years . As
well as, it considers the strongest events locate very close to Sana’a city. More details ofthese assumed scenarios as mention below:

5.1.1 Assuming Hamdan Earthquake Scenario:
This is the first simulation scenario, called "Hamdan Earthquake Scenario" this event
mentioned in historical documents that hit Sana’a and adjacent areas in 1644 withequivalent magnitude to Mw = 6.0 and caused several damages and losses . It was set atthe location 15.40N 44.00E and 20km west Sana’a city.

5.1.2 Assuming Dhamar Earthquake Scenario:
The second scenario called "Dhamar Earthquake Scenario" hit Dhamar in 13 Dec.,1982 .
It is consider as modern strong earthquake with magnitude Mw6.2, depth 7km andepicenter located at 14.7°N and 44.2°E. and 70km south of Sana’a. This event hit Dhamar
and adjacent area caused a lot of damage and earth cracks in Dhamar and Sana’a. The
shock waves were perceptible as far as Jizan, Najran and Taiz, all at an average distanceof 230 km.
HamdanEQ
Figure 11
shows thelocation ofearthquakes

Sana’ cityused forscenario
damageassessment

16

DhamarEQ

5.2 Deterministic Seismic Hazard Assessment
The geological and seismological information are the basis for appropriate simulation, andthese are usually given in broad terms, involving the location, magnitude, rupture length.
And attenuation relation. Attenuation models provide the severity of the ground motion in
respect to the source magnitude and mechanism, distance to the epicenter and local soil
effects.

5.2.1 Soil conditions:
For estimating the local soil effects, the present study used the site geotechnicalclass-map of Al-Subai et al. (2006) and site effect study using Microtremor array survey(SPAC) by Al-Masni et al.(2008) to estimate average shear wave velocity (Vs30) in
quaternary deposits. Whereas, (Vs30) of geological rock units such as Igneous,
Metamorphic, Volcanic, and old sedimentary rocks was calculated from the information'sof standard typical values of P-wave velocity structure range, Nick, Barton , (2007) andcorrelated with the Vs30.
Then, geological unites are divided to five classes, from hard rock (A) to soft rock (E) as
shown in Fig.( ?) according to the classification system recommended by the National
Earthquake Hazard Reduction Program (NEHRP) (FEMA, 1997).

5.2.2 Seismic ground motion model :Deterministic hazard was evaluated using both intensity and ground motion parameters(PGA and SA) based on appropriate attenuation relationships following below. For bothcases the median (50-percentile) value obtained from the used attenuation relationships
was adopted. The selected ground motion parameters of analysis are the Peak GroundAcceleration (PGA) and the Spectral Acceleration (SA) at periods of 0.2, 0.3 sec and 1.0
sec . A comparison of the attenuation relationships of Ambraseys et al. (1996) and Boore etal. (1997) with New Generation Attenuations (Abrahamson and Silva, 2008, Boore andAtkinson, 2008, Campbell and Bozorgnia, 2008, Chiou and Youngs, 2008) are plotted in
Figure 12. For near source conditions, Ambraseys et al. (1996) attenuation highly17overestimates the peak ground acceleration. In this study, for earthquake scenario I andII, Boore et al. (1997) andaverage of Boore et al. (1997) & Ambraseys et al. (1996) isutilized for the calculation of the PGA and SA for the periods: 0.2, 0.3 and T = 1.0 sec
Based on HAZUS99 recommendations peak ground velocity (PGV) has been calculated
from SA at T=1.0 using the following formula: 386 . 4

PGV = ⋅ S Al  / 1 . 65
 2λ
Where SA1 is the spectral acceleration in units of g, at T=1.0sec.
10
Ambraseys et al (1996)
Boore et al (1997)
Abrahamson-Silva (NGA 2008)
Boore-Atkinson (NGA 2008)
Campell-Bozorgnia (NGA 2008)
Chiou-Youngs (NGA 2008)

PGA (g)

1

0.1

0.01
0.1

1

10

100

Closest Distance, R (Km)
Figure 11: Comparison of PGA Attenuation Relationships for soil type B

5.2
5.2.2.1 Intensity Based Deterministic Earthquake Hazard
The empirical relationships between PGA, PGV and Modified Mercalli Intensity (MMI) of
Wald et al. (1999) which were developed for the San Andreas Fault area, were
investigated for the estimation of the intensity attenuation using the following equations:

Imm = 3.66*log PGA -1.66, for V ≤ Imm ≤ VIII
Imm= 3.47*log PGV + 2.35, for V≤ Imm ≤ IX
18

The average for these equations was favorably comparable with the isoseismal maps ofthe previous earthquakes (i.e Dhamar,1982). However, comparing these results against
PGA-MMI relationships used for Greece, Turkey and Palestine (Bendimerad, 2008 Personal communication) proved to be significantly conservative for all PGA levels,
suggesting that intensities may be under-estimated. Based on local studies, Bendimerad(2003-Unpublished) suggested a PGA-MMI equation for the region:

Imm= 1.6 * Ln PGA+ 0.545 * Mw +5.78

Figure 13. shows a comparison between the results based on equations of Walid et al. (1999)
and Bendimerad (2008) for a magnitude of 7.5 against distance. Accordingly, deterministic
modeling of the seismic hazard is calculated in terms of the distribution of site-dependent
intensities, based on the intensity attenuation of Bendimerad (2003).
10
9.5

Wald_Soil_B
Bendimerad_Soil_B

9

Wald_Soil_C
Bendimerad_Soil_C

8.5

Wald_Soil_D
Bendimerad_Soil_D

Imm

8
7.5
7
6.5
6
5.5
5
0

10

20

30

40

50

60

70

Distance (Km)

Figure 13: Comparison of the intensity for different soil types using Wald (1990), based on the
average of PGA and PGV, and Benimerad (2003) equations.
19

5.2.2.2.2.2.
.2. Site Dependent Intensities Spectral Accelerations
Spectral accelerations (SA) for T=0.2, 0.3 and 1.0 sec will be modified according to the1997 NEHRP Provisions (FEMA, 1997) of site coefficients presented in Tables 3. and 4.
These amplified spectral accelerations are later used in the construction of the standard
shape of the response spectrum. The standard shape of the response spectrum is taken
equal to the so-called “Uniform Hazard Response Spectrum” provided in 1997 NEHRP
Provisions (FEMA, 1997). This spectrum, which is employed to assess the demand on
structures (for vulnerability analysis), is approximated with the site-specific short-period(Sms) and medium-period (Sm) spectral accelerations as illustrated in Figure 14. Sms and Sm

are represented by the calculated SA at T=0.2 sec and T=1.0 sec, respectively. using given
formula.
Ln ( (S A ) = b1 + b 2 ( M − 6 ) + b 3 ( M − 6 ) 2 + b 5 Ln ( r ) + bvLn (Wherer 2jb + h

r =

Vs
)
VA

2

And



b1 = 


20

b 1 ssFor strike-Slip earthquakesb 1 Rv

For reverse Slip earthquakesb 1 allIfmechanism not specifiedSA

is spectral acceleration to be derived

b1,b2,b3,b5,bv

are constants provided with the equation

M

is the magnitude of the earthquake

rjb

is the horizontal distance from epicenterVs

the shear wave velocity of the soil class provided by NEHRP classification

Table 3.: Short period site-correction definedin the 1994 and 1997 NEHRP Provisions (BSSC, 1995 &1998).
Site Class

Ss≤0.25 Ss=0.50 Ss=0.75 Ss=1.0 Ss≥1.25

A

0.8

0.8

0.8

0.8

0.8

B

1

1

1

1

1

C

1.2

1.2

1.1

1

1

D

1.6

1.4

1.2

1.1

1

E

2.5

1.7

1.2

0.9

-

F

-

-

-

-

-

Table 4: Long period site-correction definedin the 1994 and 1997 NEHRP Provisions (BSSC, 1995 &1998)
Site Class

S1≤0.1 S1=0.20 S1=0.3

S1=0.4

S1≥0.5

A

0.8

0.8

0.8

0.8

0.8

B

1

1

1

1

1

C

1.7

1.6

1.5

1.4

1.3

D

2.4

2.0

1.8

1.6

1.5

E

3.5

3.2

2.8

2.4

-

F

-

-

-

-

-

Figure 14. Standard Shape of the Response Spectrum (FEMA, 1997).
21

5.3 Building Vulnerability Assessment
Earthquake vulnerability of a building is defined as the amount of expected damage
induced to it by a particular level of earthquake intensity. Vulnerability is a function ofmagnitude of an event and the type of elements at risk. The more elements at risk thehigher will be the vulnerability.
There are two methods for the analysis of building vulnerability; namely qualitative andquantitative methods. The qualitative method is based upon the statistical evaluation of
past earthquake damage. This method is suitable for non-engineering buildings that havethe same type of building character. The quantitative method is based upon the numericalanalysis of the structure. The buildings with the same material and construction type aregrouped into one class. The performance of the buildings is predicted based upon design
specifications and construction details. Using these curves damage description is provided
for each building class in each damage state including: None, Slight, Moderate, Extensive
and Complete (Figure 15 andFigure エラー! 指定したスタイルは使われていません。).

Figure 15: Structural vulnerability and damage states for various levels of seismic demand.

22

Figureエラー! 指定したスタイルは使われていません。: Uncertainties in seismic performanceand use of fragility curves.

Construction of the fragility or damage curves is the key element in estimating theprobability of various damage states in buildings or building components as a function of
the magnitude of a seismic event..

5.3
5.3.1 Building Vulnerability Definitions
The European Macroseismic Scale (Grünthal, 1998), differentiates the structuralvulnerabilities into six classes (A to F). Reinforced Concrete buildings with low levels ofearthquake resistant design are assigned an average vulnerability class of C. Due to
deficiencies in design, concrete quality, lack of direct engineering supervision, andconstruction practices, the bulk of the reinforced concrete building stock in Sana`a may beconsidered in this vulnerability class.
Table エラー !

指定したスタイルは使われていません。. and Figure 4.3 illustrate thedifferent damage grades of reinforced concrete buildings (Figure 15). Similarly, Coburnand Spence (1992) incorporated these classes into the definition of the state of damage ofmasonry buildings (Table 6).
Table

エラー! 指定したスタイルは使われていません。: Damage grades definition(Grünthal, 1998)

Grade
D1
23

Description
Negligible to slight damage (No Structural Damage (SD), SlightNon-Structural Damage (NSD))
D2Moderate damage (Slight SD, Moderate NSD)

D3

Substantial to heavy damage (Moderate SD, Heavy NSD)

D4

Very heavy damage (Heavy SD, very heavy NSD)

D5

Total Destruction.

Table 6: Damage grades of reinforced concrete buildings (Grünthal, 1998)
Damage Grade

Masonry Buildings

D1-Slight

Hairline cracks

Panels cracked (Non-structural)

D2-Moderate

Cracks 0.5-2cm

Structural Cracks <1cm

D3-Heavy

D4-Partial
Destruction

Cracks >2cm or wallmaterial dislodged
Completecollapseofindividual wall or roof
support

D5-Collapse-

RC Buildings

Heavy damage to structural members, loss of concreteComplete collapse of individual structural member or
major deflection of structure

Failure of structural members to allow fall of slabs.

Moreover, Grünthal (1998) tied the grade of damage of reinforced concrete buildings
with low levels of earthquake resistant design with the definitions of earthquake
intensities Table 7.

Table 7: Definitions of earthquake intensities tied to the grade of damageof reinforced concrete buildings (Grünthal, 1998).

Intensity

Damage Description*

Intensity VI

A few buildings of vulnerability class C sustain Damage of grade 1.

Intensity VII

A few buildings of vulnerability class C sustain damage of grade 2.

Intensity VIII

Many buildings of vulnerability class C suffer damage of grade 2; a few of grade 3.

Intensity IX

Many buildings of vulnerability class C suffer damage of grade 3; a few of grade 4.

Intensity X

Many buildings of vulnerability class C suffer damage of grade 4; a few of grade 5.

*Where “Few” describes less than 20% and “Many” describes between 20% and 60%.
For the general indication of vulnerability in different earthquake intensity zones;
Coburn (1987) defined the following damage percentages of various building material24

of heavy damage to collapse classes (Table 8).

Table 8: Vulnerability of building stock in different hazard zones (Percent Damage).

Percent Damage for Building Type
Io(MSK)

Poor Masonry

Good Masonry

RC

>=D3

D5

>=D3

D5

>=D3 D5

>IX

90%

50%

60%

5%

50%

1%

VIII

75%

5%

50%

1%

5%

-

VII

50%

1%

5%

-

1%

-

It can be said that existing vulnerability functions vary in there response according to
the building structure and associated building materials.

5.3
5.3.2 Building
Building inventory
For an effective estimation of damage to buildings, a building classification is necessary.
Buildings may be classified according to various parameters. For example, building
may be classified according to their material types, usage, age, structural types andlocal building codes, etc. Development of realistic fragility curves for the building stockand lifelines in Sana’a building inventory is essential for seismic risk analysis such as
damage, social and economic losses. In HAZUS (FEMA, 2003; FEMA, 2006a, b), thebuilding inventory classification system is utilized to group buildings with similar
characteristics into a set of pre-defined building classes, commensurate with therelevant vulnerability relationship classes. For a general building stock, the Structural(e.g., height); Nonstructural elements; and Occupancy (e.g., residential, commercial,and governmental) are the parameters that affect and characterize the damage andloss.
Overall, the HAZUS presents four main building types: wood, masonry, concrete and25steel, and these can be further subdivided into 36 classes according to the buildingheight and seismic design level (for more details see HAZUS Technical Manual,
chapter 3).The HAZUS building damage functions, which are formulated as fragility
curves, describe the probability of reaching or exceeding discrete states of damage forthe structure and nonstructural systems. The states of the damage are: None, Slight,
Moderate, Extensive and Complete. Descriptions of these damage states are found in
the HAZUS Technical Manual (FEMA, 2003; FEMA, 2006a, b).
Since there are no damage functions available for Yemen, the present study used thedefault capacity and fragility parameters functions given by the HAZUS for all types ofloss. The building stock used in this research consists of about 260,000
buildings/Dwellings based on Census tract 2004 . The stock was classified in to fivegroups according to types of construction materials, year of built, the number of stories
and the seismic design level. As well as, the total buildings number for each class has
been computed. Figure 17. shows the statistical classification of the buildings based on
constriction materials and number of stories in term of Low- rise , Mid- rise and High-rise buildings.
The simulations of the loss estimation were thus based on these groups, ranging fromthe worst-case scenario that included the URM-Pre code, up to the RM –Low code.
These two building types set the maximal and minimal loss estimations, suggesting
the actual damage should be somewhere in between. In order to improve and perform abetter and more accurate estimation of the losses, it is essential to develop the local
damping, capacity and fragility curves typical for the Yemeni building types. Following
an explanation procedure for modeling the buildings based on type, height and age(Seismic Design Consideration ).

Construction Type ( I )1. Reinforcement concrete building filled with masonry block.
2. Reinforcement concrete building filled with masonry stone..
26

3. Masonry (Stone/concrete Block) buildings
4. Masonry (Bricks) buildings
5. Masonry (Clay) buildings

Number of stories ( J )1. Low -rise (1-3 stories)
2. Mid -rise (4-6 stories)
3. High-rise (more than 6 stories)

Construction date ( K )1. Construction year: Pre-1982
2. Construction year: Post-1982

Figure 17. shows the Results of buildings classification based on constriction materials andnumber of stories in term of Low- rise , Mid- rise and High -rise buildings

5.3
5.3.3 Building Damage Analysis
Analysis
Buildings respond to ground shaking in earthquakes. As buildings are tied to theground with foundations, the free end i.e., roof shakes more than the ground. There is27

always some inbuilt strength to resist this shaking. But when it reaches it maximum
levels, it tends to reach its upper limit and finally collapses. Till a limit, in built
strength of the building resist the shake and allow the building remains stiff and standstraight , this is called yield capacity point. When building reaches it is yield capacity it
starts to shake to a limit and at a stage the building loses it complete strength and canno longer resist the force of shaking and structural system completely fails. That point
before losing all strength to shake is called ultimate capacity point. The capacity curveis generally derived from two points.
Kircher et al. (1997) describes capacity and fragility curves functions which are used by
HAZUS methodology for estimating damage from ground shaking caused byearthquakes. Capacity curves define the non-linear behavior of buildings which aredescribed by the yield and ultimate strength and on the other hand the probability
level of damage to the buildings at given ground shaking level is predicted by thefragility curve.
In this study building damage analysis calculated based on spectral displacement asfollowing steps:

5.3.3.1 Spectral Displacement Based Fragility Curves
In spectral displacement-based fragility curves, the horizontal axis represents the
spectral displacement demand and vertical axis refers to the cumulative probability ofstructural damage reaching or exceeding the threshold of a given damage state.
Therefore, it is required to determine the spectral displacement demand of a given
structure for a given earthquake action.

5.3.3.2 Analytical Basis of Fragility Curves
The analytical expression of each fragility curve is based on the assumption thatearthquake damage distribution can be represented by a lognormal distributionfunction (FEMA 1999, Kircher et al. 1997):

28

P [D ≥ ds | Sdi] = Φ [(1 / βds) ln (Sdi / Sd,ds)](

われていません。.1)

エラー! 指定したスタイルは使where D refers to the damage, Sdi is the inelastic spectral displacement demand, Sd,ds
represents the median value of spectral displacement corresponding to the threshold of
the damage state reached – ds (slight, moderate, extensive or complete), βds is thestandard deviation of the natural logarithm of the spectral displacement corresponding
to the damage state concerned. Φ refers to cumulative standard normal distributionfunction. Median spectral displacement values corresponding to each damage state,Sd,ds , are estimated in terms of story drift ratios specified for each building type. On theother hand, the standard deviation βds is empirically estimated to cover theuncertainties associated with the definition of the damage level concerned, the building
load capacity and the earthquake ground motion specified.

5.3.3.3 Analytical Basis of Structural Capacity
The use of spectral displacement-based fragility curves require the spectral
displacement demand of a given structure be determined for a given earthquake action.
In HAZUS damage estimation methodology (FEMA 1999), the spectral displacement
demand for a given structural type is essentially estimated on the basis of Capacity
Spectrum Method (ATC-40, 1996). In this method, inelastic structural capacity of thestructure is represented by the so-called “capacity spectrum” (capacity diagram)plotted in terms of spectral acceleration versus spectral displacement.
The capacity diagram of a given structure can be readily estimated through its “yield
spectral acceleration”, Say, which is defined as (ATC-40, 1996):

Say =

Vy
M x1

(5.2)

where Vy represents the base shear capacity at yield and MX1 refers to the participating
modal mass effective in the first mode of vibration. The latter is defined as:29

M x1 =W
α1 (g

エラー! 指定したスタイルは使われていません。

5.3)
in which W represents the total seismic weight of the structure, g is acceleration ofgravity and α1 refers to participating mass ratio.
On the other hand the base shear capacity at yield can be estimated as:

Vy
W

ん。.4)

= Cs γ λ (エラー! 指定したスタイルは使われていませwhere Cs is the approximate value of the estimated design lateral strength factor
assumed to be valid for the date of construction (this factor is not necessarily related tothe seismic coefficient defined in the codes), γ and λ are the approximate “over-strength
factors” estimated according to the date of design/construction. The factor γ represents
the ratio of the yield strength to the design strength whereas factor λ is defined as theratio of the ultimate strength to the yield strength. Building capacities are based on
best-estimate approximate factors supported by engineering judgment, without any
analysis performed.
Thus, from Eqs 4.4, 4.5 and 4.6 the yield spectral acceleration is obtained as

Say = Cs γ λ

g

α1

(

エラー! 指定したスタイルは使われていません。.5)
A typical capacity diagram is shown in Figure 18, which is idealized to represent anelastic-perfectly plastic behavior. The slope of the initial line corresponds to the squareof the natural frequency, which is related to the natural period as ω = 2π / T.

30

Figure 18. Typical capacity diagram

5.3.3.4 Estimation of Structural Capacity and Fragility Curves
This study adopts the spectral displacement procedure explained above and the risk
assessment analyses for buildings are performed using StrucLoss Software. The
algorithms and the methodology used in the software are given in Appendix A. Table(8 ) shows the initial starting values of capacity and fragility curves parameters fordifferent building classes were adopted from HAZUS-MH (2003).

Table 8: Left table show , Building fragility parameters and right table Building capacity

parameters315.3.3.5 Estimation of Spectral Displacement Demand
In the Capacity Spectrum Method (ATC-40, 1996), the spectral displacement demand
is obtained through the intersection of the capacity spectrum with the so-called“demand spectrum”. The concept of demand spectrum rests on the idea of reducing theelastic acceleration spectrum with an equivalent viscous damping of a linear
single-degree-of-freedom (SDOF) system represented by its secant stiffness. There has
been a debate since the inception of the method on whether the empirically defined
spectrum reduction factors are representative of the inelastic behavior of theequivalent SDOF system. In fact, Chopra and Goel (1999) reported that the Capacity
Spectrum Method based the approximate demand spectrum generally overestimates
the response by a significant margin. Similar findings are also reported in ATC-55,
2001. The Demand Spectrum is generated by the Equation given by Boore et al. (1997)
given below.

Ln ( (S A ) = b1 + b 2 ( M − 6 ) + b 3 ( M − 6 ) 2 + b 5 Ln ( r ) + bvLn (

Vs (
)
VA

エラー! 指定したスタ

イルは使われていません。.8)
then from the equation spectral acceleration SA is derived. Then SD is calculated fromthe equation given below:

SD = 9.8 * SA * T2(

ん。.9)
SA
T

32

エラー! 指定したスタイルは使われていませis the spectral Acceleration calculated from the first equationis the time period in seconds as given in the constants provided with the equation

Response or Demans Spectrum at As Sabain District
0.14
0.12

)g
(a
S 0.1
onti
ar 0.08
lee
cc
0.06
A
la
re
tc0.04
ep
S0.02

系列1

0
0

0.1

0.2

0.3

0.4

0.5

0.6

Specteral Displacement Sd(inch)

Figure 19 : show response or Demand spectra at Sana’a(Assabain) area

5.3.3.6 Damage probability of all five model building types
The damage probabilities of all five model building types were calculated by method
explained above. The damage probability matrix was thus derived for allmodel-building types for all damage states by using damage algorithm described inAppendix A. Table 9. provides an example of discrete damage probabilities derived fromcumulative probabilities given in the example Figure 20.
The damage probability represent the performance of five model building type for a low
seismic design code and pre- seismic design code.

Figure 20 show an example of vulnerability curve of RC type high-rise buildings

33

GＲＩＤ_ID
ＲＩＤ_IDＳ１

ＳＳ

ＮＤ２３２Ｎ

ＮＤ２３２Ｉ

ＮＤ２３２Ｓ

ＮＤ２３２Ｍ

ＮＤ２３２Ｅ

ＮＤ２３２Ｃ

ＮＤ２３２Ｔ

1301.0

0.046

0.106

0.0

0.0

0.0

0.0

0.0

0.0

0.0

1302.0

0.044

0.100

165.9

0.0

46.4

11.8

2.3

0.3

226.7

1303.0

0.047

0.108

78.5

0.0

25.4

7.0

1.4

0.2

112.5

1304.0

0.049

0.113

75.2

0.0

26.5

7.7

1.5

0.2

111.2

1305.0

0.052

0.120

208.9

0.0

81.6

25.2

5.1

0.8

321.6

1306.0

0.047

0.109

78.1

0.0

25.7

7.2

1.4

0.2

112.6

1307.0

0.047

0.107

53.7

0.0

17.2

4.7

0.9

0.1

76.6

1308.0

0.044

0.101

215.1

0.0

60.8

15.6

3.0

0.4

294.9

1309.0

0.043

0.098

134.2

0.0

36.1

9.0

1.7

0.2

181.3

1310.0

0.036

0.081

144.0

0.0

26.2

5.3

1.0

0.1

176.6

2301.0

0.020

0.065

28.4

0.0

1.2

0.1

0.0

0.0

29.8

2302.0

0.011

0.036

30.8

0.0

0.2

0.0

0.0

0.0

31.0

2303.0

0.012

0.037

12.9

0.0

0.1

0.0

0.0

0.0

13.0

Table 9. shows an example of discrete damage probabilities of RM H buildings derived from above Vulnerability cumulative curve

6- Discussion and results of Earthquake Building Risk Assessment
The results of expected damage on buildings calculated by HAZUS method, gave good results
at the broad level evaluation. However, the results seem not to be very accurate for fine levelrisk evaluation. The parameters like building response and damage curves of US based
building classes could be one of the major factors of getting these results. The accurate valuesof Yemini’s buildings capacity and damage function should be needed to get the more realistic
results of risk evaluation of buildings in study area. The difference in structural properties of
RM and URM classes with structural properties of framed and masonry buildings in study
area could be one other reason of getting inaccurate results of building damage.
The results of earthquake risk assessment calculated from both scenarios with considering
ground conditions of study area in Sana’a city are plotted in term of chart diagram in
Figures( 21,22.23 and 24 ). As well as the risk map are shown in Figure 25 for describe the34percent of complete damage at all five model buildings in the area. The graphs indicates thebuilding having structural properties similar to URML model building type is the mostvulnerable among all five model building types. Whereas buildings having structural properties
similar to RM class is least vulnerable to earthquake damage. On the other hand, the buildings
located above soft sediments site have higher damage and more vulnerable to risk comparing tobuildings located on hard rock . Figure 26. Shows soil amplification map.

Figure 21 Chart diagram shows Expected damage of RM buildings from Dhamar scenario

Figure 22 Chart diagram shows Expected damage of URM buildings from Dhamar Scenario

35

Figure 23 Chart diagram shows Expected damage of RM buildings from Hamdan scenario

Figure 24 Chart diagram shows Expected
damage of RM buildings from Hamdan scenario

36

Figure 25 left show Risk Map resulted

Figure 26 Soil amplification map atfrom Dhamar Earthquake scenario

Sana’a basin

Appendix A

StrucLoss 1.5 Software and algorithm37

(Updated Version of KoeriLoss 1.0)38StrucLoss 1.5 is an updated version of Koeriloss software. The updated version is developedby Earthquake and Structural Department of Gebze Institute of Technology, Turkey.
(http://www.gyte.edu.tr/Dosya/328/Software/StrcuLoss.htm ).
Four major developments are included in this version
1. Risk assessment of lifelines including water transmission pipelines, waste watertransmission pipelines, gas transmission pipelines, motorways and highways.
2. Integrate the deterministic hazard into the software for widely used attenuation
relationships computation is integrated.
3. Line by Line analyses procedure to replace the Grid by Grid procedure. Each line
contains a part of the Grid that included in the block. This procedure provides easy
and correct way to aggregate the different loss results to Block and Districts.
4. Provide Intensity based outputs of the results for each damage states of eachbuilding types. Calibration and testing the capacity curve and fragility curveparameters can be done more accurately and in fast way.
5. Initial input parameters file is included to allow the user to change the default
analyses parameters of the software

KoeriLoss 1.0 is developed by the Earthquake Engineering Department of Bogazici
University, Kandilli Observatory and Earthquake Research Institute (KOERI). The software
applies a loss estimation methodology developed by KOERI to perform analyses for
estimating potential losses from earthquakes. KoeriLoss Version 1.0 in its current form iscapable to perform building damage estimation analysis using both intensity and spectral
displacement based methodology. It is also able to estimate the direct economic losses andcasualties related to building damages.

StrucLoss 1.5 is user-friendly software that operates through Geo-cells systems. Geo-cells
39

(Grids) facilitate the manipulation of data on building stock, population and, earthquake
hazards. The software is developed using the MapBasic language and runs efficiently
under MapInfo software. Therefore, the software is fully integrated with MapInfo andcapable to utilize the powerful features in displaying, querying, manipulating and mapping
inventory databases. StrucLoss provides a great flexibility in displaying the outputs. Tablesof building damages, social and economic losses can be easily mapped and displayed on
the screen, printed or pasted into electronic documents.
Methodology and Algorithm
StrucLoss Estimation Methodology is the basis for the algorithm used to develop thesoftware. General algorithms for spectral displacement based loss estimation are shown in
Figure E1.
Classification of Building DataClassification systems are essential to ensure a uniform interpretation of data and results.
Building specifications used in the methodology have been developed to provide the ability
to differentiate between buildings with substantially different damage and loss
characteristics. The building inventory stocks can be classified using three categories:-Structural systems category (I)Example: I = 1 : RC frame building
I = 2 : Shear wall building
I = 3 : Masonry building- Number of building stories category (J)Example: J = 1 : 1 – 3 stories (including basement)
J = 2 : 4 – 6 stories (including basement)
J=3:> 6 stories (including basement)- Construction Year category (K)Example:40

K = 1 : Construction year: pre-1980 (included)

Example:K = 2 : Construction year: post-1980

Therefore any building type can be specified as I-J-K where I, J, and K refer to the structural
system, number of stories and construction year of the building respectively. To specify agroup of building type, wildcards can be used. If 0 is specified as I, J and/or K, all thebuilding types of that group will be considered. The building classification system is
discussed thoroughly in section 3.1.
Classification of Structural Damage
The structural damage of the buildings are classified in four groups:-(1) Slight damage-(2) Moderate damage-(3) Extensive damage-(4) Complete damage

Classification of Casualties
Casualties are classified in four categories of severity:-

Severity 1-

Severity 2-

Severity 3-

Severity 4

Output of the Analysis
The software deterministic hazard part provides the ground motion parameters (PGA, PGV,Intensity and Spectral Accelerations S0.2, S0.3, S1). The loss estimation part provide
building damage loss, economic loss and the number of casualties in terms of Geo-cells,
sub-districts (Blocks) and districts as MapInfo Output tables.
Lifeline
The lifeline loss assessment estimations are based on methodologies proposed by ATC-25,
41

HAZUS 2002, ALA 2001 and Japan waterworks associations.

Input Building

Input Spectral

Input Spectral

Calibration with

Inventory

Acceleration

Displacement

Intensity Based

Database forfor Geo-Cells

Based

Vulnerabilities

Input Capacity
Curve for each
Building Type

Compute Building Damage
Ratio for each Building
Types

Compute Number ofDamaged Buildings foreach building Class
Input
Economic
Loss Data

Input
Demographic

Compute Direct Economic
Loss for each Building

Compute Casualties foreach Injury Groups

Database for
Casualties

Economic

Buildings

Input

Losses for

Losses for

DamagesCasualties

geo-Cells,

geo-Cells,forLoss data

Sub-district

Sub-districtgeo-Cells, Districts, Districts,

Figure E1: General Algorithm of StrucLoss Software for Building Damage Estimation

42

Analysis Method

Options

Options

Icons

Input andControlStart
Analysis

StrucLoss 1.5 Main Window Dialog

43

Dialog Form for Deterministic Hazard and Analyses Parameters

Detailed Output Control of the Analyses for Deterministic Hazard and Building Losses
44Intensity based outputs of the results for each damage states

45

Buildings Structural Capacity Estimation and Fragility Curves Validation
Buildings Structural Capacity and Fragility Curves Parameters Estimation
Comprehensive procedure based on Pushover analyses is considered to estimate the initial
capacity curves and fragility curves parameters. The guidelines proposed in Chapters 5 and
6 of Hazus-MH-MR3 (2003) are followed when it is applicable. The estimation methodology
can be summarized as follows•

The buildings dimensions and detailing are based on average values for real buildings

designed and constructed by local engineering experience in Aqaba. The details of thebuildings used in the analyses are given below.
•

The skeleton type building is a type of R/C Moment Frame. The local engineer called itskeleton type because all the analyses and computations for the design forces are basedon continuous beams theory or approximate Hardy Cross’s moment distributions. The
standard R/C Moment Frame detailing of beams and columns are applied but with the lackof shear confinement at the beam-columns joints.
•

In 1990’s the engineering supervision for buildings and concrete quality were greatly

improved. This change influence a better design practice and engineering controls. In thisproject we consider 1990 as the year of change.
•

The pushover analyses are performed for typical buildings with average dimensions anddetailing. The analyses are done on typical representative building to initially estimate thecapacity and fragility curves parameters. The initially estimated parameters wereconsiderably updated using calibration process with the empirically based intensity data.
•

The structural analyses software SAP2000 V14 is used to model and analyze thebuildings structures. The Finite Element models and buildings details are plotted for eachbuilding class.
•

Frame elements are used to model beams and columns, while main pier-rigid beammodels are utilized for shear walls.
46

•The stiffness of brick based infill walls is ignored and their masses and weights are

considered in the models.
•The stiffness of stone-concrete infill walls are considered based on the works of Royal

Scientific Society, Building Research Center (2003) and Al-Nimry H S. (2010).
•

The cracked section properties for beams and column are considered for modal andPushover analyses.
•

The hinge M3 properties for the beams and PMM hinges properties for the columns arecomputed based on FEMA 356 recommendations for concrete beams using the existing
concrete type and reinforcing steel rebars.
•

The hinge PMM properties for columns are based on FEMA 356 recommendations forthe existing reinforcements details and the nonlinearity for the shear walls are considered
as main pier-rigid beam system as explained in Fahjan et al (2010). A standard detailing of
the shear walls are shown in Figure C1 below.
•

The nonlinear behavior of stone-concrete infill walls are modeled using approximate

nonlinear link model for old and new constructions as shown in Figure C.2 below. The
nonlinear link models properties are computed based on the experimental works of
Al-Nimry H S. (2010).
•

The hinges for beams and columns are located at both ends of the members.

•

To include the effect of soft stories in the buildings classes (B421, B422), the first floor

are considered to be much higher than the upper stories. The stone-concrete infill walls aremodeled using nonlinear link elements.
•

To ensure a convergence in the analysis for the three dimensional models with many

irregularities such as shear-walls elements and infill elements; the moment-rotation curvefor the hinges is assumed to be elasto-plastic with no load drop. Even though, the approach
may lead to monolithic increase in capacity, it has minimum effects on resulting plastic
rotations and drift ratio. This approach is recommended in contemporary codes as Turkish Earthquake Code (2007).

47

•

The Pushover capacity curves for each building type in both X and Y directions are given for each building class.

•

The spectral yield acceleration, Say, estimated from pushover capacity curve is equivalent to ultimate capacity, Au,

defined in Hazus99.
The building natural fundamental period is estimated from the modal (eigenvalues) analysis results of SAP2000. The•

average of X and Y directions are approximated.
The fragility curve mean spectral displacement values are estimated by computing the drift ratio from the base•shear-roof displacement of the pushover curve, utilizing the drift ratio proposed by Hazus MH (2003) to define Slight,
Moderate, Extensive, Complete damage states. The drift ratios used to determine the mean spectral displacement are
given in .4.12 for each building class together with the corresponding building type in HAZUS.
The initial values of fragility curves Beta β (βc ,βT,ds) are utilized the values proposed in Hazus MH (2003) and those•

proposed in GAM.
Typical Drift Ratios Based on HAZUS-MH (2003) for Different Building Classes

Building
HAZUS Building Type

SlightModerate

Extensive

Complete

Class
B111

C1-Low-Rise (Low Code)

0.005

0.008

0.020

0.050

B112

C1-Low-Rise (Low Code)

0.005

0.008

0.020

0.050

B121

C1-Mid-Rise ((Moderate Code)

0.003

0.006

0.015

0.040

B211

C1-Low-Rise (Low Code)

0.005

0.008

0.020

0.050

B212

C1-Low-Rise (Low Code)

0.005

0.008

0.020

0.050

B221

C1-Mid-Rise (Low Code)

0.003

0.005

0.013

0.033

B222

C1-Mid-Rise (Low Code)

0.003

0.005

0.013

0.033

B311

C1-Low-Rise (Moderate Code)

0.005

0.009

0.023

0.060

B321

C1-Mid-Rise ((Moderate Code)

0.003

0.006

0.015

0.040

B411

C1-Low-Rise (Low Code)

0.005

0.008

0.020

0.050

B421

C1-Mid-Rise (Low Code)

0.003

0.005

0.013

0.033

B422

C1-Mid-Rise (Low Code)

0.003

0.005

0.013

0.033

B512

C1-Low-Rise (Low Code)

0.005

0.008

0.020

0.050

48

0.6 m

3.5 m

Φ10@0.2 m

8Φ14

0.25m
0.25 mΦ10@0.2 m

P

M3
M2

Plastic (P-M-M Interaction) hinge
Figure C1: Example of reinforcement distribution in the shear wall and column members
and PMM plastic hinge49