Journal of Natural Disaster Science, Volume 29, Number 2, 2007, pp73-81

73

Evaluation of the Structural Fragility of a Bridge
Structure Subjected to a Tsunami Wave Load
Gaku SHOJI and Tetsuo MORIYAMA
Department of Engineering Mechanics and Energy, Graduate School of Systems andInformation Engineering, University of Tsukuba(Received for 1 June., 2007 and in revised from 24 Oct, 2007)

ABSTRACTIn this study, the structural fragility of a bridge structure due to a tsunami wave load is evaluated, quantitatively
analyzing the damage data of bridge structures due to the 2004 Tsunami in Sri Lanka and in Indonesia, which areon basis of 58 data on Sri Lanka and 17 data on Sumatra. By the formulation of a fragility curve of a bridge structure from statistical analysis of the data, the structural fragility of a bridge structure due to a tsunami wave load,
which describes the relation between the tsunami damage classification of a bridge structure and a tsunami wave
load such as inundation depth and inundation height, is revealed.

1. INTRODUCTION
A giant earthquake of M 9.1, whose hypocenter was locatedfar off the northern part of Sumatra island in Indonesia, occurredon December 26th, 2004 (UTC 00:58:53) (USGS, 2007). The
tsunami induced by the earthquake caused catastrophic damage incountries surrounding the Indian Ocean such as Indonesia, Sri
Lanka, Thai, India, Malaysia, and Myanmar. The main reason forthe damage is that as well as masonry and wooden houses necessary for the dairy life of inhabitants being severely affected bytsunami wave loads, infrastructure such as transportation facilities,
electricity power supply systems, and water treatments were also
affected structurally and functionally. For instance, along the east,
south, and southwest coastline of Sri Lanka of a total about 1,000
km, and along the northwest coastline of Sumatra of more than 250
km, road infrastructure was affected by the tsunami, and various
damage patterns, which are classified into washout and movementof a superstructure, minor damage, and scouring and erosion of soil
embankments around abutments, were observed dependent on thetsunami wave height.
Such infrastructure systems play a crucial role for the stakeholders involved in a tsunami disaster in responding at the stage ofcrisis management even after an event as well as in reconstruction
and rehabilitation management; it is important to use road infrastructure for the evacuation of inhabitants and first-aid for wounded persons, for transportation of emergency materials to affectedareas, and for dispatch of associated expertise at the above stages.
In consideration of the high risk associated with a tsunami disasterin Japan that is feared with the anticipated Tokai, Tohnankai, andNankai Earthquake, the development of a framework of tsunami
risk assessment for infrastructure is significantly required.
Many valuable studies on the fragility evaluation of a structure
due to a tsunami have been conducted mainly in the field of seismology as well as and coastal and hydraulic engineering. Amongthese, Hatori (1984) clarified the relation between the damage percentage of a wooden house with an inundation height on the basisof previous tsunami damage data such as the 1933 Sunriku and the1960 Chile Tsunamis, and Shuto (1993) first introduced the tsunami fragility curve of a wooden house based on analysis of theresults by Hatori (1984). Matsutomi and Shuto (1994) analyzed
the relation between the damage level of a reinforced concrete(RC) house, a concrete bloc house, and a wooden house with aninundation height from assessment of tsunami damage data of the1993 Hokkaido-Nanseioki Earthquake. From the viewpoint ofevaluation of tsunami wave velocity, which is the other important
index of a tsunami wave load, Matsutomi and Iizuka (1998) theoretically formulated equations to evaluate tsunami wave velocity
on basis of the results of their hydraulic experiments. In addition,from the viewpoint of evaluation of tsunami wave force on a structure, Matsutomi and Oomukai (1999) evaluated the drag force acting on a house on the basis of a series of hydraulic experiments.
Mizutani and Imamura (2000) showed a framework of evaluationof tsunami wave pressure on an inclined structure such as a shore
protection structure, and Asakura et al. (2000) proposed a model todescribe tsunami wave pressure on a structure when a tsunami runs
up across a shore protection structure. Furthermore, experimental
and numerical studies were conducted to clarify the hydrodynamic
force acting on a house in groups of houses due to flood- or tsunami- induced flow (Fukuoka et al., 1997, Iizuka and Matsutomi,
2000). However, these researchers dealt with tsunami wave loads
affecting houses and costal infrastructure such as a shore protection
structure, whereas there is insufficient research dealing with tsunami damage to road infrastructure, although results on the basis of afield survey of road structures in Indonesia and in Sri Lanka were
promptly reported even after the 2004 Tsunami in the Indian Ocean(e.g., Iemura et al., 2005, Unjho et al., 2005, Shoji and Mori, 2006,
Kosa et al., 2006).
For the reason above, in this study, the structural fragility of a

KEY WORDS: 2004 Giant Earthquake and Tsunami in the Indian Ocean, bridge, structural fragility, tsunami wave load

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G. SHOJI AND T. MORIYAMA

bridge structure due to a tsunami wave load is evaluated, quantitatively analyzing the damage data of bridge structures due to the2004 Tsunami in Sri Lanka and in Indonesia, on the basis of 58
data on Sri Lanka and 17 data on Sumatra. From the statisticalanalysis, the relation between the probability of tsunami damage toa bridge structure to a tsunami wave load such as the inundation
depth and the inundation height is revealed.
2. FRAGILITY CURVE
Failure probability Pf of a bridge structure due to a tsunami isderived as probability P (C £ R) so that the response of a bridge due
to a tsunami R (bridge response) becomes equal to and larger than
the resistance of a bridge against a tsunami C (bridge resistance) as
follows:
Pf = P(C £ R) = P( X =C£ 1.0)
R(1)

where R is the function R (rm, δr) of median rm and coefficient ofvariation δr of the bridge response, and C is the function of C (cm,δc) of median cm and coefficient of variation δc of the bridge resistance. X is the random variable to present the ratio of bridge resistance C to bridge response R, and then X is assumed to be logarithmic normal distribution. Hence, probability density function fx
associated with X is derived as follows:fX =È 1 Ï ln x - (ln c - ln r ) ¸ 2 ˘mm
exp Í- Ì˝ ˙x2p ◊ x ◊ x
ÍÎ 2 Ó˛ ˙˚1(2)

where ξ is the logarithmic standard deviation:x = ln(1 + d c2 )(1 + d r2 )By the modification of Eq. (5), the damage probability of abridge structure in relation to a tsunami wave load will be modeled
mathematically as a fragility curve as shown in the following chapter.
3. TSUNAMI FRAGILITY ASSESSMENT OF A
BRIDGE STRUCTURE
3.1 SUBJECT DATA
(1) DAMAGE DATA OF BRIDGE STRUCTURES IN SRI
LANKA
Subject data used for fragility analysis are the damage data ofbridge structures collected in Sri Lanka by Shoji and Mori (2006).
These bridges are located along the southwest and south coast of
Sri Lanka as shown in Fig. 1. Shoji and Mori (2006) collected andarchived 60 data that contain the information shown in Table 1: thestructural failure mode of subject bridges due to a tsunami, structural type, bearing type, span, length of deck, height of deck, total
width of deck, thickness of deck, distance from the coastline to a
subject bridge, the height from the still water surface level underthe bridge to the deck, and the inundation depth around a subject
bridge due to a tsunami. Based on the data, we classified the damage pattern of affected bridges from washout and fall-down of adeck (rank A), movement of a deck or damage to an abutment due
to scouring and erosion (rank B), minor damage to a deck attachment such as bridge railings (rank C), to no damage (rank D) as
shown in Table 2.
Fig. 2 shows the structural type, span, and bearing type of subject bridges and Fig. 3 shows a schematic view of two affected
bridges, Akurala Bridge in Paraliya and Magalle Bridge in Galle
City, to introduce rank A and rank B damage to one of the bridges
in Sri Lanka. A quantitative index to present a tsunami wave load
on a bridge structure in mechanics is the inundation depth around a
subject bridge as previously mentioned. The value of an inunda-

From Eq. (1) and Eq. (2), failure probability Pf of a bridge
structure due to a tsunami is derived as probability distributionfunction Fx of fx as follows:

Pf = FX = Ú01

È 1 Ï ln x - (ln c - ln r ) ¸ 2 ˘mm
exp Í- Ì˝ ˙dx (3)x2p ◊ x ◊ x
ÍÎ 2 Ó˛ ˙˚1Now, the variable transformation associated with X is performed as the following Eq. (4), and random variable Z is newly
defined as a parameter in order to calibrate the dimension of X bymultiplying X by median rm of bridge response R and to make Z thesame dimension as C:
Z = X ◊ rm =

C
◊r
R m

(4)

Substituting Eq. (4) for Eq. (3), failure probability Pf of a bridge
structure due to a tsunami is derived as the function of C:

Pf = FZ (rm ) = Ú0mr

ÏÔ 1 Ê ln z - ln c ˆ 2 ¸Ômexp Ì - Á
˜ ˝dz
x
¯ Ô
2p ◊ x ◊ z
ÔÓ 2 Ë˛
1(5)
Fig. 1 Subject road infrastructure in Sri Lanka

EVALUATION OF THE STRUCTURAL FRAGILITY OF A BRIDGE STRUCTURE SUBJECTED TO A TSUNAMI WAVE LOAD

Table 1 Structural characteristics and failure mode of subject bridges, and data on inundation depth around subject bridges in Sri Lanka

Table 2 Damage pattern of a bridge structure due to a tsunami

tion depth is defined as that of the height from the still water surface level under a subject bridge to the inundation line marked on ahouse located around a subject bridge where the inundation line
could be identified and measured during the survey. However,when it could not be, the value of the inundation depth is definedas that of the height from the still water surface level under a subject bridge to the inundation depth level over the bridge surface on
the basis of the associated information by hearings from inhabitants
living in houses around a subject bridge.

Fig. 2

Structural type, span, and bearing type of subject bridges in
Sri Lanka

75

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G. SHOJI AND T. MORIYAMA

Because the values of the inundation depth are those dependent on the tide level at the site of a subject bridge at the time of
day of the field survey, the values of the inundation depth were
adjusted to those on December 26th, 2004, using the method of
Tsuji et al. (2005), as follows (Fig. 4):
H = a + b−c(6)where H is the inundation depth adjusted as the value on December(a) Akurala Bridge

26th, 2004, a is the height from the still water surface level under asubject bridge to the inundation depth level over the subject bridgeat the time of day of the field survey, b is the difference in height
between the still water surface level at the time of day of the fieldsurvey and the minimum still water surface level, and c is the difference in height between the still water surface level on December
26th, 2004 and the minimum still water surface level. a is obtained
directly from the survey data, and b and c are the values of astronomical tide levels in Colombo and Galle numerically computed
by Tsuji et al. (2005). In Sri Lanka, these values are obtained atonly two sites, Colombo and Galle, and then, to adjust the value ofthe inundation depth at subject bridges located near Colombo(bridge nos. 1 to 23 in Table 1), the values of b and c are used as
those of astronomical tide levels in Colombo, whereas to adjust thevalue at subject bridges located near Galle (bridge nos. 24 to 58 in
Table 1), the values of b and c are used as those of astronomicaltide levels in Galle. However, two data of bridge nos. 59 and 60 in
Trincomalee associated with inundation depth are not adjusted by
Eq. (6) because the two sites of bridge nos. 59 and 60 are far fromeither Colombo or Galle. From the adjustment, Fig. 5 shows theinundation depth at the sites of the subject bridges, accompanying
related data collected by Tomita et al. (2005).
(2) DAMAGE DATA OF BRIDGE STRUCTURES IN
SUMATRA
Damage data of bridge structures in the northwest of Sumatra
Island in Indonesia, collected by the field survey team organizedjointly by members from the Japan Society of Civil Engineers(JSCE) and the Japan Association of Earthquake Engineering(JAEE) in the summer of 2006 (JSCE and JAEE field survey(b) Magalle Bridge
Fig. 3 Schematic view of affected bridges

Fig. 5

Fig. 4 Definition of inundation depth of a subject bridge in Sri Lanka

Analyzed data associated with inundation depth at the sitesof subject bridges in Sri Lanka

Fig. 6 Structural type and span of subject bridges in Sumatra

EVALUATION OF THE STRUCTURAL FRAGILITY OF A BRIDGE STRUCTURE SUBJECTED TO A TSUNAMI WAVE LOAD

team), as well as data of Sri Lanka, are used for structural fragility
analysis. Table 3, like Table 1, shows the data associated withstructural characteristics and damage to 27 subject bridges in
Sumatra due to the tsunami. The context of the data regarding thebridges in Sumatra in Table 3 (Sumatra data) is almost same asthat regarding the bridges in Sri Lanka in Table 1 (Sri Lanka data).
However, the data associated with bearing type, distance from thecoastline to a subject bridge, and height from the still water surface
level under the bridge to the deck are not collected in the Sumatra
data. Fig. 6 shows the structural type and span of subject bridges
in the Sumatra data. In assessing the Sumatra data, not the inundation depth but the inundation height around a subject bridge is usedas the quantitative index to present a tsunami wave load on a
bridge structure in mechanics. These data are measured by Tsuji etal. (2005) and Fujima et al. (2006). Fig. 7 shows the location ofsubject bridges and information on inundation height and tsunami
runup height in the northwest of Sumatra.
3.2 FRAGILITY ANALYSIS(1) DEVELOPMENT OF FRAGILITY CURVES
Now, fragility curves both in the Sri Lanka data and theSumatra data are developed by the modification of Eq. (5) as previously described in the Chapter 2. Fifty-eight data among 60 in the
Sri Lanka data, in which 2 data of unaffected bridges are included,
and 17 data among 27 in the Sumatra data, with the information on
inundation height around subject bridges, are used for fragility
analysis.
Cumulative damage probability Pci (i=rank A ~ rank D) of abridge structure due to a tsunami wave load, by which the damage
to affected bridges is classified as rank A to rank D as shown in
Table 2, is assumed to be the same as failure probability Pf of a77

bridge structure due to a tsunami, and random variable Z, which
describes the relationship between bridge resistance C with bridge

Fig. 7

Location of subject bridges and analyzed data associatedwith inundation height and tsunami runup height in thenorthwest of Sumatra

Table 3 Structural characteristics and failure mode of subject bridges, and data of inundation height and runup height around subject bridges in Sumatra

78

G. SHOJI AND T. MORIYAMA

response R, is assumed to be the variable to present a tsunami wave
load,
as follows: 1
ÏÔ 1 Ê ln z - m ˆ 2 ¸ÔziY
PC = Ú0exp Ì - Á˜ ˝dz
2p ◊ s Y ◊ zÔÓ 2 Ë s Y ¯ Ô˛(7)where μY and σY are mean and standard deviation of random variable Y, which is defined as the logarithm of random variable Z:
Y=ln Z. z means the value of Z. In assessing the Sri Lanka data, aninundation depth H (Fig. 4) is idealized as tsunami wave load Z,
whereas in assessing the Sumatra data, an inundation height H isidealized as tsunami wave load Z, as shown in Fig. 8. In addition,)
we have the relationship between μY and the median of Z, mZ , andthat between σY and the coefficient of variation of Z, Vz, as follows:)mY = ln mZ
s Y2 = ln(1 + VZ2 )normal distribution function) and ln z as described below.
The values of Pci are transformed into those of Φ-1 (Pci) by the
inversion of standard normal distribution function Φ, and those aredefined as observed data Φobs-1 (Pci). Then, linear regression linesΦfit-1 (Pci) to idealize the relation between observed data Φobs-1 (Pci)(vertical direction: y-axis ) and lnz (horizontal direction: x-axis) are
derived by the method of least squares, as shown in Figs. 9 and 10,
as follows:
F -fit1 ( Pci ) =ln z - mY1m=
ln z - YsY
sY
sY

Tables 6 and 7 show the values of the y-intercept (-μY/σY) andx y-inclination (1/σY) derived from Figs. 9 and 10, the coefficient(8)

Tables 4 and 5 show the frequency of damage rank i (i =rank
A ~ rank D) of subject bridges d i, its cumulative frequency dci, andicumulative damage probability Pc with the function of tsunami
wave load Z in the Sri Lanka data and the Sumatra data, respectively. The value of the section in which the range of inundation depth
is divided is 1 m in the Sri Lanka data, whereas it is 4 m in theSumatra data, considering the coefficient of determination to obtainthe linear regression lines between Φ-1 (Pci) (Φ means the standard(9)

Fig. 8 Definition of a tsunami wave load on a subject bridge

Table 4 Frequency of damage rank i of subject bridges d i, its cumulative frequency dci, and cumulative damage probability Pci basedon the Sri Lanka data

Table 5 Frequency of damage rank i of subject bridges d i, its cumulative frequency dci, and cumulative damage probability Pci basedon the Sumatra data

EVALUATION OF THE STRUCTURAL FRAGILITY OF A BRIDGE STRUCTURE SUBJECTED TO A TSUNAMI WAVE LOAD)
Table 6 Mean μY, standard deviation σY, and median mZ of inundation depth Z based on the Sri Lanka data)
Table 7 Mean μY, standard deviation σY, and median mZ of inundation height Z based on the Sumatra dataof determination when adopting the method of least squares. MeanμY and standard deviation σY derived from the y-intercept and x y)
inclination adopting Eq. (9) and median mZ of tsunami wave load
Z derived from Eq. (8) are also shown in Tables 6 and 7. Hence,
all parameters to model cumulative damage probability Pci shownin Eq. (7) are determined, and the fragility curves associated withicumulative damage probability Pc of a bridge structure against
tsunami wave load Z can be developed as shown in Figs. 11 and 12.
In Fig. 12, only the fragility curve of rank A is derived
because based on the Sumatra data, the number of data related todamage of rank B and rank C is not sufficiently obtained for the
linear regression analysis. Figs. 11 and 12 shows the structural
fragility of the total subject bridges based on 58 data in the Sri
Lanka data and 17 data in the Sumatra data; the curves indicate thegeneral fragility trends of a bridge structure and contain information associated with various types of structures. Therefore, in thefollowing, the fragility curve that presents the specific fragility
trends of a single-spanned reinforced concrete bridge without bearings, based on the Sri Lanka data, referring to Fig. 2, is derived asshown in Fig. 13.
(2) TRENDS OF TSUNAMI FRAGILITY OF A BRIDGESTRUCTURE

Relation between the data of Φobs-1 (Pci) and lnz based on the
Sri Lanka data and regression lines Φfit-1 (Pci)Fig. 11 Fragility curve of a bridge structure due to a tsunami basedon the Sri Lanka data

Fig. 10 Relation between the data of Φobs-1 (Pci) and lnz based on theSumatra data and regression line Φfit-1 (Pci)Fig. 12 Fragility curve of a bridge structure due to a tsunami basedon the Sumatra data

Fig. 979

80

G. SHOJI AND T. MORIYAMA

From Fig. 11, damage probability PA (=PcA) of rank A, whichmeans washout and fall-down of a deck, becomes nearly 0.1 when
the inundation depth is 4 m, whereas the value of PA increases from
0.2 to 0.25 when the inundation depth increases from 6 m to 8 m.
Damage probability PB (=PcB-PcA) of rank B, which means movement of a deck or damage to an abutment due to scouring and erosion, becomes nearly 0.3 when the inundation depth is 4 m, whereas the value of PB increases from 0.3 to 0.35 when the inundation
depth increases from 6 m to 8 m.
Compared with the trend of PA in Fig. 11, derived by the useof all the data among the Sri Lanka data (all bridge data), the trendof PA in Fig. 13, derived by the use of only the data associated witha single-spanned reinforced concrete bridge without bearings (single-spanned bridge data), becomes different; the value of PA basedon the single-spanned bridge data becomes larger than that basedon all bridge data when the inundation depth approaches a value
from 6 m to 8 m, although the values of PA based on both the single-spanned bridge data and on all bridge data are almost same
when the inundation depth is 4 m. This indicates that a singlespanned reinforced concrete bridge without bearings subjected to atsunami wave load is more fragile compared to other types ofbridge structure. One explanation for this may be that drag force
Q dI span against a tsunami wave induced in a deck of a singlespanned bridge becomes smaller than the QdM span induced in decksof a multi-spanned bridge, supposing that tsunami wave velocity v
is almost same when inundation depth Z is the same in this analysis
based on the Sri Lanka data. Now, drag force Qd is derived as follows:

Fig. 13 Fragility curve of a bridge structure due to a tsunami basedon the data associated with a single-spanned reinforced concrete bridge without bearings among the Sri Lanka data(a) Mechanism I

Qd =1
r C Av 2
2 w d

(10)

where ρw is the mass of sea water in a unit volume, Cd is the dragcoefficient, and A is the section area of a deck subjected to a tsunami wave. The drag coefficient of a deck of a single-spanned
bridge, CdI span, and that of a deck of a multi-spanned bridge, CdM span,
could be assumed to be almost the same, and the section area of adeck of a single-spanned bridge subjected to a tsunami wave, AI span,
becomes smaller than that of a deck of a multi-spanned bridge subjected to a tsunami wave, AM span; hence, from Eq. (10), QdI span
becomes smaller than QdM span, supposing that tsunami wave velocity v is almost same.
On the other hand, in Fig. 12, which is the case based on theSumatra data, damage probability PA of rank A when the inundation height becomes more than 9 m is clarified because not inundation depth but inundation height is used as the index of a tsunami
wave load. From Fig. 12, damage probability P A of rank A
becomes nearly 0.4 when the inundation height is 12 m, whereas PA
increases to nearly 0.5 when the inundation height increases to 20m; this inundation height level corresponds to an extreme tsunami
wave load, and it has high possibility of causing catastrophic damage to a bridge structure.
(3) FAILURE MECHANISM OF A BRIDGE STRUCTURE
BY A TSUNAMI WAVE LOAD
Now, we will hypothesize that the mechanism of the tsunami
wave load on a bridge structure is qualitatively divided into two
mechanisms; the mechanism due to the flow induced by a tsunami
wave (mechanism I) and that due to the impulsive pressure induced
by a tsunami wave (mechanism II), as shown in Fig. 14. It might
be considered that not mechanism I but mechanism II occurs whena tsunami wave load becomes extremely large compared to thecapacity of resistance of a bridge structure, for instance, when theinundation depth or inundation height becomes extremely large.
Such a hypothesis makes it possible for the fragility curves
from Fig. 11 and Fig. 13 based on the Sri Lanka data to result frommechanism I, whereas the fragility curve from Fig. 12 based on theSumatra data results from mechanism II. Examining it in detail, atsunami wave load within the range 5-m to 10-m inundation depth
corresponds to that on a bridge structure associated with mechanism I, whereas a tsunami wave load beyond the range of 10-m
inundation height and approaching a 20-m inundation height corresponds to that associated with mechanism II. The tsunami wave
load on mechanism I causes the movement of a deck following thewashout and fall-down of a deck, which results in major damage
to a bridge structure of either rank B or rank A at its worst, whereasthat on mechanism II causes the direct and catastrophic washout(b) Mechanism II

Fig. 14 Mechanism of the tsunami wave load on a bridge structureEVALUATION OF THE STRUCTURAL FRAGILITY OF A BRIDGE STRUCTURE SUBJECTED TO A TSUNAMI WAVE LOAD

and fall-down of a deck and columns, which results in 'severe'
damage of rank A. However, because there is no direct and independent evidence to decide the above matter, further numerical andexperimental studies will be performed to prove our hypothesis.

4. CONCLUSIONSIn this study, the structural fragility of a bridge structure due
to a tsunami wave load was evaluated, quantitatively analyzing thedamage data of bridge structures in Sri Lanka and in Indonesia dueto the 2004 Giant Tsunami in the Indian Ocean, which are on basisof 58 data on Sri Lanka (Sri Lanka data) and 17 data on Sumatra(Sumatra data). Assessing the data and classifying the tsunami
damage to a bridge structure into washout and fall-down of a deck
(rank A), movement of a deck or damage to an abutment due toscouring and erosion (rank B), minor damage to a deck attachment
such as bridge railings (rank C), to no damage (rank D), the relation between the probability of tsunami damage to a bridge structure with a tsunami wave load such as inundation depth and inundation height is clarified with the development of fragility curves.
From the analysis, the following conclusions are deduced.
1) From the fragility curves derived based on the Sri Lanka
data dealing with a 'major' tsunami wave load on a bridge
structure, which means an inundation depth level within 10
m, damage probability P A or P B of rank A or rank B
becomes nearly 0.2 to 0.3 when the inundation depth comes
within 5 m, whereas the value of PA or PB increases from
0.35 to 0.4 when the inundation depth approaches a value
close to the 10-m order; it might cause the failure mode of abridge structure due to the flow induced by a tsunami wave.
2) From the fragility curves derived based on the Sumatra data
dealing with a severe tsunami wave load on a bridge
structure, which means an inundation height level ranging
from 10 m to 20 m, damage probability P A of rank A
becomes nearly 0.4 when the inundation height reaches thevalue beyond 10 m, whereas PA increases to nearly or morethan 0.5 when the inundation height approaches a value of
20 m; it might cause the failure mode of a bridge structure
due to the impulsive pressure induced by a tsunami wave.
ACKNOWLEDGEMENTS
This research was sponsored by the Ministry of Education,
Culture, Sports, Science and Technology (MEXT) under a grant
provided as Special Coordination Funds for Promoting Science andTechnology, associated with the 2004 Giant Tsunami in the Indian
Ocean 'Restoration Program from Giant Earthquakes andTsunamis' (leader, Professor T. Kato at University of Tokyo,
Professor H. Iemura at Kyoto University, and Professor O. Murao
at University of Tsukuba). The authors deeply appreciate research
information and valuable assistance associated with the field survey in Sri Lanka, provided by Mr. G. N. Paranavithana at Natural
Resources Management Services (Pvt.), Ltd. in Sri Lanka, Mr. N.
Rupasighe at the Central Engineering Consultancy Bureau in Sri
Lanka, Dr. S. Herath at the United Nations University, andProfessor K. Meguro at the University of Tokyo. The authors arealso deeply grateful for research information and valuable assis-

81tance associated with the field survey on Sumatra in Indonesia,
provided by the members of the field survey team organized by theJapan Society of Civil Engineers (JSCE) and the Japan Associationof Earthquake Engineering (JAEE) (leader, Professor M. Miyajima
at Kanazawa University, Professor K. Fujima at National Defense
Academy of Japan, Professor K. Kosa at the Kyushu Institute ofTechnology, and Professor H. Matsutomi at Akita University).
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