USMCA 2018
17th International Symposium on
NEW TECHNOLOGIES FOR URBAN SAFETY OF MEGA CITIES IN ASIA
12-14 December 2018
International Institute of Information Technology, Hyderabad, India

USMCA 2018

KEYNOTES

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 78

TOWARDS DISASTER RESILIENT SOCIETY IN URBAN AREA
K. MEGURO1
1

Director/Professor, ICUS, IIS, the University of Tokyo, Japan, meguro@iis.u-tokyo.ac.jp

Keywords: Disaster Resilience, Disaster Imagination, Comprehensive Disaster Management System,
Comprehensive Disaster Management Matrix
1. INTRODUCTION
Why do many people live in disaster-prone areas? The
reason is that hazards bringing damage to a community
can be benefitted at the same time if the community has
high disaster resilience. Then, how can we build adisaster resilient community? The most important thing is
to improve disaster imagination capability of the people
from decision making a level to the general public. This isbecause people cannot prepare and respond well to an
unimaginable situation.
In my lecture, I will introduce what disaster
imagination is and a concept of "comprehensive disastermanagement system” which can effectively improve thedisaster resilience of society in the urban area.

by filling up all columns with possible countermeasuresand it should be standardized by specialists in the field of
disaster management. The CSM, which shows all
countermeasures already implemented in the target area,
should be prepared by local governmental officials.
After the 1995 Kobe Earthquake, the importance ofMA and SE has been recognized, however during the 2011
Great East Japan Earthquake and Tsunami Disaster, theinvolvement of private companies in MA and SE wasrecognized as important, collaborating with the local
people in activities such as rescue and firefighting.
The countermeasure by three types of effort is often
complementary to each other and it must be well-balanced.
In other words, if the work is concentrated in PS part, thecost could be enormous while, if each individual puts aneffort while cooperating with each other, it could be much
more effective with lesser cost. PS should promote MA
and SE rather than enhancing people’s dependency on PS.
In order to realize this situation, the disclosure of

2. COMPREHENSIVE DISASTER MANAGEMENTSYSTEM
In order to minimize the negative impact due to hazard,
I have proposed "Comprehensive disaster management
system” as shown in Figure 1. The system is down into
seven stages, starting with “damage mitigation”,“preparedness”, and “prediction and early warning” as
pre-disaster countermeasures and “damage assessment”,“disaster response”, “recovery”, and “build back better” inthe post-disaster countermeasures. Information andcommunication play an essential role in all seven stages.
By combining these seven measures properly
considering natural and social characteristics of the target
region, the negative impact due to hazard can be
minimized. Moreover, considering disaster as animportant opportunity to solve potential problems of theaffected region, we can create a better region andcommunity than before.
3. PROCEDURE FOR DISASTER RESILIENT
SOCIETY
3.1 Comprehensive Disaster Management Matrix
At all seven stages of disaster management, it isnecessary to understand that the government is not the
only actor in disaster management but the collaboration
among local community and the residents’ participation isvital. Therefore, there are three forms of effort describedas public support (PS), mutual assistance (MA) and selfhelp effort (SE). Although there are differences in weights
in each countermeasure, there are structural (H: Hard) andnon-structural (S: Soft) measures. Further, acomprehensive disaster management matrix (CDMM)
shown in Figure 2 can be prepared. A CDMM is composedof two kinds of the matrix; ideal situation matrix (ISM)
and current situation matrix (CSM). The ISM, which
includes all measures by three efforts, should be prepared

Figure 1: Comprehensive disaster management system

Event
Damage Prepared- Prediction
Mitigation
ness
and
Early
Warning

SE

DamageAssessment

Emergency Recovery andDisasterReconstruction
Response

H(Self-help
effort ) S(Self
Effort)MA H(MutualAssistance) S

Two kinds of matrices :Ideal and current situations

PS H(Public
Support)S

Figure 2: Comprehensive disaster management matrix

1

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 78
information about the disaster risk to the general public
becomes important.

PDCA management cycle is put into practice and effective
progress management is realized as shown in Figure 5.

3.2 Promotion method for comprehensive disastermanagement
In order to efficiently conduct disaster management
countermeasures, it is essential to make appropriate
combinations of countermeasures at seven stages by threeefforts considering regional characteristics, target disastertypes, current disaster preparedness, available time andbudget at each stage. Figure 3 shows the specificprocedure to find appropriate combinations ofcountermeasures. The difference between ISM and CSM
indicates the action item matrix (AIM) that shows thenecessary countermeasures have to be taken. To all
countermeasures (action items) written in the AIM,
information on responsible section/person, necessary timeand budget, and the effect when completed will be added.
This approach could be applied to all possible hazards inthe target area. However, the contents will differ based on
the type of hazard, and thus Disaster Management Matrix
for each type of disaster needs to be created, and allnecessary disaster matrices should be integrated as shownin Figure 4.
Subjected to the available time and budget, it ispossible to determine realistically, the countermeasuresthat can achieve maximum effect within the given
condition. By practicing this process over several years,

3.3 Relation among national, prefectural andmunicipality governments
According to the Disaster Countermeasures Basic
Act in Japan, the mayor of the municipality, such as city,
town, and the village has responsibility for disaster
operation and response. Therefore, when they discuss thedisaster management plan and countermeasures, they tend
to consider hazard, which can be managed by themselves,
as a scenario hazard. Then, it becomes very difficult, or
practically impossible for them to consider a much largerscale disaster that they could not manage. This situation
was observed in many affected areas due to the 2011 Great
East Japan Earthquake and Tsunami. One of the maincauses was that they put only themselves, the municipality
level government, in disaster countermeasure matrix
when they discussed disaster management plan andcountermeasures as shown in the upper sub figure in
Figure 6. In order to solve this problem, they should put
prefectural and national governments besides them in PS
column as shown in the bottom subfigure in Figure 6.

Figure 5: PDCA cycle for implementation of efficientcountermeasures

Figure 3: How to obtain action item matrix

Figure 6: Relations among national, prefecturaland municipality governments

Figure 4: How to obtain integrated action item matrix

2

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 78
Then, they can write what they cannot do in the columns
of prefectural and national governments. By combining
these seven measures properly considering natural andsocial characteristics of the target region, the negative
impact due to hazard can be minimized. Moreover, also,
considering disaster as an important opportunity to solve
potential problems of the affected region, we can create abetter region and community than before. From theprefectural governments’ viewpoint, they considered thatwhat they should do in case of the disaster was waiting forrequests from municipalities and respond them. However,prefectural governments can recognize that when theaffected municipalities cannot respond because of toolarge disaster for the municipalities to manage, without
waiting for requests from the affected municipalities,
prefectural governments should visit the affected sites andcarry out operation and response of disaster instead of theaffected municipalities. Moreover, when three-levelgovernments fill all countermeasure items together thateach government should do in the bottom matrix as shownin Figure 6, they can recognize spontaneously, theduplications and gap among different governments.

much more people are killed and injured by the collapseof masonry structures compared with another type ofstructures. First, as failure behavior of weak masonry
structure is brittle, people cannot have time for theirevacuation. Second, the size of bricks is small as astructural material and members, they fill the survival
space during the collapse, and it becomes difficult to havesurvival space under the damaged structure. Third, heavy
dust is generated during the collapse, and people cannot
get fresh air under such condition.
Based on these facts, we should recognize thatstrengthening of weak structures is the most importantmeasures for earthquake disaster reduction in the future.

4. MISUNDERSTANDING ON DISASTER
MANAGEMENTAs mentioned in chapter 3, the negative impact due tohazard can be minimized, and potential problems can also
Figure 7: Who took out the people from under thebe solved by a proper combination of countermeasures atdamaged structures
all seven stages. However, in many countries, especially(1995 Kobe earthquake, Japan)
in developing countries, disaster response is considered
personthe most important measures of disaster management.
*public sectors: fire fighter and self-defense force
1,000
Major activities of the disaster response stage are a supply
900
of emergency goods, such as food, water, clothes, and800
fatalities
700
search and rescue operation.
survivors600
In case of the 1995 Kobe earthquake disaster in Japan,(survivors’ ratio)
193
816
500
608
approximately 40,000 to 45,000 people were trapped
400
under the damaged structures just after to a couple of days.
300
231
419
Among them, as Figure 7 shows that 8,000 people were
428
200
116
(%)
80
189
(69)
taken out by public sectors and local communities did
100
9(3.8) 4(3.3)
2(2.4)(24) 114(12) 30(6.7)
027,000. Survivor’s ratio of the people taken out by local
Jan.17
18
21
23
22
19
20
communities was much higher than that by public sectors.
Figure 8 shows the number and survivor’s ratio of people
Figure 8: Number and Survivor’s ratio of people
taken out under damaged structures by public sectors intaken out under damaged structures
Kobe City. The total number was getting bigger in theby public sectors* in Kobe City
second, and the third days, however, survivor’s ratio was
getting smaller from approximately 70 % in the first day,Rescued/ Recovered Victims
20% in the second day, and 10 % in the third day. Beside
9256
Japanese public sectors’ teams, international search andv
9,256*Total*TOTALVICTIMS
Victims
22326
22,326
rescue teams with rescue dogs visited from Switzerland,
France, and the UK and they could rescue no survivor and
6988
v
By
Community
6,988
BY COMMUNITY AND/OR SELF
17887
17,887find 13 dead bodies. In the case of the 2015 Gorkha
and/or Selfv
Earthquake disaster in Nepal, over 9,000 people were**By Nepal
2133
v
2,133
**BY NATIONAL SAR TEAMS
killed mainly by the collapse of vulnerable structures.
4420
v
4,420
SAR Teams
While over 22,000 people were rescued from under the:死者
Dead: Live
Alive
生存者
Dead
***By International 135
damaged structures. Among them, over 80 % of them***BY INTERNATIONAL SAR TEAMS 19135
SAR Teams 19
were saved by local communities but only less than 0.1 %
25000
5000
10000
15000
20000
25,00000
15,00020,0005,000
10,000were rescued by international search and rescue teams.
Source: *Nepal Police, 2 July 2015, **Reports by Nepalese Army, Nepal Police
Figure 10 shows 21 earthquakes causing over 5,000
and Armed Police Force, June 2015, *** report by Nepalese Army, June 16, 2015
fatalities in the last 100 years. Among 21 events, collapse
of weak masonry structures was the primary cause of
Figure 9: Result by Search and Rescue Operation
fatalities in 17 ones. There are three major reasons why(2015 Gorkha Earthquake, Nepal)

3

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 78

Figure 10: Earthquakes causing over 5,000 fatalities in the last 100 years
About search and rescue, the local community cancontribute the most, and we should not expect too muchon the contribution of international teams.
However, when we checked the disaster-related
international projects in the past, many of them arefocused on emergency and disaster response as shown in
Figure 11. Main activities of “emergency response” aresearch and rescue operation, and emergency supply.
However, both of these two activities cannot contribute todisaster reduction in the future. Also, as alreadymentioned, it is quite difficult to save people by search andrescue operation by international teams.
Then, what is the reason of concentration of projects
on the phase of “emergency response”? I think that there
are two major reasons. One is that it is relatively easier tocarry out emergency response, such as rescue operationand emergency supply, compared with the other phase
activities, especially mitigation and preparedness. The
other reason is that responsible person of the project isalways requested the high presence of the project by thesponsor organization. In order to raise the presence of the
project, the most effective way is to get the press to report
it. Mass media people report disaster-related activities
only just after the big disaster.
To solve the problems introduced above, what should
we do? We should pay attention to two issues below.
Besides the budget, it is necessary to establish proper
indicator/index for the evaluation of real effects of the
project for reducing human casualties and economic loss
due to hazards in future. To let the public understand betterthe real effects of each disaster countermeasures,
education of press to improve disaster imagination for
better information dissemination is essential.

Figure 11: International projects on disastermanagement during 1990 - 2010"prediction and early warning" are the elements of preevent measures, and "damage assessment", "(emergency)
disaster response", "recovery", and "build back better" arethose of post-event measures. Combining these sevencountermeasures properly considering a natural and social
characteristics of the target region, we can minimize thenegative impact due to hazard. And also, considering
disasters as an important opportunity to solve potential
problems of the affected region, we can create a better
community than before.
In each of the seven countermeasures, there are threeefforts, namely, "self-help effort (SE)", "mutual assistance(MA)" and "public support (PS)". Based on the
combination of above mentioned countermeasures andefforts, the "comprehensive disaster management matrix"
was introduced.
In addition, based on the past earthquake disasters, I
have pointed out some important lessons that are often
misunderstood by many people. Due to the limitation of
the space, a solution to improve seismic capacity of weakbuildings and disaster information management were notexplained in this manuscript, I will introduce them during
my lecture at the conference.

6. CONCLUSIONS
To build a disaster resilient community, I haveintroduced "comprehensive disaster management system”
that consists of three pre-event measures and four postevent ones. "Damage mitigation", "preparedness", and4

USMCA 2018

SESSION 1
INFRASTRUCTURE MANAGEMENT

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 25

DEVELOPMENT AND PRACTICAL APPLICATION OF
TRAIN OPERATION CONTROL METHOD AGAINST WIND GUST USING DOPPLER RADAR
H. SUZUKI1, K. KUSUNOKI2, C. FUJIWARA3 and H. INOUE4
1

Director, Research and Development Center, East Japan Railway Company, Saitama, Japan, h-suzuki@jreast.co.jp(corresponding author)
2
Head, Meteorological Research Institute, Ibaraki, Japan, kkusunok@mri-jma.go.jp
3Researcher, Research and Development Center, East Japan Railway Company, Saitama, Japan, chusei-fujiwara@jreast.co.jp
4Researcher, Meteorological Research Institute, Ibaraki, Japan, hainoue@mri-jma.go.jp
Keywords: Wind gust, Vortex, Doppler radar, Train operation control
train operation control method against wind gusts using
Doppler radar.
By this method, the radar automatically detects andtraces vortices in the air that accompany tornados on the
ground surface. When it is predicted that vortices cross arail line, a warning is issued to stop trains in that section.
This method was put to practical use on the Uetsu Lineand the Rikuusai Line in the Shonai area from December
19, 2017. This is the first case of practical use of suchtrain operation control method against wind gusts using
Doppler radar.

1. Introduction
Wind gusts such as tornadoes are among natural
disasters that can cause serious damage. On inland inJapan, approximately 25 tornadoes occur each year[1].
Railways also suffer damage from wind gusts. In Japan,
train derailment accidents caused by wind gusts haveoccurred in 1970, 1978, 2005 and 2006[2],[3],[4] asshown in Table 1. Among these, an accident occurring in
December 2005 on the Uetsu Line suffered casualties[3].
The cause of this accident is said to be winter wind guston the Sea of Japan side[3]. We thus developed a train
operation control method against such wind gusts using
Doppler radar and this method was put to practical use
from the 2017-18 winter.
Railway operators in Japan enforce train operation
control such as speed reduction or suspension ofoperations based on wind velocity observed byanemometers, to ensure safe train operation in the timesof strong winds. But it is difficult to detect wind gustswith anemometers arranged at intervals along the tracks,
because the spatial scale of wind gusts is small. Doppler
radars, which can make planar and continuous
observation of wind velocity, are suitable for detecting
such wind gusts.
In developing a train operation control method against
wind gusts using Doppler radar, we started withobserving and studying winter wind gusts themselves, as
there have been many unexplained areas. We thus
deployed a weather observation network, using Doppler
radars and anemometers etc. on the Shonai Plain in
Yamagata Prefecture. Based on the obtained knowledge
regarding winter wind gusts, we developed a method
suitable for detecting wind gusts with Doppler radar, and

2. Observation network and obtained knowledge
There have been many unexplained areas in wind
gusts. In particular, knowledge was scarce regarding
winter wind gusts on the Sea of Japan side that caused
the Uetsu line accident on 2005. We thus started withobserving and studying winter wind gusts themselves.
Therefore, from 2007, we deployed a weather
observation network on the Shonai Plain in Yamagata
Prefecture[5],[6].
Two X-band Doppler radars were installed with anobservable range of a radius of over 30 km[5]. We set up
26 weather observation stations to measure winddirection and velocity, air pressure, temperature andhumidity[5]. Furthermore, we also set up a linear array
wind and pressure sensors system, with 12 anemometersat 100 m intervals and 25 barometers at 50 m intervals[6].
From those observations, we obtained following
knowledge regarding winter wind gusts. (1) Wind gustson the ground surface accompany precipitation andvortices in the air[7]. (2) Vortices form on the Sea ofJapan, move straight east and make landfall[8].

Table 1: Outline of train derailment accidents caused by wind gusts in Japan
Date and time

Location

Type ofwind gustOutline of accidents
Overturn of two vehicles of express train
in time of reducing speedSouce2006.9.17
14:05

The premises of Minami-Nobeoka
station on Nippo Line

Tornedo2005.12.25
19:14

Between Sagoshi station and KitaAmarume station on Uetsu Line

Unknown Overturn of 6 vehicles of express train

1978.2.28
21:34

Between Minami-Sunamati station andTornedoKasai station on Touzai Line

Overturn of one vehicle and derailemtof two vehicles of passenger train

21 Injueries

1970.2.5
10:10

The premises of Kamiyama station on
Uetsu Line

Overturn of one vehicle of freight train

Four Injueries

Tornedo5

Two Injueries

Japan Transport
Safety Board[4]Five desths and
32 injueries

Japan Transport
Safety Board[3]Fujii et al.[2]Distance from the radar (km)17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 25

1Doppler velocity.

Reflectivity
dBZ

m/s

48

24

36

20

24

16

12

12

0

8

0

-1

-2

1

2

3

1

2

Distance from the radar (km)3

Figure 1: Radar image at time of wind gust observation.(December 5, 2007)
Step 1

Step 4

Ｗarning and train operation control

Observation by
Doppler radar
30 s interval

Step 2

Predicted
moving range

Stn. A

Detecting vortex and calculatingrotational wind velocity
Approaching

Stn. B

Dopplerradar

VortexStn. C

Doppler radar
Step 3

Receding
Doppler velocity

VortexCalculating moving direction andspeed of vortex

Tracking vortex
MovingDirection

Stn. D
Stn. E

Rotational wind velocity

Stn. F

Moving speed

Fully automatic fromobservation to warning

Moving speed
Wind velocity =Rotational wind velocity + Moving speed

Figure 2: Procedure of the train operation control method against wind gusts using Doppler radar.
(3) Multiple vortices sometimes occur simultaneously[9].
(4) Vortices develop from lower layer to upper layer[10].
(5) Wind velocity distribution of wind gust on the groundsurface roughly agrees with the Rankine vortex
model[11]. (6) The maximum wind velocity of the vortex
on the ground surface and the vortex in the air are
roughly the same[12].
The following findings in regards to method of wind
gust detection are obtained based on above knowledge.
(1) Method of detecting vortices in the air using Doppler
radar is effective to detect wind gusts on the groundsurface. (2) The moving speed and direction of vortices
in the air can be obtained by tracking vortices. (3) A
wind gust detection system needs to simultaneously
detect and track multiple vortices. (4) A detection
method that frequently observes the lower layer issuitable. (5) It is considered that vortices in the air can bedetected with the Rankine vortex model. (6) The
maximum wind velocity of the vortex on the groundsurface can be estimated from the maximum windvelocity of the vortex in the air.

3. Methods of detecting vortices
A Doppler radar is a meteorological observation
device that can observe wind phenomena, in addition toits function as a conventional weather radar measuring
precipitation. It can observe components of approaching
and receding wind from radar in the air, using the
Doppler effect of radio waves reflected fromprecipitation particles such as raindrops blown by thewind. In a Doppler radar, rotating winds such as vortices
in the air that accompany tornados can be detected byextracting pairs of approaching and receding winds.
Figure 1 is a typical example of radar images when awind gust on the ground surface is observed, and shows
images of reflectivity and Doppler velocity of a wind
gust on December 5, 2007. In this case, a hook-shaped
echo was observed which is the characteristic pattern of avortex, and a pair of approaching and receding winds
was present in the Doppler velocity image.
Wind velocity distribution of vortex accompanied bywind gust on the ground surface roughly agrees with
Rankine vortex model. From this knowledge, it is6

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 25
Table 2: Wind velocity and Fujita scale of wind gusts that have caused train accidents in Japan.
Date and time

Location

Type of wind
gustWind velocity ofwind gustRank onFujita scale

Souce

2006.9.17
14:05

The premises of Minami-Nobeoka
station on Nippo Line

TrornadoOver 51～53m/s

F-2

Japan Transport
Safety Board[4]2005.12.25
19:14

Between Sagoshi station and KitaAmarume station on Uetsu Line

Unknown

About 40 m/s

F-1

Japan Transport
Safety Board[3]1978.2.28
21:34

Between Minami-Sunamati station andKasai station on Touzai Line

TrornadoOver 80m/s

F-2～3

Shimamura[14]1970.2.5
10:10

The premises of Kamiyama station on
Uetsu Line

Trornado

UnknoenUnknown

considered that vortices in the air can be extracted fromthe Doppler velocity data observed by Doppler radarusing the Rankin vortex model. Therefore, to detect
vortices in the air, we decided to use the algorithm
improving the multi-scale meso-vortex/divergencedetection algorithm for detecting mesoscale vortex/
divergence signatures in Doppler radar observations
proposed by Suzuki et al.[13].

Extrapolated positionΔθ

Actual position

Vortex4. Procedure for train operation control
Based on the above knowledge, we proposed a train
operation control method against wind gusts using
Doppler radar enforced by the procedure shown in
Figure 2. There is single Doppler radar used in thismethod. This procedure is conducted fully automatically.
Step 1 is observation by Doppler radar. Observation by
Doppler radar is conducted at 30 second intervals.
Doppler radar observes low layer as possible. This isbecause vortex in the air develops from lower layer toupper layer. Quality control of the observed data is thencarried out.
Step 2 is to detect vortex in the air and calculate its
rotational wind velocity. Vortices are detected to findpairs of approaching and receding winds. This is because
rotating winds such as vortices are observed as pairs ofapproaching and receding winds by Doppler radar. To
detect vortices, the algorithm improving the multi-scalemeso-vortex/divergence detection algorithm proposed by
Suzuki et al.[13] is used. Furthermore, rotational windvelocity of vortices is calculated using that algorithm.
Step 3 is to calculate moving direction and windvelocity of vortex. When the vortex is under continuous
observation, the moving direction and speed of thevortex can be obtained. Then the maximum windvelocity of vortex in the air can be obtained by adding
rotational wind velocity of vortex and the moving speedof vortex. This wind velocity is recognized as the
maximum wind velocity of wind gust on the groundsurface. This is because the maximum wind velocity ofthe vortex on the ground surface and the vortex in the air
are roughly the same. Therefore, train operation control
against wind gust is issued based on the wind velocity ofvortex in the air.
Step 4 is to issue warning and train operation control.
When the vortex accompanied wind velocity above a
train operation control value is detected, a warning isissued. Furthermore, in the case that vortex crosses a rail
line, train operation control is issued in the section wind
gusts are predicted to pass.

Figure 3: Schematic diagram of actual position ofvortex and extrapolated prediction positionof that.
5. Train operation standard
In putting this method into practical use, it isnecessary to decide the train operation standard such as
train operation control value of wind gust, the predictedmoving range of that, operation control classification andsection, and duration of train operation control.
5.1 Train operation control value
The train operation control value of wind gust is set
based on wind gusts that have caused train accidents inJapan in the past. Table 2 shows the wind velocity andFujita scale of wind gusts that have caused train
accidents. Based on this table, the minimum windvelocity was about 40 m/s and the minimum rank ofFujita Scale was the F-1 scale. Therefore, the train
operation control value is set at wind velocity of 33 m/s
which is the minimum wind velocity of the F-1 scale.
5.2 Predicted moving range of wind gust
The predicted moving range of wind gust is set as thearea where wind gusts are predicted to pass within ten
minutes, because ten minutes is enough time to stop
trains.
Specifically, this range is set as the extrapolated range
based on the moving speed and direction of the vortex to
the range plus the prediction error. Figure 3
schematically shows actual moving position of vortex
and extrapolated prediction position of that. Figure 4
shows frequency distribution of difference between theactual moving position and the extrapolated predicted
position of moving distance and direction. The range ofthe prediction error is set to be twice the standard
deviation of the difference between them. Figure 5 shows
the predicted moving range of wind gust.
5.3 Operation control classification and section
Baker and Sterling[15] showed that the reduction of7

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 25
2σ =0.26 times

2σθ =16.2 degree80Frequency

Frequency

80

40

0

0.0

0.5

1.0

1.5

40

0

2.0

Ratio of actual moving distance andextrapolated prediction distance of vortices

-50

-25

0

25

50

Difference actual moving direction and extrapolated
prediction direction of vortices (Degree)

Diameter of vortex(m)Figure 4: Frequency of difference between the actual moving position and the extrapolated predicted position.
Right side is ratio of actual moving distance and extrapolated prediction distance. Left side isdifference of actual moving direction and extrapolated predicted direction.

=

1200
1000
800

系列1
Detection

600

Undetection
系列2

400
200

系列3

0

系列4

=

0
100 200 300 400
Azimuth resolution(m): Predicted moving range: Predicted moving distance: Predicted moving distance for 30 seconds: Standard deviation of moving distance: Predicted moving distance for 10 minute系列
10

0 5 10 15 20 25 30
Distance from radar(ｋｍ）

Figure 6:: Predicted moving direction: Standard deviation of moving direction: Diameter of vortex

Propriety of detection of vortex, andrelationship between diameter of vortex
and azimuth resolution.

detected by Doppler radar. In the Shonai Plain, from the
2007-08 winter to the 2013-14 winter, there were nowind gusts that the Japan Metrological Agency (JMA)
has certified as the F-1 scale or more. That is, no wind
gusts exceeding the train operation regulation value haveoccurred. Therefore, evaluation was enforced using wind
gusts certified as the F-0 scale or observed byanemometers on the ground surface. The F-0 scale is thelowest rank on Fujita scale. Wind gusts observed byanemometers were assumed to be the case where thewind velocity suddenly increased to a wind velocity of
30 m/s or more. The breakdown is as follows: three F-0
scale, and six wind gusts observed by anemometers. Thismethod could detect six wind gusts out of those but
could not detect three wind gusts as shown Table 3.
Figure 6 shows relationship between diameter ofvortex and azimuth resolution of Doppler radar. Here, theazimuthal distance increases with distance from the radar.
The straight line in this figure shows the value at which
the azimuth resolution of the radar and the diameter ofthe vortex are 1: 3. From this figure, it is considered that
it is divided into a region in which vortices in the air canbe detected and a region in which vortices can beundetected, and the boundary is considered to be divided
by that straight line in which the azimuth resolution of
the radar and the diameter of the vortex are 1: 3.
Figure 7 shows Doppler velocity distribution map andthe Doppler velocity at the center position of the meshes
in the XY cross section in the case of vortex detected andFigure 5: The predicted moving range of wind gust(wind gust).
train speed at times when tornadoes are expected would
lead to a very significant reduction in accident risk.
Therefore, operation control classification is decided to
be stopped due to the lowest risk of accident. When avortex accompanied wind velocity above the train
operation control value is detected and that vortex
crosses a rail line, suspension of operations is issued forthe section where wind gusts are predicted to pass.
Suspension of operations is enforced between nearest
stations outside the predicted moving range of wind gust.
5.4 Duration of suspension of operations
The predicted moving range of wind gust is set as thearea where wind gusts accompanied wind velocity above
the train operation control value are predicted to passwithin ten minutes. Therefore, suspension of operations
is continued for ten minutes after that vortex is detected.
6. Evaluation of this method
The evaluation of this method was conducted from the
aspects of both safety and stability of train operation.
Because, in railway, it is important to ensure sufficient
safety, but in addition to this it is also important to ensure
normal train operation as much as possible[16].
Safety was evaluated by the number of wind gustcaptured. This number is the number of wind gusts

8

-10

7

-20

6 X

-10
-20
-30

-9 -8 -7 -6 -5Distance from the radar in
the east-west direction (km)

X

Y

-1.0

0

1.0

27

m/s
10

26

Y

25 X

-10

24
-8

Distance from center of vortex
(km)

0

-7

-6

-5

-4

Doppler velocity (m/s)

0

8

0

Distance from the radar in
the north-south direction (km)

Y m/s

9

Doppler velocity (m/s)

Distance from the radarin the north-south direction(km)17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 25
10
5
0
-5
-10
-15
X
-20
-1.0

0

1.0

Distance from center of vortex(km)

Distance from the radar in
the east-west direction(km)(a) Detected vortex

Y(b) Undetected vortex

Figure 7: Right is Doppler velocity distribution and left is the Doppler velocity at the center position of the mesh in the
XY cross section in the case of vortex detected and undetected by Doppler radar.
Table 3: Number of wind gust occurred and wind gust captured
Area

Scale of wind gust

Number of wind gust occurred

Number of wind gust captured

Shonai Plain

F-0 scale

9

6

Other areas

Over F-1 scale

4

4

Table 4: Predictive rate of wind gust, and number ofdetected wind gusts and actual wind gusts
Predictive rate

Detected wind gustActual wind gust

81.9%

99

81

Table 5: Rate of added time of suspension of operations,and hours of suspension of operation of wind
gust (this method) and strong wind.
Rate of added time ofsuspension ofoperations
7.0%

Hours of suspension of operations (per year)
Wind gustStrong Wind

2.2

31.2

undetected by Doppler radar. In Figure 7(a) where avortex can be detected, there are three observed values
between the maximum and the minimum of the Doppler
velocity. On the other hand, in Figure 7(b) where thevortex could not be detected, there is no observed value
between them. Although figures of other cases areomitted, in the case where vortex could be detected, there
were one or more observed values between them.
Therefore, if the diameter of vortices is more than threetimes the azimuth resolution of the radar, it is considered
to be able to detect the vortex.
Furthermore, we analyzed the capture performance of
our algorithm to detect vortices using four strong wind
gusts occurred in other areas. The breakdown is asfollows: one F-3 scale, one F-2 scale, and two F-1 scale.
This algorithm was able to detect all these wind gusts asshown Table 3.
Stability was evaluated by the predictive rate of wind
gusts. This rate is the ratio of the detected vortex to theactual vortex. The detected vortex is a case where thewind velocity of vortex in the air observed by Doppler
radar is equal to or higher than the train operation control
value of wind gust, and the rail line is included in thepredicted movement range of wind gust. The actual
vortex is the case where the detected vortex is actually avortex. Table 4 shows number of detected wind gusts andactual wind gusts, and predictive rate of wind gust from

Figure 8: New Doppler radar used the train operation
control against wind gusts
the 2007-08 winter to the 2013-14 winter. The predictive
rate was high at 81.9%. In addition, we research the timeof suspension of operations due to wind gust and strong
winds. A train operation control against strong winds has
been enforced conventionally. As a result, the time ofsuspension of operations due to wind gust was low at
7.0% of the time of suspension of operations due tostrong winds as shown in Table 5.
Therefore, this method can secure both safety andstability of train operation. East Japan Railway Company(JR East) thus decided to adopt this method as a train
operation control method against winter wind gusts that
occur on the Sea of Japan side.
7. Practical application
For practical application of this method, a new X-band
Doppler radar was built as shown in Figure 8. This
Doppler radar has higher performance than the radarused in development and it was installed at a location
more suitable for observation of wind gusts.
This method, as countermeasure of winter wind gustson the Sea of Japan side, was put to practical use on the9

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 25
Reflectivity

Distance from the radar (km)accident between Sagoshi station and Kita-Amarume
station on the Uetsu Line of East Japan Railway
Company”, http//www.mlit.go.jp/jtsb/eng-rail_report/
English/RA2008-4e.pdf, 1p.
[4] Japan Transport Safety Board, (2008), Railway
accident investigation report “Train derailment
accident in the premises of Minami-Nobeoka on the
Nippo Line of kyuushu Railway Company”,
http//www.mlit.go.jp/jtsb/eng-rail_report/
English/RA2008-6e.pdf, 1p.
[5] K. Kusunoki, et al., (2008), An overview of the
Shonai area railroad weather project and earlyoutcomes, Preprints, 5th European Conf. on Radar in
Meteorology and Hydrology, Eur. Meteor. Soc., p.
12.1.
[6] K. Kusunoki, et al. (2012), A linear array of pressure
and wind sensors for high resolution in situ
measurements in winter tornadoes, Preprints, 7thEuropean Conf. on Radar in Meteorology andHydrology, Eur. Meteor. Soc.
[7[ K.Kusunoki, et al., (2009), Wind gust and storm
evolutions observed during the Shonai Area Railroad
Weather Project: A preliminary survey, Proc., 5thEuropean Conf. on Severe Storms, Eur. Meteor. Soc.,
P09.16.
[8] T. Ishitsu, et al., (2015), Statistical study of vortices
landed in the Shonai plain in winter observed by
Doppler radar, Proc. 108th Conf. Japan Meteor. Soc.,
108, pp. 373. (in Japanese)[9] H. Inoue, et al. (2011), Finescale Doppler radarobservation of a tornado and low-level misocyclones
within a winter storm in the Japan Sea coastal region,
Mon. Wea. Rev., Vol.139, pp.351-369.
[10] K. Shimose, et al. (2011), Numerical simulation of
weather disturbance caused wind gusts in the Shonai
Plain, Proc. 100th Conf. Japan Meteor. Soc., pp.220.
(in Japanese)[11] H. Inoue, et al.,(2013), Wind gust and weather
disturbances observed in the Shonai Plain - Vortex
and surface wind in the vortex II-, Proc. 104th Conf.
Japan Meteor. Soc., pp.70. (in Japanese)[12] R. Kato, et al., (2015), Analysis of the horizontal
two-dimensional near-surface structure of a wintertornadic vortex using high-resolution in situ wind andpressure measurements, J. Geophys. Res. Atmos,
Vol.120, pp.5879–5894.
[13] O. Suzuki, H. Yamauchi, M. Nakazato and K.
Akaeda, (2007), A new multi-scale meso-vortex/
divergence detection algorithm with modified
Rankine combined vortex, Preprints, 33rd Conf. on
Radar Meteor. P5.1.
[14] M. Shimamura, (2006), Prevention from disasters
and learn from disaster - Struggle of railway civilengineering maintenance department -, Japan
Railway Civil Eng. Assoc., 271p. (in Japanese)[15] C. Baker and M. Sterling, (2018), The calculation oftrain stability in tornado winds, J. Wind Eng. Ind.
Aerod., Vol.176, pp.158-164.
[16] H. Muraishi, T. Sugiyama and S. Kagawa, (1995),
Study on disaster prediction method by effective
rainfall index, RTRI REPORT, Vol.9, pp.7-12. (inJapanese)

Distance from the radar (km)Figure 9: Example of reflectivity image of new Doppler
radar and status at the time of issuingsuspension of operations.
Uetsu Line and the Rikuusai Line in Shonai area from
December 19, 2017.
Figure 9 shows example for reflectivity image of new
Doppler radar and status at the time of issuingsuspension of operations. Suspension of operations was
issued 53 times by this method from its start to the end of
March 2018. This was higher than the average times
from the 2007-08 winter to the 2013-14 winter. This wasdue to severe weather condition of the 2017-18 winter. In
addition, it is considered that the performance of new
Doppler radar is higher than that of the radar used indevelopment and predictive rate of wind gust is lowered.
8. Summary
We developed a train operation control method against
winter wind gusts using a Doppler radar. In this method,when it is predicted that a wind gust at wind velocity ofover 33m/s (lower limit of F-1 scale on Fujita scale)crosses a rail line within ten minutes, a warning is issued
to stop trains in that section. This method was put topractical use on the Uetsu Line and the Rikuusai Line in
the Shonai area from December 19, 2017. It is the firsttime in the world that such train operation control
method against wind gusts using Doppler radar has been
applied.
In the future, we will continue development to further
improve the number of wind gust captured and thepredictive rate of wind gusts, and expand the using areaof this method.
REFERENCES[1] Japan Meteorological Agency, Database of wind
gusts such as tornadoes, http://www.data.go.jp/obd/stats/data/bosai/tornado/index.html.(in Japanese)[2] M. Fujii, T. Fujii and H. Muraishi, (1995), History of
train operation control against strong winds, RTRIREPORT, Vol.9, pp.43-48.
[3] Japan Transport Safety Board, (2008), Railway
accident investigation report “Train derailment
10

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 08

DEVELOPMENT OF BOND DETERIORATION MODEL IN CORRODED RC MEMBER FORDISCRETE ANALYSIS MODEL
K. NAGAI1, P. JIRADILOK2, and K. MATSUMOTO3
Associate Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, nagai325@iis.u-tokyo.ac.jp
Project researcher, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, punyawut@iis.u-tokyo.ac.jp
3
Project Assistant Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, km312@iis.utokyo.ac.jp
1
2

Keywords: reinforced concrete, corrosion, bond deterioration, RBSM, discrete analysis
1. INTRODUCTION
For a maintenance of reinforced concrete (RC)structures, corrosion is the most serious problem thatwould lead to the collapse of the structures. For theappropriate maintenance, evaluating the precise residual
capacity of corroded structures is necessary, although it isdifficult due to the complicated damage patterns of local
corrosion and cracking. Meso-scale simulation is one of
the beneficial tools for analyzing the structure’s member
where the local damages are presented directly. In thisstudy, a numerical model for simulating the spatial
corrosion damage of reinforced concretes is developed
based on a discrete analysis, Rigid Body Spring Model(RBSM). The corrosion model consists of rust expansion
damage model, rebar effective-cross-section area
reduction, and bond deterioration model. When the
corrosion occurs, the corroded rebar losses its shape andcreates corrosion product which changes the surface
properties. However, in the typical discrete analysis model,
the element is modeled as a rigid element which cannot
deform. So, in this paper, the author focuses on thedevelopment of the bond deterioration model for
representing the corrosion effect. Pull-out experiments are
performed by using different corrosion degree anddifferent reinforcement shape specimens. The data
analysis is done for extracting the necessary information
for developing the equivalent model for the bonddeterioration in rigid element. Finally, the simulation
results are compared with the previous experimental
results for the validation of applicability of the model.

concrete element is approximately 1-2 cm3, referred toaggregate size, while the size of the steel element is set
according to the geometric complexity of thereinforcement bar arrangement (Figure 1). To prevent thecracks propagated in a non-arbitrary direction, a random
geometry, called Voronoi Diagram, is used for the elementmeshing.
The properties of the springs are determined so that theelements, when combined together, enable to predict the
behavior as accurate as that of the experimental result. In
this study, the 3D simulation system and original
constitutive model were developed by Eddy et al., is used.
[2]. The corrosion expansion model and spatial corrosion
model used in this paper were developed in the previous
studies by authors. [3,4]3. EXPERIMENT
3.1 Concept of experiment
In this study, the changing of bond at interface when the
corrosion occurs is investigated. In general, the bonding
mechanism between rebar and concrete involves
mechanical bond and frictional bond. By the pull-out testof concrete specimen reinforced with the round bar, theresistance force is only the friction bond which can becalculated by the rebar-concrete contact area and the
maximum pull-out capacity. While, by the pull-out of
deformed bar reinforced specimen, the resistance force isthe contribution of both the friction bond and themechanical bonds. Therefore, by performing the pull-out
test on different corrosion degree specimens, the changing
of these bonds due to the corrosion can be extracted(Figure 2).

2. RIGID BODY SPRING MODEL (RBSM)
In this study, the corrosion model simulation isdeveloped based on three-dimensional RBSM. In RBSM,
a three-dimensional reinforced concrete model is meshedinto polyhedral rigid elements whose phases areinterconnected by a normal spring and two shear springs.
Each rigid body consists of 6 degree of freedoms, i.e. 3transitional degrees of freedom and 3 rotational degrees of
freedom at some points within its interior and connectswith other rigid bodies by 3 springs, i.e. 2 shear springsand 1 normal spring [1,2]. Response of the spring provides
the interaction between rigid elements.
This method simulates failure behavior by solving theequilibrium of forces of springs placed between rigid
elements. Two types of elements, concrete and steel, areused to define the geometry of reinforced concrete. Sincecrack direction may affect crack patterns, the size of each

Rigid body
Element 1

Degree of freedom
3 Transitions
3 Rotations
Figure 1: Elements in RBSM

11

Rigid body
Element2

3 springs
1 Normal spring
2 Shear springs

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 08

3.2 Experiment sequence
In the experiment, the concrete specimens where thesingle round bar or deformed bar is placed are prepared.
For each specimen, after around 28 days curing in wet
condition, the electrical acceleration corrosion test was
performed to accelerate the corrosion process at the rateof 0.11A
Figure 3 shows the corrosion acceleration test. The pullout test is then performed for investigating the changing
of the bond at different corrosion percentage. However, at
this stage, the cover concrete has the corrosion cracking
due to the rust expansion so that the pull-out capacity
obtained here includes the effect of concrete damage.
Therefore, in this study, second pull-out test of thespecimen by casting new concrete is performed.
After the pull-out test on the cracked concrete specimen,
the concrete cover is removed, and the corroded bar istaken. The rebar is placed again as a reinforcement in thecasting of new specimen. After around 28 days of curing
under wet condition, the specimen is tested by the pull-out
test to investigate the changing of the bond without theeffect of cracked concrete.
Figure 4 shows the form work of specimens thatreinforced with a corroded rebar. Figure 5 shows the pullout test experiment.
Friction bondFriction bond(a) Round bar(b) Deformed bar

3.3 Mix proportion of concrete
The mix proportion of concrete used for specimens isshown in Table 1.
3.4 Overview of specimens
Table 2 shows the list of specimens tested in this study.
Figure 6 shows the specimen layout and the pull-out test
condition of specimen reinforced with deformed bar (orround bar). Single reinforcement is embedded in eachrectangular concrete specimen. The test specimen isbasically a concrete cube 200mm×150mm×150mm witha bar embedded coaxially. Two types of 16 mm diameter
rebars are prepared, plain bars and deformed bars withsame embedment lengths. To achieve 100 mm embedment
length at the free end of the specimen, plasticine is used
to unbond the bars from the concrete over 100mm lengthfrom the pull-out end.
3.5 Steel corrosion acceleration experiment
Steel corrosion acceleration is conducted at 28 days
after casting in order to create the corrosion along thelongitudinal reinforcement. The specimens are provided
electricity of 0.11A at different time to create different
corrosion percentage along the rebar as show in Table 2.
The steel weight loss of steel bar is obtained by measuring
the unit weight loss of steel after the pull-out test.

(a) Removal of corroded bar

Mechanical bondFigure 2: Resistance mechanism in pull out of round bar
and deformed bar

Single reinforced
specimenDC(b) Formwork of corroded reinforcement specimen

3%
NaCl
Solution

Figure 4: Preparation of corroded reinforcement specimen

Stainless plate

Figure 5: Pull-out test
100

100

30

unbond150

DB16 SD345

200

Figure 3: Corrosion acceleration test

150

Figure 6: Specimen dimension (Unit:mm)

12

150

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 08

Table 1: Concrete mix proportion
Gmax
Slump
W/C
(mm)
(cm)
[%]
25
8±2
0.60
Table 2: List of specimens

S/A
[%]
0.45

Name

Reinforcement

RB-0W-NC
RB -1W-NC
RB -2W-NC
RB -4W-NC
DB-0W-NC
DB-2W-NC
DB-4W-NC

Round barRound barRound barRound bar
Deformed
Deformed
Deformed

Round bars

water
169

Unit weight kg/m3
cementFine aggregate
283
823

Current-time forcorrosion (amp-hours)
0
18.5
37
74
0
37
74

Deformed bars

Corrosion 0 %Corrosion 10.5 %Corrosion 5.3 %Corrosion 23.1 %𝑀𝑀𝑠𝑠ℎ𝑒𝑒𝑒𝑒𝑒𝑒 = 200 −Capacity (%)

250
200

Equation (1)

50
0

0

5

10

100

0.5𝑥𝑥+1(1)

4.2 Deformed bar Pull-out test results
Figure 9 shows the pull-out capacities of corroded
deformed bar with non-crack concrete. In case of pull-out
of corroded bar, it is obvious that even the corrosion
degree increases up to 23.1%, the pull-out capacity has
almost no change (less than 3% decreases comparing with
the no corrosion condition). It can be assumed that the
total bond of the pull out of the corroded deformed bar
without concrete damage does not change.
To extract the mechanical bond changing from the totalbond, super position theory was assumed. The frictionalbond in Equation (1) was subtracted from the total bond.
The remaining mechanical bond are shown in Figure 10.
However, the reduction trend of mechanical bond shownin Figure 10 containing many local behaviors such as the
knot deformation, the remaining of rust at interface, thesliding-opening effect and so on. Therefore, a simple
linear Equation (2) is proposed to represent the reduction
from these behaviors.

Figure 7: Corroded round bars and deform bars fromcorrosion acceleration test

100

No cracking

Corrosion level
Weight loss (%)
0
3.0
5.3
12.1
0
10.5
23.1

corrosion degree, Mshear is the modification factor of shear
spring at the corroded interface in RBSM

Corrosion 12.1 %

150

1023

Concrete condition

Corrosion 0 %Corrosion 3.0 %AE[g/10L]
13.3

Coarse aggregate

15

Corrosion degree (%)
Figure 8: Pull-out capacity of corroded round bars

70

4. EXPERIMENTAL RESULTS AND MODELINGOF INTERFACE
4.1 Round bar pull-out test results
Relationship between the steel weight loss percentage
and the pull-out capacity obtained by tests is plotted in
Figure 8. In the pull-out tests, all specimens fail by theslipping out at the interface between rebar and concrete,
which means there is no cracking occurred in concrete
phase. The pull-out capacity increases by the corrosion
because the friction is increased by the rust and change of
surface geometry.
From the results, the constitutive model for the shear
spring in RBSM to present the change of friction is
proposed by the following Equation (1). Where x is the

Capacity (kN)

60
50
40
30
20
10
0

0

5

10

15

20

25

Corrosion degree (%)
Figure 9: Pull-out capacities of corroded deformed bars

13

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 08

120

Total bond100

Capacity (%)

location as in the experiment. The load is given at the twopoints above the beam. The friction of interface between
the loading or support plate and the beam is removed. The
model contains 62,458 elements. The input tensile
strength of steel bar and concrete are 388 MPa and 3.24
MPa, respectively. Expansive strain is applied to theinterface between rebar and concrete for generating thecorrosion expansion. Subsequently, the mechanicalloading is given in the same manner as experiment. Figure
12 shows the reinforced concrete beam simulation by
RBSM in this study.

80
60
40

Friction bondEquation (1)(inverse)

Mechanical bondEquation (2)

20
0

0

5

10

15

Corrosion degree (%)

20

25

5.2 Corrosion patterns
In this study, the simulations of the models of noncorroded and corroded beams with different corrosion
patterns are carried out for investigating the effect of
spatial corrosion pattern on the capacity of RC beam.
Two different steel weight loss profile are set for thesimulations. The first corrosion case is the uniform
corrosion pattern at 25.5 percent along the bar. Secondcase is non-uniform corrosion obtained from 3D x-ray
technique as shown in Figure 13 where the corrosion wasmeasured every 5mm. The spatial variable steel weightloss is start from 250 mm to 1,090 mm in rebar length
direction. The other zone, 0 to 250 and 1090 to 1490 mm,
does not have information from the experiment, so the
corrosion level is set as uniform corrosion pattern at
25.5 % in the simulation.

Figure 10: Modeling of mechanical bond reduction

𝑀𝑀𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 = 100 − 𝑥𝑥(2)

Where Mnormal is the modification factor for the normal
spring stiffness spring at the corroded interface in RBSM
and, x is the corrosion percentage.
5. CORRODED BEAM SIMULATIONThis chapter aims to validate the applicability of thenumerical models proposed in this study. By the
combination of the spatial corrosion model, the expansive
strain model, and the bond deterioration model into
RBSM simulation, it can consider the changing of steel
properties and expansion damage on adjacent concrete
based on steel weight loss, the bond deterioration and thenon-uniformity of corrosion pattern [3,4]. In this study the
corroded beam models are simulated. The loading test of
corroded beam by S. Lim et al. [5] is referred.
Reinforcements in the simulation are modified at every 5
mm based on corrosion profile obtained from theexperiment.
Figure 11 shows the dimension of beam done by S.
Lim et al. An experiment of corroded RC beam wasconducted to study the effect of local corrosion conditionon the capacity of the beam. After the corrosion
acceleration test, the digital camera and X-ray techniquewere used to measure the corrosion profile along the rebar
every 5 mm. Then, the corroded beams were subjected tothe mechanical loading test to investigate the residual
capacity.
Figure 13 shows the steel weight loss profile along therebar of beam specimen by X-ray apparatus. The average
corrosion degree is 25.54%.

5.3 Analysis results
5.3.1 Load-displacement relationship
Load-displacement relationships of simulation resultswith the experimental data are shown in Figure 14. The
load is defined as the total force acting at two pin points,
while the displacement is the vertical displacement ofloading point in the downward direction. The maximum
capacity of each simulation case is 24.0 kN, 18.3 kN and12.6 kN for the no corrosion case, the uniform corrosion
case and the spatial corrosion case, respectively. In theexperimental specimen, it was reported that the steel bar
was yielded, and the specimen showed flexural behavior
before the failure by reaching the shear capacity shown by
the dot line in Figure 14. In case of simulation, beam withcorrosions shows lower stiffness and capacity than the no
corrosion case due to initial damage from corrosion which
are bond deterioration and steel cross section reduction.
Since the critical corrosion cross-section is located at the
middle span, the stiffness of each beam is clearly different
between no corrosion, uniform corrosion and non-uniform
corrosion case. Comparing with the no corrosion case, thecorroded beam’s stiffness becomes close to theexperimental result. In terms of the capacity, it reduces by
the corrosion in the simulation. Non-uniform case shows
the higher reduction because of the local severe corrosionin the model that indicates the necessity of considering the
local corrosion to evaluate the residual capacity of thedamaged reinforced concrete reasonably.

5.1 Geometry of simulation model
The analysis model used in this study is formed up
based on the experiment. The size of RC beam is
1,460×140×80 mm3 reinforced with a DB13 rebar.
Analysis model is meshed into meso-scale elements
having average sizes approximately 10×10×10 mm3. Two
pin supports and two loading points are set at the same14

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 08

P/2

490
4-DB6@165

280

P/2

490
4-DB6@165

Wood stick

100
140

100

1-DB1370
Figure 11: Dimension of beam in corrosion acceleration experiment
100

490

280

100

490

140
DB6@165

DB13

Steel weight loss (%)

Figure 12: Geometry of numerical model by RBSM (Unit: mm)
80
70
60
50
40
30
20
10
0

250

350

450

550

650

750

850

950

1050

Length of specimen (mm)Figure 13: Local steel weight loss along the bar length

5.3.2 Crack patterns at failure
Figure 15 shows the internal crack pattern and the 3D
surface overview crack of uniform and non-uniform
corrosion simulations. For the corroded beam, corrosion
crack along the longitudinal rebar length can be observedat the bottom of the beam. After the loading, in case of no
corrosion and uniform corrosion case, the beam failure
pattern indicated a flexural failure. Flexural cracks can beobserved between the loading point pin location which is
the maximum moment span. (Figure 15(a)) For the
corroded beam with non-uniform corrosion pattern, ashear failure pattern can be observed as shown in Figure
15 (c). Shear crack occurred at the left shear span of thebeam. This cracking is corresponding with the critical
corroded cross-section. This result indicates that the initial
crack damage from local corrosion can lead to the
propagation of shear crack in the left span of the beam.
Considering this effect, the beam simulation with nonuniform corrosion damage can present the similar failure
pattern as the experiment correctly.

No corrosion
Uniform
nonuniform
Experiment

25

Load (kN)

20
15
10
5
0

0

5
Displacememt (mm)10Figure 14: Load-displacement relationships

15

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 08[2] L. Eddy, K. Nagai (2016) "Numerical Simulation of
Beam-column Knee Joints with Mechanical Anchorages
by 3D Rigid Body Spring Model", Engineering Structures,Vol. 126, pp.547-558[3] P. Jiradilok, K. Nagai and K. Matsumoto, (2017),“Development of Spatial Corrosion Damage Simulation
based on Rigid Body Spring Model.", The 6thInternational Doctoral Symposium, Hokkaido University,
Hokkaido, Japan[4] P. Jiradilok, K. Nagai and K. Matsumoto, (2018),“Development of non-uniform corroded RC member
simulation based on Rigid Body Spring Model.”, 12th fib
International PhD-Symposium in Civil Engineering,
Czech Technical University, Prague, Czech Republic[5] S. Lim, M. Akiyama and D. M. Frangopol, (2016),“Assessment of the structural performance of corrosionaffected RC member based on experiment study andprobabilistic modeling”, Engineering structures 127,
pp.189-205

0.1 mm crack width
0.3 mm crack width(a) Internal crack pattern (uniform-corrosion)
0.3 mm crack width(b) Internal crack pattern (non-uniform)

Deformation × 10(c) Overview crack pattern (non-uniform)(d) Crack pattern in experiment

Figure 15: Failure patterns in simulations and experiment
6. CONCLUSIONS
1. The simulation system for evaluating the residual
capacity of corroded RC beam considering the effects of
the rust expansion, the bond deterioration, the rebar
reduction, and the non-uniformity of corrosion pattern isdeveloped.
2.The constitutive models of the bond deterioration bycorrosion were reasonably developed based on thedesigned experiment. To extract the changing of thefriction bond and the mechanical bond, the pull-out
experiment program of concrete specimens reinforced
with corroded round bar and corroded deformed bar atdifferent corrosion percentage without corrosion cracking
damage, were performed. The new constitutive model ofshear spring and normal spring were proposed based on
the changing of maximum pull-out capacities at different
corrosion degree.
3. To validate the applicability of the new constitutive
model, the corroded RC beam simulation were carried out
using the new constitutive model. The simulation results
show the reasonable results comparing with theexperiment. The stiffness reduction and the residual
capacity of corroded beam due to the initial damage fromcorrosion were simulated well. The non-uniform
corrosion simulation showed the similar failure pattern as
the experimental result.
REFERENCES[1] K. Nagai, Y. Sato, T. Ueda, (2005) “Mesoscopic
Simulation of Failure of Mortar and Concrete by 3D
RBSM”, Journal of Advanced Concrete Technology, Vol.3,
pp.385–402
1617th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 16

NUMERICAL MODELLING OF RADIATING BOUNDARY CONDITIONS COMBINED FOR
WAVE PROPAGATION IN NONLINEAR UNBOUNDED DOMAIN
R.S. Badry1, P.K. Ramancharla2
1

Research Scholar, IIIT Hyderabad, Ravishankar.Badry@research.iiit.ac.in (corresponding author)

2

Professor and Registrar, IIIT Hyderabad, ramancharla@iiit.ac.in

Keywords: Absorbing Boundary Conditions, Nonlinear material, Soil-Structure-Interaction, Finite Element Method,
Explicit Time Integration
1. INTRODUCTION
The effect of radiating boundary conditions on
numerical simulations is one of the important aspects insoil structure interaction problems. As soil is a nonlinear
medium, the boundary conditions have to consider the
nonlinear behaviour to accurately resemble the wave
propagation. To address the radiating boundary condition
problem,
researchershavedeveloped
variousformulations, such as Local Absorbing Boundary
Conditions [1], Absorbing Layers techniques (which
includes Perfectly Matched Layers [2], Caughey
Absorbing Layer Method [3] and Absorbing Layers by
Increasing Damping [4]), Boundary element method [5]and Infinite elements [6]. With the exception ofabsorbing layer techniques, the above methods are notappropriate for simulating wave propagation throughnonlinear material. Meanwhile, the absorbing layer
methods require large number of layers or highcomputational complexity.
This paper presents a new radiating boundary
condition for wave propagation in nonlinear material.
The efficiency of the proposed methods has been verified
for both 1D and 2D wave propagation problems and theaccuracy is compared with extended meshed models.
The study concludes that better responses can beobtained by using the proposed approach when comparedwith traditional Local Absorbing Boundary Conditions.
The proposed method inherently considers the relaxation
due to plastic deformation beyond the numerical domainboundary
2. METHODOLOGY
The proportionality relation between the incremental
velocity
and incremental strain
is established by
von Karman [7] for 1D nonlinear wave propagation
problems
(1)

……

(2c)

where,,, andare the incremental particle
velocities in ,and directions respectively.
is the axial strain.
, andare the shear
strains.
andare the p-wave and s-wave
propagation velocities respectively. Let,,andare the known incremental particle
velocities at timein boundary local , anddirection, then the incremental strains near the boundary
can be obtained using equation (2)
(3a)
(3b)
(3c)
where,
andare the p-wave and s-wave
propagation velocities at the instantaneous strainscomputed near the boundary at time . The wave
propagation velocities are estimated from the tangent
material matrix computed at previous time step. When
the waves impinge in normal direction to the boundary,
the incremental strain,, anddue towave propagation are assumed to be zero. Therefore, theincremental strain vector can be defined as(4)
The strain vector can be updated to next time step
using
(5)
The tangent material matrix
and wave velocities
for p-wave and s-wave can be estimated corresponding
to instantaneous strain. The absorbing stresses atthe boundary can be computed using(6)
The above equation represents the local Absorbing
Boundary Condition for nonlinear materials (NLABC).
The procedure outlined can be applied for any nonlinear
materials.

where,
is the p-wave velocity corresponding toinstantaneous strain. Similar hypothesis can beapplied for 3D wave propagation problem for developing
local absorbing boundary condition assuming the waves
impinge in normal direction.
(2a)

3. RESULTS AND DISCUSSIONSIn this section, the efficiency of the proposed method isverified with pure P-wave propagation as shown in Fig. 1.
Two material models are selected to verify theapplicability of the method.

(2b)

17

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 16
the material to linear isotropic hardening material. The
tangent modulus is taken as= 1200 N/m2. Stresses
and displacements in X-direction are presented in Fig 3.
The reflections are estimated as 7.93 N/m2 and 0.82
N/m2 respectively for ABC and NLABC. The stressprofile for NLABC deviates from the extended meshmodel after 6 seconds. This indicates that current method
cannot include the effect of plastic free energy
dissipation i.e. energy dissipated due to loss of heat.
4. CONCLUSIONSIn this study, the framework to model radiating boundary
conditions for wave propagation through nonlinear
material is presented and the following conclusions are
drawn from the study
1. The method requires additional computation cost to
estimate the tangent material stress strain tensors
and wave propagation velocities corresponding toinstantaneous strains at the boundary.
2. The proposed method demonstrates that the effects
of material nonlinearities i.e. tangent stress-strain
tensor are accounted effectively.
3. The efficiency of the method is also analyzed forenergy dissipation. Two types of energy dissipation
are considered i.e. plastic deformation and plastic
free dissipation. The proposed method does accountfor the energy dissipation due plastic deformation
but not the plastic free energy dissipation. Therefore,
this method produces reflection due to plastic freeenergy i.e. when isotropic hardening is present.
4. The method assumes that propagating wave impinge
the boundary in normal direction. If the wave
impinges any other direction, the performance ispoor and needs further investigation.

Figure 1. 2D Plane strain model for P-Wave propagation
3.1 Von-Mises elastic perfectly plastic material
Material properties chosen for the medium are initialmodulus of elasticity= 4800N/m2, Poisson’s Ration= 1/3, density = 1800kg/m3 and ultimate yield stress= 5N/m2. The analysis has been carried out for 10
seconds and time variation of load is considered using a
Gaussian wavelet with time shift= 4 seconds andpeak frequency = 1Hz. Stresses and displacements in
the X-direction due to pure p-wave propagation in themedium are presented in Fig 2. The reflections are
estimated as 10.71N/m2 and 0.47N/m2 respectively for
ABC and NLABC. This concludes that the NLABC
includes the energy due to plastic dissipation energy
effectively.

REFERENCES[1] J. Lysmer., R.L. Kuhlemeyer., (1969). “Finite
dynamic model for infinite media”. Journal ofEngineering Mechanics. Div ASCE 95(EM4):859–877.
[2] J.P. Berenger., (1994) “A perfectly matched layer forthe absorption of electromagnetic waves.” Journal ofComputing in Physics; 114(2):185–200.
[3] J.F. Sembalt., L. Lenti., G. Ali., (2010) “A simple
multi directional Absorbing Layer method to simulate
elastic wave propagation in unbounded domains”,
International Journal for Numerical methods inengineering; 1: 1-22.
[4] P. Rajagopal, M. Drozdz, E.A. Skelton, M.J.S. Lowe,
R.V. Craster, (2012) “On the use of absorbing layers tosimulate the propagation of elastic waves in unbounded
isotropic media using commercially available finite
element packages”, NDT&E Int. 51:30–40.
[5] P.K. Banerjee., R. Butterfield., (1981). Boundary
element methods in engineering science. McGraw-Hill
Book Co.
[6] P. Bettess., (1978) “Infinite elements”, International
Journal for Numerical Methods in Engineering;11:54-64.
[7] T. von Karman., and P. Duwez., (1950), “Thepropagation of plastic deformation in solids”. J. App.
Phys., 21:987-994.

Figure 2: a) Stress at 2m and b) Displacement at 3m in
the X-direction for elastic perfectly plastic material
3.2 Von-Mises Isotropic linear isotropic hardening
material

Figure 3: a) Stress at 2m and b) Displacement at 3m in
the X-direction for linear isotropic hardening material
The model described for elastic perfectly plastic material
including analysis time and loading is used by changing

18

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 09

CAUSE ESTIMATION AND PROPOSAL OF INSPECTION METHOD FOR DAMAGED PC
SLEEPERS OF INDIAN RAILWAYS
K. MATSUMOTO1, K. NAGAI2, R. SUNDARAM3, and A. AWASTHI4
1

Project Assist. Prof., ICUS, IIS, The Univ. of Tokyo, Tokyo, Japan, km312@iis.u-tokyo.ac.jp (corresponding author)
Associate Prof., ICUS, IIS, The Univ. of Tokyo, Tokyo, Japan, nagai325@iis.u-tokyo.ac.jp
3
Engineer, Sumitomo Mitsui Construction Co. Ltd., Tokyo, Japan, rajacz11@gmail.com
4
Deputy Chief Engineer, Construction Organization, Indian Railways, India, anupamawasthi1978@gmail.com
2

Keywords: Delayed Ettringite Formation (DEF), Alkali Silica Reaction (ASR), Sleepers, Prestressed Concrete
1. INTRODUCTION
Indian railways uses prestressed concrete (PC) sleepers
made by pretension system in factories for its railway
trucks. Sleepers are members which directly carry weightof train cars, therefore they are quite important for thesafety transportation. Recently, a number of the PC
sleepers are damaged by cracks after 6 to 9 years of
production. These cracks are also seen in sleepers which
are not used, even though any loads has not been applied
to them. Figure 1 shows typical damages observed in thesleepers. According to the survey conducted in the central
region of India, 45,000 of 128,000 sleepers in 100 km
range of a train line are damaged by the cracks. This
number corresponds to 35% of the total number sleepers.
Consequently, Indian railways are facing to a problem
related to passenger’s safety transportation.
This study aims to determine the cause of damage in thesleepers, clarify mechanical performances of the sleepers
in both material and structural level, and propose aninspection method for the existing sleepers. To determine
the cause of the damage, Scanning Electron Microscope(SEM) for samples taken from the PC sleepers was carriedout. To clarify mechanical performances of the damaged
PC sleepers in material and structural level, compressive
tests of core samples taken from the sleepers and loading
tests of the damaged sleepers were conducted. In addition,
an evaluation method for determining damage levels fromcrack patterns which can be seen on the outer surface ofthe sleepers was proposed based on the structural
performances observed in the loading tests.

Map cracks (end parts)

2. MANUFATURING CONDITION OF SLEEPERS
To know the temperature rise inside the concrete during
steam curing, field measurement of temperature using
thermocouples and data-logger was performed in a
concrete sleeper plant in India. For a sleeper, temperature
was measured at two points, one inside the sleeper where
maximum temperature is expected and one just outsidethat point.
Figures 2 shows the result of the temperature
measurement. The measurement reveals that the
maximum temperature reached inside concrete is over
80°C. Therefore, it is very well established that concretetemperature is beyond the critical temperature for theoccurrence of Delayed Ettringite Formation (DEF)
problem (as mentioned by Ghorab et al. [1], Heinz andLudwig [2], Hanehara and Oyamada [3]). The temperatureinside concrete generally follows the trend of temperature
outside concrete but becomes more than the outside
temperature after approximately 6 and 1/2 hours of casting.
This depicts the effect of heat of hydration in addition tothe outside curing temperature.
3. CLASSIFICATION OF DAMAGE LEVELS
Table 1 shows classifications of damage levels of thesleepers, which are expected to be used to evaluate
inspection results in the field. The damage levels are
determined according to the maximum crack width andnumber of cracks. There are four damage levels, which are“No damage”, “Mild damage”, “Moderate damage” and“Severe damage”. The reason why the damage levels are

Longitudinal cracks (center parts)

Diagonal cracks (insert

Figure 1: Typical crack patterns observed in the damaged PC sleepers of Indian Railways
1917th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 09(a) Severe damage

Figure 2: Temperature change during steam curing
Table 1: Classification of damage levels
Grade

DesignationI

No damageII

Mild damage

III

Moderate damage

IV

Severe damage

Width and number ofcracks
No cracks
Less than 1 mm max
width
Larger than 1 mm andless than 2 mm width,or single crack
Larger than 2 mm widthand multiple cracks(b) Moderate damage

determined from width and number of cracks is that
expansion strain of the concrete caused by DEF and Alkali
Silica Reaction (ASR) seems has a correlation with them.
After several times of discussion with Indian Railways,
by classifying the damage levels into four categories
shown in Table 1, it was confirmed that they can considera realistic replacement plan of the 45,000 pieces of
sleepers.
4. INVESTIGATION BY SCANNING ELECTRONMICROSCOPE (SEM)
To investigate cause of the premature cracking of
sleepers, different damage levels of samples, “Moderate
damage” and “No damage” were collected. The
specimens are prepared by embedding small pieces ofsamples (approximately 1 cm x 1 cm x 1 cm) from eachof the three categories into epoxy resin solution. Epoxy
resin facilitate mounting of small pieces of concrete
samples, which is polished to view the microstructure ofconcrete under SEM. After hardening of the epoxy resin,these specimens are cut and the exposed surface is grindedby using polishing abrasives. Then the polished surface iscoated with platinum, which is needed to prevent the
charging of specimen with the electron beam.
Figures 3(a), (b) and (c) show the typical SEM imagesof the specimen of “Severe damage”, “Moderate damage”
and “No damage” sleepers, respectively. In the cases of(c) No damage
Figure 3: SEM images of samples“Severe damage” and “Moderate damage” sleepers, it
reveals that there is ettringite deposition around theinterface of aggregate and paste. Also, ettringite could benoticed inside the paste. Few coarse aggregate also show
some porosity and cracks inside them but ASR gel like
substance is not noticed. On the other hand, in the case of“No damage” sleepers, it is observed that the interface of
aggregate and paste seems to be intact and no ettringite
formation has been noticed either in the C-S-H gel or at
the interface of aggregate and paste. Apart from this, no
ASR gel like substance is noticed.

20

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 09

Table 2: Damage level and manufacturing year ofcut sleepers
No.
1
2
3
4
5
6
7

Damage level
I
I
II
III
IV
IV
IV

Table 3: Damage level and manufacturing year of
sleepers used for taking core samples
Damage
level
I
I
II
IV

Manufacturing year
2015
1986
2006
2006
2002
2006
2002

Section (1) Section (2)Manufacturing
year
2015
1986
2006
2006

Number of
taken samples
22
2
2

Section (3)Figure 5: Core samples of "Severe damage" sleepers

Section (1)(a) No damage (manufactured in 2015)

Section (2)(b) No damage (manufactured in 2002)(c) Mild damage (manufactured in 2002)

Section (3)Figure 4: Inner crack patterns in cut cross sections
The results of SEM suggests that delayed ettringite
formation might be the cause of premature damage in theconcrete sleepers in India. However, occurrences ofalkali-silica reaction also cannot be denied. ASR gel like
product, in one of the “Severe damage” sleeper sample,
suggests that ASR might have taken place. There are
evidences that high early age temperature in concrete
triggers both ASR and DEF ([4] and [5]).

(d) Severe damage (manufactured in 2002)
Figure 6: Damage conditions of sleepers for sample
coringIn each damage level, depth of the cracks is about 20 to
30 mm. The cracks do not progress to the central part ofthe sleepers. Especially, crack width at the surface of“Severe damage” sleepers is larger than 2 mm, however,progress depth of the cracks is comparatively shallow.
There is a tendency that inner macro cracks are notsignificant even though severe damage is observed on thesurfaces. It can be considered that expansion of concrete
caused by DEF and/or ASR is not uniform. Occurrence of
DEF and ASR is affected by curing temperature and watercontent of the concrete. Cement hydration results the innertemperature to be higher than that near the surfaces. Also,
depending on the environment condition around thestructures, outside and inside water content becomes

5. CRACK PATTERNS AND MECHANICALPROPERTIES OF CORE SAMPLES
5.1 Crack patterns in cut cross sections
To investigate inside crack progress, several locationsof the PC sleepers were cut. Table 2 lists damage level andmanufacturing year of the cut sleepers. Figure 4 shows
typical inside crack patterns of “Severe damage” sleepers.
In the cases of “No damage” sleepers, cracks are notobserved in the cross sections.

21

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 09

and manufacturing year of the core samples. Figure 5
shows a typical crack pattern of core sample taken from
“Severe damage” sleepers. Figure 6 shows damage
conditions of the sleepers used for taking core samples.
Macro cracks were not observed in the core samples
because cracks do to progress to the inner part of thesleepers as mentioned in 3.1. However, gaps can benoticed around the aggregates. It is because only the
cement pastes are expanded by DEF as explained in theprevious study [6].

60

40
2

Elastic modulus (kN/mm )

50
40
30
20
10
0

(a) Compressive strength
Figure 7: Results of compression tests of core samples

30
20
10
0

(b) Elastic modulus

Table 4: Damage levels andmanufacturing year of
sleepers for loading tests
Damage Manufacturing
level
year
2015

Ⅰ

2015

Ⅰ

1986

Ⅰ

1986

Ⅰ

1986

Ⅱ

2006

Ⅱ

2002

Ⅲ

2006

Ⅲ

2006

Ⅲ

2006

Ⅳ

2006

Ⅳ

2006

Ⅳ

2002

Ⅳ

2002

18

Ⅰ

242

22

2015

Loading jack

LVDT

235

Ⅰ

Loading frame

180

73

497.5

22

Compressive strength (N/mm2)

different. From the above reasons, there is a possibility
that the expansion strain occurred only in the inner part ofthe sleepers. When only the inner part is expanded, outerside of the concrete is subjected to tensile forces, as
observed in the ring tension problem, resulting that cracks
occur only in the outer part. Thus, crack patterns areaffected by not only amount of expansion strain but also
its spatial distribution.
5.2 Mechanical properties of core samples
Compressive loading tests of core samples taken fromthe sleepers were conducted. Table 3 lists damage levels

280

Sleeper

280

1195

497.5

SupportFigure 8: Apparatus of the loading test of sleepers (unit: mm)
Flexural crack

Crack induced by DEF and/or ASR

Crushing

Figure 9: Failure pattern of “Severe damage” sleeper

22

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 09
300

II: Mild damage
III: Moderate damage

I: No damage

Load (kN)

Experiment (kN)

I: No damage

IV: Severe damage

200

IV: Severe damage

100

0
Mid span deflection (mm)

II: Mild damage

200
100
Calculation (kN)

300

Figure 11: Comparison between calculated
and experimental values of flexural capacities

Peak load (kN)

Figure 10: Load-mid span deflection relationships

Figure 12: Peak loads versus crack patterns induced by DEF and/or ASR
Figure 7 shows the compressive strength and elastic
modulus of the core samples. The elastic modulus wascalculated based on Japanese Industrial Standard [7]. The
results are slightly scattered, but there is a tendency thatthe elastic modulus decreases in the order of “No damage”,“Mild damage” and Moderate damage” while thecompressive strength is almost constant. In the case of“Severe damage”, both compressive strength and elastic
modulus significantly decreased. Compared to “Nodamage”, compressive strength and elastic modulus of“Severe damage” cases reduced by 42% and 17%,
respectively. It reveals that mechanical properties ofconcrete decrease by gaps around the aggregates even if
macro cracks do not occur.

simply supported condition were conducted. Table 4 lists
damage levels and manufacturing years of the PC sleepers
used for the loading tests. The tests were conducted byload control. The applied load was measured by load cells
provided between the sleeper and the loading frame. The
mid span deflection is calculated from displacements
measured by Linear Variable Differential Transformers(LVDTs) installed at the mid span and supporting points.
Figure 8 shows apparatus of the loading tests.
Figure 9 shows the failure pattern of “Severe damage”
sleeper. After flexural cracks progressed, concrete wascrushed at the compression fiber and the load suddenly
decreased. The PC strands were not yielded, indicatingthat the failure mode was flexural compression failure.
Figure 10 shows load-mid span deflection relationships.
Especially in the case of “Severe damage” sleepers, bothmaximum load and member stiffness are reduced.
Average of the maximum loads of “Severe damage”
sleepers decreased to 69% of that of “No damage”
sleepers.

6.
INVESTIGATIONOFSTRUCTURALPERFORMANCES OF DAMAGED PC SLEEPERS
6.1 Loading test
To investigate the structural performances of thedamaged PC sleepers, two-point loading tests in the23

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 09

Figure 11 shows the relationships between the
maximum loads and crack patterns before the loading(that is, cracks caused by DEF and/or ASR). With wider
crack width and larger number of cracks, the maximum
load tends to decrease. It indicates that the damage levels
determined by the method shown in Table 1 has acorrelation with the structural performances. From thisresult, this study proposes classifications listed in Table 1
as an evaluation method for determining replacement
priority of the damaged PC sleepers of Indian Railways.
6.2 Flexural capacity evaluation by macro equations
To investigate the possibility to evaluate flexural
capacities of the existing damaged PC sleepers by usingmaterial test results of core samples, the flexural
capacities are calculated by macro equations and comparethem with the experimental results. In the calculation, ageneral method for calculating flexural capacities of PC
members, in which plain strain distribution is assumed, isused. The test results of core samples (average values inFig. 7) are used for compressive strength and elastic
modulus of concrete. The equivalent stress block is
assumed for stress distribution of concrete in thecompression zone. In this calculation, the effect ofconcrete expansion and bond loss of PC strands onprestress is not considered.
Figure 12 shows comparison between the calculationand the experimental results. The calculated capacity
almost agrees with the experimental result in the case of“No damage” sleeper. However, in the case of “Milddamage”, the calculation overestimates the capacity. It isconsidered that the compressive strength of the coresamples in “Mild damage” cases is excessive. On the other
hand, in the case of “Severe damage” sleeper, thecalculation underestimates the capacity even though given
compressive strength is obtained from the core samples
which do not contain macro cracks. The failure mode in
the calculation of “Severe damage” sleeper is almost near
the compression failure of concrete just after theprestressing, however, such a behavior is not noticed in
the experiment before the loading. One of the possible
reasons is that prestress levels of the actual PC sleepers
are decreased by bond loss of the PC strands after theconcrete expansion. It is not easy to exactly predict theprestress loss due to expansion. However, this study
confirmed that the macro equation can evaluate thedecreasing tendency of flexural capacities according to thedamage levels.

3) An evaluation method for determining damage levelsof PC sleepers of Indian Railways deteriorated by
DEF and/or ASR was proposed. In the proposed
method, damage levels are classified into “Nodamage”, “Mild damage”, “Moderate damage” and“Severe damage”.
4) The damaged PC sleepers were cut and inner crack
patterns were investigated. Even “Severe damage”
sleepers, cracks do not progress to the inner part. It isbecause the expansion strain occurs in only the innerpart. Thus, not only amount of expansion strains but
also spatial distributions of the expansion strain affects
crack patterns.
5) Compression tests of core samples taken from thedamaged sleepers revealed that compressive strengthand elastic modulus significantly reduced in the caseof “Severe damage” even though macro cracks are notobserved. There is a possibility that mechanicalproperties of concrete affected by DEF decrease eventhough cracks on the surface are not visible.
6) According to the result of the loading tests of damaged
PC sleepers, flexural capacities tend to decrease in thecases that DEF and ASR induce wider crack width andlarger number of cracks. It indicates that the damage
evaluation method proposed in study seems to beappropriate.
REFERENCES[1] H.Y. Ghorab., D. Heinz., U. Ludwig., T. Meskendahl.
and A. Welter., (1980) “On the Stability of Calcium
Aluminate Sulphate Hydrates in Pure Systems and in
Cements,” 7th International Congress on Chemistry of
Cement, Vol. IV, pp. 496-503.
[2] D. Heinz. and U. Ludwig., (1987) “Mechanism ofSecondary Ettringite Formation in Mortars and Concretes
subjected to Heat Treatment,” American Concrete
Institute, SP 100-105, Detroit, pp. 2059-2071.
[3]S. Hanehara. and T. Oyamada., (2010) “Reproductionof Delayed Ettringite Formation (DEF) in Concrete andRelationship between DEF and Alkali Silica Reaction,”
Monitoring and Retrofitting of Concrete Structures- B. H.
Oh, et al. (eds) 2010 Korea Concrete Institute, Seoul,ISBN 978-89-5708-181-5.
[4] M. Thomas., K. Folliard., T. Drimalas. and T.
Ramlochan., (2008) “Diagnosing Delayed Ettringite
Formation in Concrete Structures,” Cement and Concrete
Research, Vol. 38, pp. 841-847.
[5] L. Baingam., W. Saengsoy., P. Choktaweekarn. and S.
Tangtermsirikul., (2012) “Diagnosis of a Combined Alkali
Silica Reaction and Delayed Ettringite Formation,”
Thammasat International Journal of Science andTechnology, Vol. 17, No. 4, pp. 22-35.
[6] C. Famy., (1999) “Expansion of Heat-cured Mortar,”Ph.D Thesis, Imperial College of Science, Technology andMedicine.
[7] Japanese Industrial Standards, (2017) “JIS A 1149:
Method of Test for Static Modulus of Elasticity ofConcrete.”

7. CONCLUSIONS
1) Temperature change during steam curing wasmeasured in the factory of PC sleepers of IndianRailways. It revealed that the inner temperature of theconcrete exceeds 80°C at the maximum. There is ahigh possibility of the occurrence of DEF.
2) Samples were taken from the damaged sleepers andSEM analysis was conducted. It was observed that
gaps are formed around the aggregates and the gaps
are filled with ettringite. It also indicates theoccurrence of DEF.

24

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 07

EFFECT OF SUB-STRATA LENGTH VARIATIONS ON SEISMIC PERFORMANCE OF MULTISTOREY STRUCTURE WITH RAFT AND PILE FOUNDATION
M.S. ANU1, V.S. VANI,2 R.R. RAJESWARA3, and M.NEERAJA4
1

PG student, Civil Engineering Department, GITAM deemed to be University, Vizag, India, anuavanthika1@gmail.com
Asst.Professor, Civil Engineering Department, GITAM deemed to be University, Vizag, India, drvsvani@gmail.com
3
Asst.Professor, Mechanical Department, GITAM deemed to be University, Vizag, India, r.resapu@gmail.com
4
Asst.Professor, Civil Department, GITAM deemed to be University, Vizag, India, medapatineeraja@gitam.edu
2

Keywords: L/D Ratio, ANSYS APDL, Soil structure-interaction, Raft, Pile Foundation, Seismic Performance
1. INTRODUCTION
Urbanization in the name of smart city is increasing day
by day. These smart cities need to accommodate
migrated people, resulting in growth of construction
activities. The increased construction activities are
imposing more loads on earth’s crust especially in urban
lands. Also deep foundations from the constructed multistorey structures may also create disturbances on earth’s
crust changing profile of sub structure strata. This may
result in movement of tectonic boundaries thereby
increasing earthquake occurrences in recent past. During
an earthquake lot of infra-structure damage is observed
and the major damage is to structures. It is observed thatinteraction of surrounding sub-strata along withfoundation plays a major role in response of structuresduring earthquake. The properties of surrounding soil tothe structure and type of foundation also influencestructural deformations and storey shears.

Figure 1: Model of G+5 Structure
The model with varying lengths (20, 40 and 120 m) withconstant depth (20 m) is analyzed for using transient
analysis by using El-Centro earthquake data [3]. The
variations in seismic parameters like displacement andbase shear is studied. An attempt has been made tocorrelate seismic parameters (peak displacement,
maximum base shear ) with length to depth (L/D) Ratios

2. LAYOUT OF TEXTPREVIOUSSTUDIES
Gaikwad M.V et.al[1], Sharmila Belkar et.al [2] etc.,studied soil structure interaction considering seismic
effects. Their studies concluded that the seismicparameters related to structure are affected by sub-strata
that include type of soil, foundation.
METHODOLOGY
A G+5 RCC structure is modelled along with foundation(raft and pile), soil (marine clay) and bedrock (granite)
considering Visakhapatnam sub-strata. It is modelled ascontinuum element using Ansys APDL. The dimensionsof the model (Figure1) are given in Table 1.
Table 1: The details of the model
Structure Height18 m
No. of floors & bays
G+5 & 4Height of each floor
3m
Area
Column & Beam size
Soil dimensions

Figure 2: Total displacement of structure with varying
lengths for raft foundation

Figure 3: Total shear with varying lengths for raft
Foundation

Figure 4: Total displacement of structure with varying
lengths for pile foundation

23*23 m
0.5 m & 0.3 m (Beam 188
from Ansys library )40 * 20 m, 80 * 20 m &120*20 m (Drucker prager
model)

Figure 5: Total shear with varying lengths for pile
Foundation25

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 07

RESULTS AND DISCUSSIONS
The results obtained from the model structure after EICentro Earthquake [3] is analyzed in terms displacement
and shear for both raft and pile foundation.
It is observed from Figure 2 that the structure
exhibited more deformations when compared to soil
during earthquake in raft foundation. From the obtained
results, graph (Figure 6) is plotted between total peak
displacement and L/D ratio for nodes in structure andsoil separately. An equation is obtained for deformation(structural nodes) using regression analysis is second
degree polynomial as in (a) with R² = 1.
Y = 0.0016x2 - 0.0379x + 0.359 ----------->(a)The equation is tested for intermediate L/D ratio 3 forwhich it resulted peak displacement 0.2597. To simulate
similar conditions the opted model length is 60 m forsame constant depth 20 m. The model is analyzed andobtained peak displacement is 0.28961 for node 161. The
error obtained from above model is 12% considering
displacement in structure. Considering SSI (soil nodes)
the L/D indicates only position of peak displacements i.e.,
shifting from structure to soil through foundation.

L/D ratios.

Figure 8: Variation of peak displacement for L/D interms of varying lengths for pile foundation

Figure 9: Variation of maximum shear for L/D in termsof varying length for pile foundation
Considering shear with the help of L/D ratio (Figure 9)neither position nor value can be predicted forintermediate values.
3. CONCLUSIONS•For both raft and pile foundation, value ofmaximum shear at intermediate L/D ratios cannot be
predicted. But the position of maximum shear can bepredicted at intermediate L/D values which may occur on
the plane of foundation and structure or soil.
•
For both raft and pile foundation, value ofmaximum displacement at intermediate L/D ratios can bepredicted for length variation (as per polynomial second
degree). These values are shifting towards bottom
storeys of structure as the length increased.
•
For both foundations it is observed thatadjacent buildings to the existing building will beaffected within the range of 50 m from the adjacentbuilding.

Figure 6: Variation of peak displacement for L/D forraft foundation
Figure 3 it is observed that the shear is more in soil
structure junction at the structural base. From theobtained results, graph (Figure 7) is plotted between total
base shear and L/D ratio.
From the Figure 7 it is observed that the variation of
maximum shear shifted downward as L/D increased
considering SSI

REFERENCES
References in the text should be numbers in square
brackets like this [1]. The details of references are
required to be provided in the following format given
below.
Reference to a journal publication:[1] Gaikwad M.V, Ghogare R.B and Vageesha
S.Mathada, “Finite Element Analysis of Frame with Soil
Structure Interaction”, International Journal ofEngineering Research and Technology, 2015, Volume 4
Issue 1, PP 91-95.

Figure 7: Variation of maximum shear for L/D in termsof varying lengths for raft foundation.
From the obtained results, graph is plotted between total
peak displacement and L/D ratio for nodes in structureand soil separately for pile foundation (Figure 8). An
equation is obtained for deformation considering
structural nodes using regression analysis. It is a second
degree polynomial as in (b) with R² = 1. A correlated
equation cannot be obtained for nodes in soil.
Y = 0.0073x2 - 0.1059x + 0.5402 ----------->(b)Figure 9 shows variation of maximum shear for L/D interms of varying lengths for raft foundation. The
variation of maximum shear cannot be predicted using[2] Sharmila Belkar and Dr. Kiran Ladhane, “Dynamic
Analysis of Soil Structure Interaction of Pile Supported
Frame Structure”, International Journal of Scientific &Engineering Research, 2015, Volume 6, Issue 10, pp 704708.

26

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 07

27

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 15

AUTOMATIC AND HIGH-SPEED DAMAGE DETECTION OF REINFORCED CONCRETE
BRIDGE SLAB BY GROUND PENETRATING RADAR
T. MIZUTANI1, T. TAMAGUCHI2
1

Project lecturer, Institute of Industrial Science, , The University of Tokyo, Tokyo, Japan, mizu-t@iis.u-tokyo.ac.jp
Ph.D. Student, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan, tyamaguchi@bridge.t.utokyo.ac.jp
Keywords: Ground Penetrating Radar, Bridge Deck, Damage, Crack, Segregation, Signal Processing
2

The costs of maintenance and replacement of highway
in Japan are estimated about 4 trillion yen in 2015 whichis equivalent to a few percent of Japanese national
budget. The large percentage of the cost is for repair andreplacement of reinforced concrete (RC) bridge slabs dueto their deterioration. Countries other than Japan isconsidered to face with similar situation in present days
or in the near future. In order to maintain transportation
safety with a limited budget, inexpensive and reliablecondition evaluation techniques of RC slab should be
developed. Human-based inspection methods, such as
dense hammering test on slab surface, have been
conducted so far, however to conduct those inspection,
pavements need to be removed beforehand and lane
restrictions should be taken. As a result, those tests
become time-consuming and costly. In addition, thoseinspection result have variation because the human-based
test highly depends on the ability of inspectors.
Up to now, a variety of non-destructive testing
techniques, for example Thermography, Impact-Echo
method, Radar and etc., have been proposed anddeveloped. As a particularly promising technique in thesetechniques to detect damages inside bridge slab
automatically, radar technique which can realize noncontact and high-speed measurement is focused on inthis research. Radar techniques are already practicallyused as “Ground Penetrating Radar (GPR)” to detect
extraneous material, holes inside ground. There are sometypical damages of bridge slab which can lead to serious
damage such as holes. Horizontal cracks with width lessthan 1 mm can occur in the vicinity of upper
reinforcement bar (rebar). If horizontal cracks deteriorate
more, damage becomes “Sand-like” damage which iscalled “segregation”. To prevent the serious damage
occurrence mentioned above, in the stage of horizontal
crack or segregation, damage should be detected.
In present damage detection via GPR system,
inspectors are just visually checking the image ofreflected wave signal from slabs. However, the signal
change at damage area are really slight because thewavelength of Ultra High Frequency (UHF) radio wave
used in existing GPR system is several hundred times
larger than the vertical scale of the damages. Thus,
accurate damage detection is really difficult and thedetection accuracy highly depends on the inspectors’ability and expertise. In addition, the image-checking byinspectors are really time consuming and requires lots ofeffort. To increase the damage detection accuracy andrealize automatic damage detection to decrease the

Figure 1: Ground Penetrating Radar-Mounted Vehicle

Figure 2: Example of Signal Processing Result
inspection time and the labor cost, the system should be
improved from the both the sides of software andhardware.
To improve the software at first, the purpose of thisresearch is set to develop the signal processing algorithm
to detect damage of slab from radar signals. For
hardware, GPR (Stepped Frequency-Continuous Wave
(SF-CW) type, and 200 MHz-3.02 GHz range) which isalready commercialized and which can realize on-vehicle
measurement are utilized in this research[1], [2].
REFERENCES
Reference to a journal publication:[1] Tsukasa Mizutani, et al., “Bridge Slab Damage
Detection by Signal Processing of UHF-Band Ground
Penetrating Radar Data,” Journal of Disaster Research,
Vol.12 No.3, pp. 415-421, 2017.
[2] Takahiro Yamaguchi, Tsukasa Mizutani, “Sensitive
Damage Detection of Reinforced Concrete Bridge Slabby “Time-Variant Deconvolution” of SHF-Band Radar
Signal,” IEEE Transactions on Geoscience and Remote
Sensing, 2018. (to appear)28

USMCA 2018

SESSION 2
DISASTER MANAGEMENT I

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 84

Vulnerability Assessment of Soft Brick Unreinforced Masonry Walls:
Study of 2001 Gujarat Earthquake
Jayaprakash Vemuri1, Syed Ehteshamuddin2, Kolluru V.L. Subramaniam3*
1,2,3
Indian Institute of Technology Hyderabad

Abstract

Unreinforced soft-brick masonry structures comprise a large portion of buildings in seismic prone
regions of India. Recent earthquakes have extensively damaged such structures. Experimental andnumerical studies on soft brick unreinforced masonry structures are scarce in literature. The 2001 Bhuj
earthquake which struck the Kutch region in the western part of India, was the strongest intraplate
earthquake to have occurred in the past century. The earthquake caused widespread damage tounreinforced brick masonry (URM) structures in the region. Assessing the vulnerability of the nonengineered masonry structures in this region is complicated by the lack of ground motions and realistic
models for cyclic response of masonry. In this study, a suite of strong ground motions for the region is
generated using the modified stochastic finite fault method. Numerical simulation of soft brickunreinforced masonry panels subjected to lateral loads is performed. At the panel level, the masonry
structure is modelled using the micro modelling approach within a finite element framework. Cyclicload analyses are performed on the finite element model to understand the complex hysteretic behaviourof unreinforced soft-brick masonry walls. A hysteretic model was calibrated to experimental data of
unreinforced masonry shear walls. Nonlinear time history analyses are performed on validated modelsof two unreinforced masonry shear walls. The analytical results correlate well with observed damage
to URM structures. Seismic fragility curves indicate high vulnerability of URM structures under the
expected range of seismic intensities for the region.
Numerical Analysis of Soft Brick Masonry Walls
Numerical models are used for a better understanding of the behaviour of masonry walls for scenarios
different from the ones tested in experiments. In this paper, the simplified micro-modelling strategy isadopted, and numerical simulations are performed to assess the lateral load response of masonry walls
made with soft bricks. In this paper, the in-plane behaviour of soft brick URM at the panel level isnumerically investigated using the simplified micro modelling approach. Lourenco and Rots (1997)
developed a multi-surface interface model by including three yield effects: cap model for compressive
failure, tension cut-off for tensile failure and Mohr-Coulomb failure envelope for shear failure. All thebasic types of failure mechanisms associated with masonry, namely diagonal shear failure, bed-joint
sliding failure and flexural failure are evaluated. The crack interface reproduces the jump from onehead joint into the other, implying that all inelastic phenomena occur in the interface elements resulting
in a robust type of modelling. In micro-modelling, zero thickness interface is adopted, and the size ofthe unit is expanded by half mortar thickness in both directions. Numerical analysis was performed
using FEM platform DIANA®, to obtain the monotonic load-deformation response of the masonryunder a constant applied compression. Brick and mortar properties of the wall were obtained fromexperiments carried out brick and mortar prisms by Ravula and Subramaniam (2017). The shear andtension parameters of the joint interface were taken the same for the three aspect ratios to observe theinfluence of brick and mortar strengths. For cracks, the tensile strength, 𝑓𝑓𝑡𝑡 was taken as 1/10th of brickstrength, and high stiffnesses (𝑘𝑘𝑛𝑛 , 𝑘𝑘𝑡𝑡 ) were considered as suggested by Laurenco and Rots (1997). For
joints, the normal stiffness, 𝑘𝑘𝑛𝑛 and the tangential stiffness, 𝑘𝑘𝑡𝑡 , were calculated using Equation (7) and(8). The values of cohesion, 𝑐𝑐, friction angle, µ and cap compressive strength were taken from Ravula
and Subramaniam (2017). Diagonal cracking marks the ultimate or peak load carrying capacity of thewall (marked in Figure 1). The cyclic load response of wall obtained from the numerical analysis issown in Figure 1. The non-linear analysis was carried out in two stages. In the first stage, axial stress
was applied to its full value, and in the second stage, cyclic displacements of 6 cycles was applied.
Corresponding Author: Professor, Department of Civil Engineering, I.I.T. Hyderabad, Kandi, Sangareddy,
Hyderabad, Telangana 502285, INDIA. Email: KVLS@iith.ac.in*29

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 84
3Displacement(mm)2

Onset of Diagonal
Cracking 1.4 mm

0

-1 0

1

-2

2

3

4

5

6

7

Number of Cycles-3

Load (kN)

1

30

Pivot Point

20
10

-3

-2.5

-2

-1.5

-1

-0.5

0

Displacement (mm)
0

0.5

1

1.5

2

2.5

3

Onset of Flexural
Tension Cracking

-10
-20

Initiation of Diagonal Shear Cracking throughhead joint at 2.2 mm displacement

Cracking State at ultimate displacement of 5.5 mm-30
Onset of Diagonal Cracking at -1.45 mm

Pivot Point-40

Figure 1: Stages of Shear Diagonal Stepped Cracking for Shear Load Response; Cyclic load response

Ground Motions andStrong motion records from the 2001 Bhuj earthquake are not available. In such regions where arich database of historical strong motions is unavailable, modified records may be obtained either bygenerating artificial records or by altering natural records. Both physical and numerical models areavailable to generate synthetic records, which have a natural appearance and strong motion duration
similar to that of a real record. In this study, the modified stochastic ﬁnite fault method is used togenerate synthetic ground motions. Beresenev and Atkinson (1997) extended the stochastic point source
model to large faults by dividing entire fault into smaller sub-faults and considering each sub-fault as apoint source. Table 1 shows the characteristics of the synthetic ground motions generated for various
towns in Gujarat. These towns are situated across various seismic zones as per the seismic zonation
map of India (IS1893:2016). The simulations were conducted at hard rock sites with shear wave velocity
of 2900 m/s. The simulations were also carried out at generic rock using crustal ampliﬁcation factors
estimated for eastern North America at the NEHRP B/C boundary (Vs = 760 m/s). The values at Anjar,
Naliya, Junagarh, Ahmedabad, and Anand are comparable at the NEHRP B/C conditions (Vs 760m/s).
The values at Khambaliya, Jamjodhpur, and Amreli compare well with PGAs estimated at these sites
for hard rock conditions. These sites are hard rock sites situated on Deccan basalt. The epicentral
distance of the station, the peak ground acceleration (PGA), are tabulated.
Table 1 Comparison of PGA values – Present Study and Recorded

S.
No.

Site

Site
Class
(NEHRP)

Epicentral
Distance(km)

Recorded
PGA (g)Recorded PGA(g)
Vs 760 m/s(Corrected to
B/C)

1
2
3
4
5
6
7
8
9
10
11
12
13

Anjar
KandlaNirunaNaliyaKhambaliya
Jamjodhpur
DwarkaPorbandar
Junagarh
Amreli
Ahmedabad
Cambay
Anand

C
C
D
C
A
A
D
D
A
A
D
D
D

44
53
97
147
150
166
188
206
216
225
238
266
288

0.65
0.35
0.32
0.29
0.072
0.088
0.085
0.076
0.075
0.039
0.11
0.20
0.058

0.580
0.326
0.241
0.215
0.143
0.088
0.061
0.054
0.075
0.039
0.080
0.143
0.041

30

PGA (g) of
SimulatedGM
Vs 760 m/s
B/C(NEHRP)
0.564
0.446
0.360
0.222
0.192
0.128
0.199
0.143
0.084
0.080
0.080
0.062
0.053

PGA(g) of
SimulatedGM
Vs 2900m/s
(Hard
Rock)
0.315
0.241
0.208
0.123
0.104
0.073
0.107
0.076
0.049
0.045
0.046
0.038
0.032

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 84

In Figure 2 the PGA and the PGV are correlated with drift displacements of the walls. The limit
states of cracking, ultimate and collapse are marked for reference. It is observed that ground motions
with high PGA levels (>0.1g) excited the walls to the post peak regime causing collapse. This
corresponds well with actual damage to masonry structures as observed in reconnaissance surveys(Jagadish et al., 2001).

8

8

7

7
Collapse

Drift (mm)5Cracking

4

Ultimate

36
Drift (mm)

6

4
3

2

2

1

1

0

0

0.2

0.4
PGA (g)0.6

0.8

Collapse
Cracking
Ultimate

5

0

0

0.2

0.4
0.6
PGV (m/s)

0.8

1

Figure 2. (a) Drift versus PGA (b) Drift versus PGVReferences

Vemuri, J., Ehteshamuddin, S., & Kolluru, S. V. (2018). Evaluation of seismic displacement demand for
unreinforced masonry shear walls. Cogent Engineering, 1480189.
Ravula, M.B. and Subramaniam, K. (2017) Experimental investigation of compressive failure in masonry brickassemblages made with soft brick. Materials and Structures, 50:19.

Lourenco PB, Rots JG (1997) Multi-surface interface model for analysis of masonry structures. Journal ofEngineering Mechanics,123(7), 660–8.
Shing P, Cao L (1997) Analysis of partially grouted masonry shear walls. US Department of Commerce,
Gaithenburg, MD20899, NIST GCR, 97-710
Oliveira D, Lourenco P. (2004) Implementation and validation of a constitutive model for the cyclic behaviourof interface elements. Computers and Structures, 82(17), 1451–61.
TNO DIANA BV. (2011). Diana user manual. Release 9.4.4, Delft, Netherlands
Boore D, (1983) Stochastic simulation of high-frequency ground motions based on seismological models of theradiated spectra, Bulletin of Seismological Society of America, 1983, 73(6): 1865–1894.
Anderson J and Hough S, (1984) A model for the shape of the Fourier amplitude spectrum of acceleration at highfrequencies, Bulletin of Seismological Society of America, 1984, 74(5): 1969–1993.
Beresnev IA, and Atkinson, GM, (1997) Modeling ﬁnite fault radiation from the 𝑤𝑤𝑤𝑤 spectrum, Bulletin of
Seismological Society of America, 1997, 87(1): 67–84.
Narayan JP and Sharma ML (2004) Effect of Local Geology on Damage Severity during Bhuj, India earthquake,
Proceedings of the Thirteenth World Conference on Earthquake Engineering, 2004, Paper No.2042, August 1-4,
Vancouver, Canada

Jagadish, K., (2003). Behaviour of masonry structures during the Bhuj earthquake of January 2001, Journal of
Earth System Science, 112 (3), 431-440

31

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 01

THE WAY OF LEADERSHIP AT CRSIS MANAGEMENTTETSURO ITO
Visiting Professor, University of Tokyo, Tokyo, Japan t-g-ito@iis.u-tokyo.ac.jp
Keywords: Way of Leadership, Crisis Management, Accountability
1, IMPORTANCE OF CRISIS MAMAGEMENT
It is important for a leader to know what he should
perform based on the occasion of the crisis. The
following crisis management actions are basic at the timeof crisis.
1) Grasping of the situation by information collection
When a crisis occurs, it becomes important how youcollect necessary information quickly and precisely.
2) Predicting the development of the situation withlimited information.
While there is limited information it is necessary toguess what is taking place and to predict how thesituation will develop.
3) Quick response
It is vital to build a system to take action quickly anddecide a policy to cope with a crisis.
4) Decision making
It is important to decide what kind of policy andsystem is to be taken to cope with a crisis quickly.
5) Operation
It is needed to build up the system and handle theoperation to cope with a crisis appropriately.
6) The crisis communication
Emergency outbreak increases the importance ofcommunication among people compared to the normaltime.

2. ACCOUNTABILITY OF LEADER
It is important for a leader to explain by himself on theoccasion of the outbreak of the crisis what kind of crisis
is taking place, what the coping policy is and how he or
she is going to deal with the situation. It is important thata leader shows readiness and posture that he will be
responsible for the actions taken during the crisis
management.
When a crisis takes place, the trust for a leader isimportant to people above all since there is no choice forthem unless they trust the decision of the coping policy
and method of their leader. It is also important that aleader shows the leadership, gains trust from the people,
and to give people relief. And these attitude encourages
the subordinate. The leader should speak his or her
thought resoluteｌｙ and must act to show strong
determination to deal with a situation by his or her own
responsibility, and gain trust from the people.

3, THE WAY OF LEADER
The judgement of the situation by the leader at the timeof the crisis outbreak and the decision of the coping
policy are naturally accompanied by the responsibility.
It is the worst to put off the decision because he or she isafraid of making an error. Leader must have thereadiness to take responsibility for the result and thecourage to make decision quickly and to carry out thecountermeasures which leader regards as the best
measures．
The leader who watches the situation, does not dare tojudge the situation, dodge one's responsibility, and notcope with the crisis should be said that he or she is theleast desirable leader at the time of the emergency. And
it may be said the true value of the leader appears in thecase of a crisis. Therefore, it is necessary for the leader todevelop mental attitude preparing for a crisis all the time.

2. THE LEADERSHIPThe role of leader at the time when emergency
situation occurs is important. Important thing for leader
is to judge the situation and to decide what to do. In caseof emergency, it sometimes happen that information
about the situation is limited, it is required that leader
makes quick judgement and decides the countermeasures
to deal with the emergency.
It is dangerous for a leader to watch the situation and not
to make any decision during the emergency. A delay of
the first action due to leader’s decision to wait until thesituation is fully understood can produce irreparable
situation. Quick judgment of the situation anddetermination of countermeasures for a crisis is ability
which is needed for a leader.

32

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 68

DEVELOPMENT OF DISASTER PROCESS MANAGEMENT SYSTEMMUNEYOSHI NUMADA1 and KIMIRO MEGURO2
1
2

Associate Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, numa@iis.u-tokyo.ac.jp
Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, meguro@iis.u-tokyo.ac.jp

Keywords: PGA, BOSS, Disaster Process, Information Management
1. INTRODUCTION
This research is to define the response process andoptimization of workload needed for disaster response inlocal government level. The focus of the research is tosimulate the available and necessary responses based on
the disaster occurrence situation based on the location of
hazard attack, social conditions etc. A developed systemcalled BOSS (Bosai or Business Operation Support
System) is to support a disaster process management fora disaster situation. 48 kinds of works and about 500
processes are defined to analyze disaster responses inBOSS.

for the verification and update PDCA cycle for the
response processes.

2. METHOD
To show how the response system works, after thelocation of a disaster has been identified, social data, thedamage estimation and the necessary responses aredescribed. The PGA (Peak Ground Acceleration)
distribution according to the monitored data for anearthquake disaster and the floods distribution for a
meteorological disaster are used to calculate the damage
situation, and then the volume of response workload isevaluated based on the damage level. USGS (U.S.
Geological Survey) feeds the API (Application
Programming Interface) of earthquakes monitoring data
as real-time Geo-JSON style (Figure 1). BOSS connects
to the real time API of earthquake occurrences by USGS.
Big process manages the detail process in BOSS (Figure2). Detail explanation about the process is shown tounderstand the contents of the process. Some necessary
documents are linked to the detail processes. BOSS is
used in the Kumamoto prefecture in Japan whereexperienced for the 2016 Kumamoto earthquake disasterFigure 1: Real-time PGA distribution and affected
population map
3. CONCLUSIONSThe basic disaster response processes are defined
based on the analysis of past disaster responses in local
governments. Then developed system BOSS is
implicated in the local government to support the initial
responses.
The training system is needed to educate thestakeholders to understand effective disaster responses
by BOSS. This research also developed the disastermanagement training program by Disaster Management
Training Center in the University of Tokyo (DMTC) to
provide the professional disaster related knowledge andskills.

Big process

Detail process

Documents
Detail explanation(Plan, Manual, Law, Form)
Figure 2: Organization of the data transfer in BOSS

33

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 68

34

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 65

TOWARDS A DISASTER RESILIENT SOCIETY USING REMOTE SENSING TECHNOLOGY
H. GOKON1, Y. KATAIE2, M. KUWA3, S. KONDO4 and K. MEGURO5
1

Assistant Professor, ICUS, IIS, UTokyo, Tokyo, Japan, gokon@iis.u-tokyo.ac.jp (corresponding author)
Visiting Associate Professor, Wakayama University, Wakayama, Japan, kataie_y0001@pref.wakayama.lg.jp
3
Visiting Associate Professor, Wakayama University, Wakayama, Japan, kuwa_m0001@pref.wakayama.lg.jp
4
Associate Professor The School of Regional Design, Utsunomiya University, Japan, kondos@cc.utsunomiya-u.ac.jp
5Professor, ICUS, IIS, UTokyo, Tokyo, Japan, meguro@iis.u-tokyo.ac.jp
2

Keywords: Tsunami, Remote sensing, Disaster management
1. Introduction
Tsunami causes heavy and extensive damages along
coastal regions. In case of the 2011 Tohoku earthquake
and tsunami disaster, 561 km2 was inundated with the
maximum run up height of 40.5 meters. 127,829
buildings were collapsed by the tsunami. 15,894 people
were killed and 2,562 were still missing as of 10
February 2016. Under this situation, we might face thedifficulties to understand comprehensive impacts caused
by a tsunami disaster due to break downs ofcommunication network and interceptions of emergent
routes. This will lead to delays of decision makings thatare related to disaster response. Therefore, the decision
maker need to comprehend the impacts as soon as
possible. Remote sensing technology is an only solution
for this problem. Satellite / airborne remote sensing
technology enables us to identify the extensive impacts
within a short time without visiting the affected areas.
Especially, synthetic aperture radar (SAR) is very useful
because of the wide availability that works under all
weather conditions in day and night time.
Opportunities to use remote sensing technologies for adisaster response in Japan have been increased. However,recent advanced technologies are not fully utilized forthe response activities done by local governments. Oneof the possible reason is that effects for mitigating thework loads and damage assessment time have not been
evaluated quantitatively. Therefore, this study aims atevaluating the effects in case of a local government
affected by the 2011 Tohoku earthquake and tsunami.

!,-%&'()*+$+!"#$%&'()*+$+'./*01
2
!

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$%

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Figure 1: Pre- and post-event TerraSAR-X data

Figure 2: Damage function

2. Method
This study is divided into two parts; (1) A development
of damage estimation methods with remote sensing
technology for discussing limitations and capabilities indisaster response, (2) Evaluating the effects of themethod for reducing the work loads and saving time.

Figure2). The number of washed-away buildings were
estimated by multiplying by the pre-event number ofbuildings in local scale (Figure 3). Finally, the results
were assessed by comparing with truth data showing thepearson’s correlation coefficients of 0.98 – 0.99 in caseof using X-band SAR data, and 0.87 – 0.98 in case ofusing L-band SAR data (Figure 4).

2.1 A review of damage estimation methods
Gokon et al.(2016, 2017) developed methods for
estimating building damages in tsunami affected areasusing X-band SAR satellite data and L-band SAR
satellite data.
Based on a change detection technique using pre- andpost-event SAR data, damage ratios of washed-awaybuildings were estimated using damage function
developed by Gokon et al.(2016, 2017) (Figure 1,

2.2 Effects of reducing work loads and saving time
To evaluate the effects of remote sensing in reducing
the work loads and shortening time of disaster response,
Ishinomaki City, which was devastated by the 2011
Tohoku earthquake and tsunami, was selected as thestudy area. Building damages caused by the tsunami,schedules of building damage survey for victim’s
certificate and number of persons who assigned for thesurvey were investigated.

35

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 65

Estimation (remote sensing)

Figure 3: Damage ratios of washed-away buildings.
is a possibility to contribute to the first survey. Image
500
processing time for estimating the damage in coastal
regions of Miyagi prefecture can be finished within one
400
day by one person. The observation time of TerraSAR-X
satellite imagery was 13 March 2011(JST). So, if we
300
could finish the image processing within one day, we
might have been able to finish the identification of200
collapsed areas by 14 March 2011. In that case, decision
making for the second and third surveys might be shorten
100
for 2 weeks. Furthermore, 4 persons * 3 days = 12
(persons*day) might be saved. As the result of this0
discussion, we found the possibility to reduce the time
0
100
200
300
400
500
for decision making for building damage survey andTruthvictim’s certificate, and saving the limited resources
Figure 4: Accuracy assessment of damage estimation.
soon after the tsunami disaster.
Next, reducing work loads and saving time are
estimated by comparing the historical data in Ishinomaki
City, time for damage estimation using remote sensing
technology and performance of the damage estimation.

3. CONCLUSIONS
Effectiveness of remote sensing technologies fordisaster response was evaluated in case of the 2011
Tohoku earthquake and tsunami. As a remote sensing
technology using SAR data is utilized for building
damage survey for victim’s certificate, 14 days might beshortened, and 12 persons*day might be saved in humanresources.

2. Results and discussion
The results of the investigation in Ishinomaki City is
specified as follow.
Building damage in Ishinomaki City was 44,076(Collapsed : 14,263, Major damage : 9,465, Partial
damage : 2,356, Slight damage : 17,992). Building
damage surveys were performed totally three times.
First survey was conducted from 25th to 27th in March2011 to identify the collapsed areas by 2 groups
including 2 persons for each, that is 4 persons / day. The
second survey was performed from 4th April 2011 to 4th
May 2011. This time, 10 groups with 3 persons for each,that is 30 persons / day, investigated building damage
based on interpretations from outside and an inundation
depth at the location of the building. The third survey
was conducted from 20th May 2011 to 31st May 2011 by
10 groups with 3 persons for each. Not only from outsideof the building, but also inside was investigated this time.
The proposed remote sensing method can identify thedevastated areas with high performance. Therefore, there

REFERENCES[1] H. Gokon, S. Koshimura and K. Meguro, Verificationof a method for estimating building damage in extensive
tsunami affected areas using L-band SAR data, Journalof Disaster Research (JDR), Vol.12, No.2, 2017[2] H. Gokon, S. Koshimura and M. Matsuoka, Objectbased method for estimating tsunami-induced damage
using TerraSAR-X data, Journal of Disaster Research,
vol.11 (2016), No.2, pp.225 - pp.235

36

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 22

GENERATION OF GROUND MOTION PREDICTION EQUATION FOR IRAN
Chenna RAJARAM1, Ramancharla PRADEEP KUMAR2
1

Assistant Professor of Civil Engineering, Rajeev Gandhi Memorial College of Engineering & Technology, Nandyal,
INDIA, drchenna78@gmail.com
2
Professor of Civil Engineering, International Institute of Information Technology - Hyderabad, Gachibowli,
Hyderabad, INDIA ramancharla@iiit.ac.in
Keywords: Ground Motion Prediction Equation, Ground Acceleration, Hazard, Earthquake
ground motion values. The energy of seismic waves gets
attenuated as waves travel away from the source. The
amplitudes of body waves decrease proportionally to thereciprocal of distance and surface wave amplitudes
decrease proportionally to the reciprocal of square rootof distance. And seismic energy is proportional to thesquare of wave amplitudes. The general functional formof GMPE is expressed as follows:(1)f (Y )  a  f1 (M )  f 2 ( R)  f3 (S )  f 4 (F)  
Where Y is the ground motion parameter to bepredicted, e.g. peak ground acceleration, peak ground
velocity etc. f1(M) is a function of magnitude, f2(R) is afunction of epicentral distance, f3(S) is a function ofsite categories like rock and soil sites, f4(F) is a functionof type of fault, and σ is a value of relating uncertainties
in the predicted f(Y). It is necessary to consider thevariable separation in the relationship. First, it isreasonable to assume that function f1 depends only on M.
In this model, the seismic variables are considered
independently; no coupled terms of these variables aretaken into account. The forms of f(Y) and f1(M) areselected as:f (Y )  log10 (Y ); f1 (M)  bM
(2)
To investigate the attenuation resulting from geometricspreading and material anelasticity and scattering effect,
f2(R) can be expressed as,(3)
f 2 ( R)  c log10 ( R 2  h 2 ) dRABSTRACT
For the assessment of risk of any area threecomponents are necessary viz., Hazard, Exposure andVulnerability. While most of the times Exposure andVulnerability are easy to obtain compared to Hazard. The
selection of Ground Motion Prediction Equations(GMPE) is a fundamental component of any seismic
hazard analysis. Current research is focused on catalogueof the earthquakes occurred in Iran from 1974 to 2017,
which is taken from Building & Housing ResearchCenter (BHRC), Iran. The catalogue consists of 13
strong to major earthquakes (6.0 > Mw > 7.8) and 660
seismic stations in Iran. The catalogue consists of 13
strong to major earthquakes (6.0 > Mw > 7.8) and 660
seismic stations in Iran. The GMPE at bedrock level iscalculated
aslog10 (Y )  3.731  0.238M  2.776 log10 R 2  h 2  0.289 S  0.48 F  

1. INTRODUCTION
Geophysical parameters play a vital role in generating
synthetic accelerograms. Estimation of these parametersneeds huge earthquake catalogue and ground motion data.
Over estimation or under estimation of these parameters
lead unrealistic ground motion records, which cause
effect to the structure. In this study, Ground Motion
Prediction Equation (GMPE) is derived for Iran. GMPE
equations are frequently used for engineering purposes toestimate peak ground acceleration (PGA). This PGA
helps to estimate amount of seismic force acting onto thestructure. Numerous studies have been done worldwide
on GMPE to estimate seismic hazard. Literaturesuggested few GMPE equations can be used for Iranianregion [1]-[5]. The present study attempts to propose
GMPE exclusively for Iranian region with Iranianseismic catalogue.


geometrical spreadinganelastic attenuation

It is in general inappropriate to assume that thefunction f2 depends only on R. The parameter h is calledfictitious depth and is determined by regression andincorporates all of the factors that tend to limit motions
near the source. The parameter h is introduced to allow
for the fact that the source of the peak motion values may
not be the closest point on the rupture. If the source ofthe peak motion were directly below the nearest point on
the surface projection of the rupture, the value of hwould simply represent the depth of that source.
Theoretical study showed that the seismic wave
amplitudes decrease approximately as 1/R at far
distances and converge to a finite value as distance goesto zero. This is due to one of the effects from the nearfield term of the seismic radiations, and it is noted that
this holds true even when the distance is zero, that iswhen station is located on the fault plane. Thus, it ismore appropriate and natural to introduce the formf2~(R+h)-1 of (R2+h2)-0.5 than to keep 1/R. One important
point in this form is that the variable h depends on themagnitude M, since the near field territory depends on

2. GROUND MOTION PREDICTION EQUATIONThe GMPE relationships are commonly represented as
ground motion parameters in a function form. They
depend on the magnitude of the earthquake, distancefrom source to site, type of fault, soil conditions etc. So,
these seismological parameters should be chosencarefully for a region. Peak ground motion values areapproximately log-normally distributed. As a result,regression is usually used on the logarithm of predictive
term than the term itself. Earthquake magnitude istypically defined as the logarithm of some peak motion
parameters.
Consequently,
themagnitudeisapproximately proportional to the logarithm of peak37

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 22
the fault size of the earthquake, and on M. The variable h
is a function of M, and therefore, the function f2 depends
on M as well as on R.
The function f3(S), is not free from the non-linear
response of the ground when the ground surface at thestation is covered with soft soil, which means that thefunction depends both on the site categories S and on theamplitude that comes into the surface layers, whichintern depends on M and R. The function form for f3(S),relating to the site categories, can be taken as,(4)
f 3 ( S )  eS
Where e is the co.efficient for regression and S
represent the site categories, 1 for soil site and 0 for rocksite. The final functional form for modeling the groundmotion attenuation can be represented as follows:
log10 (Y )  a  bM  c log10 R 2  h 2  dF  eS   (5)Where σ is the standard deviation of the logarithm ofY, M is the magnitude, R is the epicentral distance.

epicentral distance. In this analysis, the term h is taken as
16.38, 29.42, 40.84 and 49.0 for magnitudes M6.0, M6.7,
M7.4 and M7.8 respectively. The dataset consists of two
orthogonal horizontal components of PGA values, themaximum value has been chosen for the purpose ofanalysis.
103
Soil-Strike Slip
Rock-Strike Slip

2

10

101

6

6.5

7

7.5

8

Magnitude (Mw)

Figure 2. The distribution of PGA with magnitude
10 3
Soil-Dip Slip
Rock-Dip Slip

10 2

3. GMPE ANALYSIS
The dataset consists of 660 seismic station records in
the Iran for studying the GMPE relationship. The Iranianearthquake information and ground motion records aretaken from BHRC (https://ismn.bhrc.ac.ir/en dated: 20
August 2018). The seismic stations are located on both
soft and rock sites, hence the term f3 (S) is taken as zero.
Current study considers shear wave velocities ranges 180
m/s to 1170 m/s. Based on Iranian code of practice forseismic resistant design of buildings (2005), shear wave
velocities are considered for Vs more than 375 m/s asrock type and less than 375 m/s as soil type. The analysis
also considers type of fault namely strike-slip fault anddip-slip fault. The term S represent the site categories, 1
for soil site and 0 for rock site. The term F represents, 1
for dip-slip fault and 0 for strike-slip fault. The
distribution of dataset used in this analysis is from theearthquakes with a magnitude range of 6-7.8 and an
epicentral distance range of 10-300 km. The distributionof seismic magnitude data with respect to hypocentral
distance is shown in figure 1.

10 1

101

102

Hypocentral Distance (km)Figure 3. The distribution of PGA with hypo-central
distance
The co.efficient c in equation 5, which is a negativevalue, means the attenuation rate with respect toepicentral distance for a fixed M [6]-[9]. In other words,
it is a weighted average of c’s, each of which is obtained
from a data set of one earthquake at all epicentral
distances. The slope c must not be calculated for thedataset of all earthquakes. The co.efficient c must be
greater than 1.0 for the short period amplitudeattenuation relation, since this term includes thegeometrical spreading of body wave and inelastic
attenuation. Hence, the analysis considered the weighted
average of c’s for a fixed at all epicentral distances.
Similarly, the co.efficient b means the amplitude increase
rate with respect to magnitude at a fixed distance. In
other words, it is a weighted average of b’s, each ofwhich is obtained from a dataset at a particular distance
range for all earthquakes. In this analysis, the weighted
average of b and c are taken at all epicentral distances
and at all earthquakes, respectively.
The residual values represent the deviations of thepredicted values from the observed values. It can be
defined as,
YResidual  log10  observed Y predicted (6)

Where Yobserved is the observed value from groundmotion record (e.g. PGA), while Ypredicted represents thevalue predicted by the GMPE. The residual can describe
the extent to which the predicted values are consistent
with the recorded values. The regression co.efficients arecalculated using regression analysis. The GMPE
obtained for Iranian region from the analysis is shown
below.

Figure 1. The distribution of data with magnitude tohypo-central distance
Figure 2-3 shows the distribution of PGA with respect
to epicentral distance, magnitude and logarithm of38

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 22
faults, Ph.D Dissertation, International Institute ofInformation Technology, Hyderabad, India, 2016.

log10 (Y )  3.731  0.238M  2.776 log10 R 2  h 2  0.289 S  0.48 F  (7)
4. CONCLUSIONS
A study has been conducted to derive GMPE for Iranregion. For this purpose, ground motion dataset is takenfrom BHRC from 1974 to 2017. The proposed GMPE
for Iran region yields good results. Though, there is adifference between PGAs due to insufficient database in
the region, the PGA value gives satisfactory result. The
proposed GMPE equation for Iranian region is as follows
log10 (Y )  3.731  0.238M  2.776 log10 R 2  h 2  0.289 S  0.48 F  

REFERENCES[1] R. R. Youngs, S. M. Day, and J. L. Stevens, Near
field ground motions on rock for large subduction
earthquakes,
ProceedingsofEarthquake
Engineering & Soil Dynamics II. Geotechnical
Division, ASCE, 1988, pp. 445-462. USA.
[2] C. B. Crouse, Ground-motion attenuation equations
for earthquakes on the Cascadia subduction zones,
Earthquake Spectra, vol. 7, No.2, 1991, pp. 201-236.
[3] N. P. Theodulidis, and B. C. Papazachos,
Dependence of strong ground motion on magnitudedistance, site geology and macroseismic intensity forshallow earthquakes in Greece: I, peak horizontal
acceleration, velocity and displacement, Soil
Dynamics and Earthquake Engineering, vol. 11,
1992, pp. 387-402.
[4] G. M. Atkinson, and W. Silva, An empirical study ofearthquake
sourcespectrafor
California
earthquakes, Bulletin of the Seismological Society ofAmerica, vol. 87, No. 1, 1997, pp. 97-113.
[5] W. B. Joyner, and D. M. Boore, Peak horizontal
acceleration and velocity from strong motion records
including records from the 1979 Imperial Valley,
California earthquake, Bulletin of the SeismologicalSociety of America, vol. 71, No. 6, 1981, pp. 20112038.
[6] Y. Fukushima, and T, Tanaka, A new attenuation
relation for peak horizontal acceleration of strong
earthquake ground motion in Japan, Bulletin of the
Seismological Society of America, vol. 80, No. 4,
1990, pp. 757-783.
[7] T. Masuda, and M. Ohtake, Comment on A new
attenuation relation for peak horizontal accelerationof strong earthquake ground motion in Japan by Y.
Fukushima and T. Tanaka, Bulletin of the
Seismological Society of America, vol. 82, No. 1,
1992, pp. 521-522.
[8] J. G. Anderson, and S. E. Hough, A model for the
shape of the Fourier amplitude spectrum of
acceleration at high frequencies, Bulletin of the
Seismological Society of America, vol. 74, No. 5,
1984, pp. 1969-1993.
[9] C. Rajaram, Numerical modeling of near-fault
seismic ground motions for strike-slip and dip-slip

39

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 41

A STUDY OF SURFACE DEFORMATION IN PIPALKOTI, INDIA
V.MAURYA1, D. MEGHANADH2, A. TIWARI3, A. B. NARAYAN3, R. DWIVEDI4, T. R. MARTHA5
1

Junior Research Fellow, GIS Cell, MNNIT Allahabad, vipinmaurya2010@gmail.com
Research Scholar, GIS Cell, MNNIT Allahabad rgi1703@mnnit.ac.in(corresponding author)
3
Research Scholar, Department of Civil Engineering, IIT Kanpur atiwari@iitk.ac.in
3
Research Scholar, Department of Civil Engineering, IIT Kanpur avadhbn@iitk.ac.in
4
Assistant Professor, GIS Cell, MNNIT, Allahabad ramjid@mnnit.ac.in
5
Scientist SF, NRSC, ISRO, Govt. Of India, tapas_martha@nrsc.gov.in
2

Keywords: Surface deformation analysis, InSAR, StaMPS, Landslide

ABSTRACT
Frequency of disasters such as landslides has increased in the last few decades in India. Loss of property and human
lives due to disasters are irreparable. The well-known disaster, Kedarnath landslide (2013) in Uttarkhand, had alone
swallowed more than 5000 lives and affected 4200 villages. Such events require the necessity of research in the field of
surface deformation analysis of landslide in order to reduce risk and prepare early rescue methods. This study presents asurface deformation analysis of Pipalkoti, a landslide prone area in Uttarakhand, using multi-temporal Synthetic
Aperture Radar Interferometry (MT-InSAR) technique.
The study uses temporal data of the European Environmental Satellite (ENVISAT) and 11 interferometric single lookcomplex SAR images from ENVISAT covering a period of 12 months has been used for analyzing surface
displacement. The computations of surface movement along with its rate (in mm/yr) were performed by using StaMPS(Stanford Method for Persistent Scatterers) algorithm, which detects phase stable pixels called Persistent scatterers (PS)pixels to calculate time-series displacement. The analysis results indicate the intensity of land mass movement, which
would be helpful in mitigating the risk associated.
INTRODUCTION
Landslide, a geomorphic phenomenon, is a type of
landmass movement under the influence of gravity.
Movement landmass or debris flow triggered byunstable slopes, seismic or volcanic activity resulting
into a landslide, are always serious concern regarding
safety of people living in mountain regions.
Techniques being used for surface deformation study
are global positioning system (GPS), total station (TS),terrestrial laser scanner (TLS), geotechnicalinvestigation and satellite imaging. These above
techniques except satellite imaging require minimum apersonnel at the study area to collect data of interest
i.e. limited regarding data collection only at accessible
locations. On the other hand, advantage with satellite
imaging is wider coverage and any time data
availability.
In active satellite imaging, Synthetic Aperture Radar(SAR) is the most frequently used method for
deformation analysis. SAR has the advantage of
having sufficient number of satellites providing data in
different frequency bands with high resolution,
independency on weather conditions, data capturing indifferent modes of whole day and night with wide
coverage. In SAR images product, acquired after signal
processing of the received echoes of the transmitted
electromagnetic chrip-pulses, we have used

Interferometric Wide (IW) Swath single look complex(SLC) images of Environmental satellite (Envisat).
Pixels of SLC images hold magnitude and phasevalues where magnitude represents backscattering of
signal scattering property of the target in pixel andproportionally brightness in the image, and phase helps
in retrieval of change in location of the pixels on the
ground [1]. Interferometric SAR (InSAR) is aneffective technique used in deformation study which
utilizes interferometric phase i.e. difference of phasesof two SAR images. As an extension of InSAR,
researchers proposed Differential-InSAR (D-InSAR)
technique by subtracting DEM and interferometricphase which helps out in calculation of phasecomponent due to displacement in the image. But incase of decorrelation of signals, this technique gives nomeasurement. To surmount this issue, [2-3] presented
the concept of permanent scatterer on the basis ofamplitude dispersion index. This technique finds itself
bounded for urban areas only, as man-made structures
have strong backscattering coefficient and thistechnique is not suitable for non-urban areas andrequires knowledge of temporal variation in the
deformation rate [4-5]. To overcome this problem, a
new method was proposed of stable pixel (persistent
scatterer (PS)) selection on the basis of phase stability

4017th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 41
known as PS-InSAR and formulated as Stanford
Method of PS (StaMPS) [5].
In recent years, multi-temporal Synthetic Aperture
Radar Interferometry (MT-InSAR) has emerged as animportant tool which uses temporal SAR data for
estimating the time series displacement of radartargets. MT-InSAR processing can be performed in
two ways: PS-InSAR and SBAS (Small baseline
subset). This study presents a surface deformation
analysis of Pipalkoti, Uttarakhand using MT-InSAR
technique based on PS-InSAR and processed by
StaMPS.

and rest are taken as slave. Then for every master-slavepair, interferograms are generated. Correlation can begiven as follows:total  t * s * d * n(1)

 Bperp  
 T   F 
.  1  f  c  .  1  f  DCc  .thermalB Tc   FDC  perp  1  f Where t is temporal correlation, s is the spatial
correlation, d is correlation in Doppler frequency,and n is correlation related to noise and T represents

STUDY AREA

temporal baseline, c used for critical, Bperp denotes

Uttarakhand state contains high elevated mountains
and peaks and because of being hilly state and having
unstable elevated slopes, there are a large number oflandslide prone areas. The study area is located at 1.4
km upstream from Pipalkoti on Srinagar-Badrinathroad. Further, there are multiple landslide locations
within 50 km upstream Pipalkoti. The study area isshown in figure1. The dataset-details used for the
analysis is given in Table1. The study uses 11 Envisat
SLC images covering a period of 12 months to analyze
surface displacement.

spatial perpendicular baseline, FDC for doppler centroid
baseline and thermal for thermal noise and f ( x ) isexpressed as:
x x  1f ( x)  
1 x  1
Then in phase stability estimation step, initially PS
pixels are selected on the basis of amplitude dispersion
index DA given as
DA 

A
A

(2)

Where  A is standard deviation and  A as mean of
the amplitude values for each pixel in the set of SLC
images. Pixels of high amplitude dispersion index areselected as PS.
In next step, equation(3) is used to estimate phasestability of PS,
Figure1. Google earth view of the study area locatedon Rudraprayag-Badrinath route
METHODOLOGY: StaMPS-based PS-InSAR
StaMPS method was proposed by [5] which
extracts coherent radar tearget based on phase stabilityof pixels and performs better than old method ofpermanent scatterer based on amplitude stability.
StaMPS method works in four steps: Interferogram
generation, phase stability estimation, PS selection anddisplacement estimation.
Firstly, Doris (Delft object oriented radar
interferometric software) is used for interferogram
generation and to remove phase component due totopography and orbital inaccuracies. In this process,first a master image is chosen on basis of minimizing
sum-decorrelation or maximizing the sum-correlation,

x ,i  W{d , x ,i  a , x ,i  S , x ,i   , x ,i  N , x ,i }(3)where  x ,i is the wrapped phase for xth pixelin the interferogram, d , x ,i is the phase change due tothe pixel motion in the direction of flight, a , x ,i is thephase due to atmospheric delay, S , x ,i is the residual
phase due to satellite orbit inaccuracies,  , x ,i is thephase due to look angle error, N , x ,i is the noise termand W is the wrapping operator.
Then, as a measure of phase stability,  x given as

x 

41

1 N
exp( 1( x ,i   x ,i  ˆu ,x ,i )) (4)
N i 1

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 41

Where N denotes number of interferograms,  x ,i is awrapped estimate of the spatially correlated parts of theinterferogram phase, namely the atmospheric error, thesatellite orbital inaccuracy error, and the look angle
error. The term ˆu
 , x ,iis the unwrapped estimate of

the residual topographic phase error.
Based on the chosen threshold value of  x , PS pixels
are selected for processing. In the next step to estimate
displacement, spatially uncorrelated look angle(SULA) error and 3D unwrapping is done. Now,
spatially correlated look angle (SCLA) error isestimated and subtracted to get phase component due
to deformation d , x ,i . Final outcomes of the StaMPS

are adopted for DA and γ, respectively, for the selectionof PS candidates which resulted in ~8000 PS pixels,
forming a dense network of PS pixels. The PS velocity
plot (Figure3) shows displacement of -62 to 84 mm/yr.
Analysing the displacement rate, we can identify
subsidising and uplifting areas and their rate of change
in mm/yr. In study area, subsidence and uplift rate in
Pipalkoti varies from -24 to 8.2 mm/yr. Areas affectedwith high displacement rate are Hailang, Gulabkoti,
Langsi, Dwing and Jalgwar. Figure4 shows GSI(Geological Survey of India) points along with
StaMPS result confirms validity of results.

processing are time-series and velocity maps withannual rate. StaMPS processing is summarized infigure 2.
Interferogramstack
PS candidate
selection by DA

No

Phase noise estimation

Figure 3: 1D LOS deformation map obtained fromPSI processing of the Envisat dataset.

Grad(γ) < Threshold
Yes
Final PS selection
based on phase noise
Removal of spatially
uncorrelated look angle
error
3D Phase unwrapping

Estimate spatiallycorrelated look angle error
PS velocity maps and PS
time series

Figure2: Flowchart of PS-InSAR processing

RESULTS AND DISCUSSION
In this section, the results of StaMPS-based PS-InSARof the 11 ENVISAT ASAR SLC images are discussedwith their interpretations. With 12 SLC images, 11
geocoded single-master interferograms are generated
for the PS-InSAR method. The values of 0.4 and 0.005

Figure 4: 1D LOS deformation map obtained fromPSI processing of the Envisat dataset with GSI points.
CONCLUSION
11 ENVISAT images covering a time period of 12months were used for deformation analysis of thestudy area. Result shows the 1D LOS deformation map
obtained using the StaMPS approach for the Envisat
dataset along with landslide prone locations identified
by GSI. Obtained displacement values show highsubsidence in the region between Pipalkoti and
Hailang along the Rudraprayag-Badrinath route.
ACKNOWLEDGEMENT
Authors are thankful to European Space Agency (ESA)
for providing ENVISAT ASAR images and to ISRO
for providing technical support in data-processing.

42

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 41

REFERENCES[1] A. Tiwari., R. Dwivedi., O. Dikshit., and A. K.
Singh., (2016). “A study on measuring surface
deformation of the L’Aquila region using the StaMPS
technique”. International
Journalof
RemoteSensing, 37(4), 819-830.
[2] A. Ferreti., C. Prati, & F. Rocca., (2000).
“Nonlinear subsidence rate estimation using permanentscatterers in differential SAR interferometry”. IEEE
Transactionson
GeoscienceandRemoteSensing, 38(5), 2202-2212.
[3] A. Ferreti., C. Prati, & F. Rocca., (2001).
“Permanent scatterers in SAR interferometry” . IEEE
Transactions on geoscience and remote sensing, 39(1),8-20.
[4] A. Hooper., H. Zebker., P. Segall., and B. Kampes.,(2004). “A new method for measuring deformation on
volcanoes and other natural terrains using InSAR
persistent
scatterers”. Geophysicalresearchletters, 31(23).
[5] A. Hooper., P. Segall., and H. Zebker., (2007).
“Persistent scatterer InSAR for crustal deformation
analysis, with application to Volcán Alcedo,
Galápagos”. JournalofGeophysicalResearch, 112(B07407), 19[6] R. Dwivedi., P. Varshney., A. Tiwari., A. B.
Narayan., A. K. Singh., O. Dikshit., and K. Pallav.,(2015). “Monitoring of landslides in Nainital,
Uttarakhand, India: Validation of PS-InSAR results”.
In Urban Remote Sensing Event (JURSE), 2015
Joint (pp. 1-4). IEEE.

43

USMCA 2018

SESSION 3
BUILDING SAFETY I

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 06

ANTIINDUCE MEASUREES OF UNDERGROUND SUBWAY STATION
S. KONISHI1, M. HORI2, S. ITO3, and Y. AOKI4
1

Director of Civil Engineering, Structure Maintenance Division, Tokyo Metro Co.,Ltd., Japan, s.konishi.r4r@to

kyometro.jp (corresponding author)
2

Staff, Structure Maintenance Division, Tokyo Metro Co.,Ltd., Japan, m.hori.x4g@tokyometro.jp

3

Vice Director, Structure Maintenance Division, Tokyo Metro Co.,Ltd., Japan, sato.itou@tokyometro.jp

4Manager of Station, Structure Maintenance Division, Tokyo Metro Co.,Ltd., Japan, yo.aoki@tokyometro.jp

Keywords: Anti-induce Measures, Flood, Subway Underground Station, Hinged Door

1. INTRODUCTION
Because of recent extreme weather events, countermeasures for heavy rains are particularly important forsafety of subway. Tokyo Metro Co., Ltd. (hereinafter,
Tokyo Metro) is taking measures against urban flood
disaster assumed by Central Disaster Prevention Council
or each municipality and Large-scale Flood Disasteronce a 1000 year probability for reducing damage fromsubmerged and early recovery (Fig.1) [1], [2].
The report describes Tokyo Metro’s improvement
policy and descriptions of various types of undergroundwaterproofing doors and the performance required ofthem.

3. WATER PROOFING FACILITIES FOR
UNDERGROUND STATION ENTRANCE
Among these, underground station entrances are
expected to suffer the most damage. Most Tokyo Metro
station entrances are situated on sidewalks, there aremany obvious spatial restrictions. In light of these,

2. OUTLINE OF WATER PROOFING FACILITIESWe are developing and installing various
waterproofing facilities at all tunnel entrances (Fig.2),
ventilation openings (Fig.3) and entrances ofunderground stations (Fig.4). Also substation andsignaling machine rooms which are built on ground levelis measures against flooding for early recovery at groundlevel.

Figure 2: Mechanical watertight gates of tunnel entrance
in which doors drop down from above

Figure 1: Conceptual diagram of expected damage in theTokyo Metro Network

Figure 3: Flood preventing machine for ventilation

44

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 06

Petitioner entranceTokyo Metro Ventilation
entrance
tower

OfficeBicycleparking

Above-groundstation

Ventilation
opening

Station office

Entrance totunnelSignal transmission

Connecting
entrance
Stationofficeconcouse

Transformer
room

Equipment Electric
room
room

Water stop point shows
location of flood control
measures
浸水対策の位置を示す

Platform

Figure 4: Tokyo Metro Flood Control Measures

Figure 10

Figure 5: Bi-fold waterdoor
Bi-foldstop
Water
Stop DoorA

Figure 8: Vertical bi-fold doorB

restrictions, conventional waterproofing doors, hinged
doors, cannot be used to improve all entrances. Thus wehave continued to develop counterpressure doors, hinged
double doors, bi-fold watertight doors (Fig.5), shutters(Fig.6), horizontal bi-fold doors (Fig.7) vertical bi-folddoors (Fig.8) and other types of waterproofing doors that
fit to the environments of individual entrances. In
addition, many buildings, which Tokyo Metro tunnels
connect underground, are not prepared for the disasters
flood damage, meaning that Tokyo Metro must takeaction on its own property to prevent flood water
inundation from such buildings. Thus, we havedeveloped counterpressure sliding doors capable ofwithstanding water pressure from flooding up to 15 m
depth.

Figure 12
Waterproof Mechanism

Figure 11
Figure6: Waterproofing shutter
Waterproofing
Shutter

REFERENCES[1] Cabinet Office website: Disaster risk reduction
information website (Expected Flood Damage to
Subways, etc., during an Arakawa River Levee Breach)[2] Tokyo Metropolitan Government website: Tokyo
Disaster Prevention website (Map of expected inundation
zone)

Figure 7: Horizontal bi-fold door

45

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 14

EVALUATION OF RESPONSE REDUCTION FACTOR ‘R’ FOR A 16 STOREY SLENDER
REINFORCED CONCRETE BUILDING USING PERFORMANCE BASED SEISMICENGINEERING.
NIRANJAN GODAGE1, R.PRADEEPKUMAR2,
1
2

M.Tech (CASE), Earthquake Engineering Research Centre-IIIT-Hyderabad,India,niranjangodage@gmail.com
Professor, Earthquake Engineering Research Centre IIIT-Hyderabad,India,,ramancharla@iiit.ac.in

Keywords: Static Non-Linear Pushover Analysis, Response Reduction factor R, reserve strength, ductility,
redundancy
1. ABSTRACT
The current industry followed standards for seismic designin India is based on Linear Static and Dynamic analysis
procedure recommended by IS1893.This procedure
incorporates the non-linear response of a structure using acode prescribed value for R i.e. Response reduction factor,
however in reality these values are difficult to justify for
different structural configurations. Also it is difficult topredict the behavior of critical structural elements oncethe structure goes in to nonlinear zone. The present study
focuses on estimating the actual value of ‘R’. A linear
force based analysis is performed using IS-1893
recommended value of R .The structure is designed using
IS 13920 ductile detailing procedure and remodeled. A
displacement controlled push over analysis is carried out
to determine the performance of the structure in the
nonlinear zone .The actual value of R is then estimatedbased on reserve strength, ductility and redundancy in the
structure.
2. INTRODUCTION
In recent times there has been a significant advancement
in computational capabilities of 3D structural analysis
packages, unleashing its full potential will help us inhaving a better control over the anticipated behavior of thestructure in the nonlinear zone. Also it has been observedin the past earthquakes that well designed and detailed
structures were able to withstand more lateral loads thanthey were designed for. This inherent capacity of astructure to dissipate energy through inelastic behavior
can be attributed to strength, ductility and redundancy inthe structure, which is represented as

Fig.1.Definition of Response Reduction Factor
Response Reduction factor = Maximum elastic force Fel
Design force Fdes
Table 1
R values as per IS 1893 for Dual Structural Systems
1 Ordinary RC Shear walls +RC OMRFs
3
2

Ordinary RC Shear walls +RC SMRFs

4

3

Ductile RC Shear walls + RC OMRFs

4

4

Ductile RC Shear walls +RC SMRFs

5

3. PUSH OVER ANALYSIS
Push over Analysis (POA) is considered as a recent
advancement in earthquake resistant design of structures.
The promise of POA is to produce structures withpredictable seismic performance. The main concept of
POA procedure is based on seismic demand and capacity.
3.1 Demand:
Ground motions during an earthquake produces complex
horizontal displacement patterns in the structures. It isimpractical to trace this lateral displacement at each timestep to determine the structural design parameters andhence the seismic demand is the static equivalentparameter accounting for the dynamic effect on the
structure.

R = RS * RR * Rμ.
This value of R can be obtained from push over curve asshown in Fig.1 where
Strength factor ‘RS’ is the ratio of Design base shear tothat of base shear at yielding.
Ductility factor ‘Rμ ‘is the ratio of roof displacement atyielding to some predefined limits.
Redundancy factor ‘RR’ depends on number of verticalframings participating in the seismic resistance.

46

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 14
Performance evaluation was done using capacity spectrum
curves. Plastic hinge hypothesis was used to capture thenonlinear behavior according to which plastic
deformations are lumped on plastic hinges and rest of thesystem shows linear elastic behavior.

3.2 Capacity
The overall capacity of a structure depends on thestrength and deformation capacity of the individualcomponents of the structure. In order to determine
capacities beyond the elastic limits, some form of
Nonlinear Analysis, such as the pushover procedure isrequired. As the name implies, it is the process ofpushing the structure horizontally with a prescribedloading pattern incrementally until the structure reaches
a limit state (ATC-40 1996) i.e. target displacement.

4.2 Modeling Schema for Linear Analysis
1) Developing a 3D model for the Building in ETABS.
2) Defining all the material properties, frame sections,load cases and mass source.
3) Performing linear static and dynamic analysis using IS
1893 specifications.
4) Designing all structural elements using ductile detailingprinciples.

4. CASE STUDY
In the present case study a G+13 storey signature
structure with a slenderness ratio of around 7 to beconstructed in Deonar, Mumbai (Zone 3) is analyzed.
Linear Static and Dynamic Analysis, displacement
controlled Push over analysis is carried out to determine
the performance in the non linear zone, hinge sequencing
mechanism, base shear, seismic demand and capacity iscompared in both X,Y direction.

4.3 Modeling schema for Nonlinear Analysis.
1) Remodeling the structure in SAP 2000 with detailed
reinforcement using section designer.
2) Assigning auto hinge properties available in SAP 2000
as per ATC-40 to the frame elements which are expected
to yield. For beams assigning default hinge that yields
based on flexure (M3), for the column assigning default
hinge that yields based on the interaction of the axial force
and bending moment (P M2 M3).
3) Application of gravity load followed by static push overload case (which will start from final state of the gravity
pushover).
4) Gravity load case involves loading the structure with
DL+0.25LL, where gravity load application is forced
controlled while that of lateral load is displacement
controlled.
5) Assigning first modal response of the structure as load
pattern for the lateral Push-x and Push-y case.
6) Obtaining Push over curves i.e plot of base shear v/sroof displacement and Performance levels for building
model in X and Y directions.
5. ANALYSIS & RESULTS:
5.1 Linear Analysis
LinearLinear
Bhuj
StaticDynamic
Vx
Vy
EQX 2364.6 THX
507.1 135
EQY 2225.8 THY
146.3 530.8

Koyna
Vx
Vy
3898.7 1671.4
2481.4 3861.2

Table 2:Base shear values in kN
5.2 Nonlinear Analysis
Push over curves and Performance levels for building
models are obtained in X and Y directions. The capacityof the building is determined by pushover curve while theperformance levels of the structure is determined based on
Hinge sequencing mechanism.
5.2.1 Hinging mechanism from Push-X and Y case
The overall performance level for G+13 story building
models were found between B and IO levels in both

Fig.2. 3D View of RC building model in SAP2000
4.1 Modeling of the structure:
The linear numerical analysis was done using ETABS
and the structure was remodeled in SAP 2000 using
Guidelines of ATC-40 and FEMA 356 .The overall

47

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 14
directions. It has been observed that very few (7-8 out of
1476) assigned hinges went beyond CP performance levelat a displacement value of around 33 mm. However there
is no indication of strength degradation at any
displacement value within range of target displacement.
The hinge location and performance level is carefully
studied and the associated member is redesigned.

Fig 5 Plot of Resultant Base Shear v/s Monitored
displacement for PUSH-Y case
5.2.3 Performance point.

Fig 3.Hinge mechanism for PUSH-X,Y case

5.2.2 Capacity Curves

Fig 6 Plot of Spectral Displacement v/s Spectral
acceleration for PUSH-X caseFig 4 Plot of Resultant Base Shear v/s Monitored
Displacement for PUSH-X case.

Fig 7 Plot of Spectral Displacement v/s Spectral acceleration
for PUSH-Y case48

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 14
The performance point for PUSH-X case was obtained at
a resultant base shear of 6968.4 kN corresponding to themonitored roof displacement of 22 mm while for the
PUSH-Y case it was obtained at a resultant base shear of
8448.6 kN corresponding to displacement of 32 mm.

ensured that the expected moment rotation demands onframe elements to be on a conservative side.
3)Numerous trial runs were performed to create astriking balance between computation time for analysis
and accuracy of the model.
4)In order to reduce the computation time the iterative
convergence tolerance was set to the order of 0.01 without
much compromising the accuracy of the model thereby
making this analysis suitable for design office settings.
5)Upon performing initial pushover runs hinges were
found to develop up to 4th Slab level in columns and hence
additional tie beams were added without compromising
the architectural constraints thereby increasing theredundancy in the lower stories.

5.3 Evaluation of Response Reduction Factor R
5.3.1 Estimation of strength factor:
Maximum Base Shear from Push over curve
Vx=6968.4 kN
Vy=8448.6 kN
Design base shear from Linear EQ Analysis
EQx=2364.6 kN
EQy=2225.8 kN
Using equation for strength factor using ATC-19
Rsi=Vi/EQi
Rsx=2.94 Rsy=3.79

6. CONCLUSIONS
1) There is not much mathematical basis for R values
tabulated in IS Code and it has been observed that thesevalues underestimate the inherent capacity of the structure
to undergo inelastic deformation beyond yield
2)In the present study the building was initially designed
and detailed considering R=5 however from push overanalysis it was observed that the R value obtained went
beyond 15.This considerable increase in capacity could be
attributed to the combined lateral resistance offered by
Ductile detailed RC Shear wall +SMRF.
3)The current code prescribed value for R is based on theprinciple of uniformly reducing the seismic demand at a
global level without taking in to account the individual
member capacity which can be considerably higher thanits demand at member level.
4) A comprehensive study needs to be performed to detail
hinges in RC members similar to shear fuses so that hinge
formation is localized and latent capacity of the structuralmember is triggered to resist the demand at member level.

5.3.2 Estimation of ductility factor
Maximum drift capacity =5 x yield drift (assumed limit)
μ=5.
Using equation for ductility derived by Miranda andBerteroRμ = {(μ - 1 / Φ) + 1}
Where
Φ for medium soil =1+{1 /(12T -μT)}–{(2 / 5T)*e-2(ln(T) – 0.2)^2}
For X directionΦx=0.913 for Tx=1.64 sec
Rμx=5.38
For Y direction
Φy= 0.828 for Ty=1.16sec
Rμy=5.84
5.3.3 Estimation of redundancy factor As per ATC-19
Drift redundancy ratio is 1 if there are more than 4 lines
of vertical seismic framing in a structure
Rr=1

REFERENCES
1)ATC-40. “Seismic evaluation and retrofit of concretebuildings.” Volume 1 and 2. Applied Technology
Council, California, 1996.
2)SAP2000 nonlinear version 19. Computers andStructures, Inc, CA.
3)ETABS nonlinear version 16.2.1. Computers andStructures, Inc, CA.
4)Pushover Analysis of a 19 storey concrete shear wallbuilding Rahul Rana1, Limin Jin 2 and Atila Zekioglu35)Formulation of Response Reduction Factor for RCC
Framed Staging of Elevated Water Tank using Static
Pushover Analysis Mr. Bhavin Patel 1 and Mrs. Dhara
Shah26)Proposed draft provisions and Commentary on Indian
Seismic Code IS 1893(Part 1),Sudhir Jain, CVR Murthy.

5.3.4 Estimation of Response reduction factor(R)
R= Rs * Rμ*Rr.
Hence
Rx=2.94*5.38*1=15.81
Ry=3.79*5.84*1=22.13
DISCUSSIONS:
1) Pushover analysis is numerically demanding and may
cause numerical difficulties for the software used to run
the analysis. Simplifying the model as much as possible
is helpful in completing the run and reducing thecomputation time.
2)Hinges were not assigned to shear wall as it isexpected to remain linear elastic till the performancepoint, development of any shear hinges was considered
undesirable from the design objective which also49

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 21

A PROPOSAL FOR AN OPTIMIZED SOLUTION FOR OPEN STOREY PROBLEM IN NONENGINEERED INFILLED MASONRY REINFORCED CONCRETE FRAMED BUILDINGSIN NEPAL
Kishor TIMSINA1, Chaitanya K GADAGAMMA 2, Hideomi GOKON3, Kimiro MEGURO4
1
Graduate Student, Department of Civil Engineering, The University of Tokyo, ktimsina@iis.u-tokyo.ac.jp(Corresponding author)
2
Project Assistant Professor, Institute of Industrial Science (IIS), The University of Tokyo,
chaitugk@iis.u-tokyo.ac.jp
3
Assistant Professor, ICUS, Institute of Industrial Science (IIS), The University of Tokyo,gokon@iis.u-tokyo.ac.jp
4
Professor, ICUS, Institute of Industrial Science (IIS), The University of Tokyo, meguro@iis.u-tokyo.ac.jp

Keywords: Infilled RC-frame, soft-story, optimization, performance, Applied Element Method.

1. INTRODUCTION
Urban and semi-urban areas of Nepal are rapidly
growing in the recent years. Reinforced concrete withmasonry infill (RC) buildings has become very popularin these areas. The data obtained from the National
Population and Housing Census (CBS 2012) shows that
there are currently about 540,000 RC buildings of 3-5
stories. Most of them are non-engineered buildings andconstructed with the involvement of masons and owners
only [1]. Generally, in the urban areas, the ground floorof more than 90% of the RC buildings are open forcommercial shutter or parking and close the upper floor
with infill masonry for the residential purpose (figure
1)[2]. So, the construction of this kind of non-engineeredbuildings without considering the consequences of theopen ground storey has resulted in many vulnerable
buildings. Reduction of the infill in a story relative to theones above increases the inelastic deformation demandon the columns of that story owing to concentration of
the global lateral drift demands to that story and thenear-fixity conditions of the columns of that story atfloor levels, as the infill panels of neighboring stories
restrain the drift there. Thus ultimately results in the soft
storey collapse of the open floor [3][4]. In recent 2015
Gorkha Earthquake (7.9Mw), the significant loss in RC
frame buildings was due to the soft storey collapse(figure 2) of the ground floor of these buildings due to a
reduction in strength and stiffness [5].
A questionnaire survey has been conducted with 35
Engineers who are working in 20 different
municipalities of Nepal, who are directly involved inbuilding permit and construction supervision. It suggeststhat the soft storey problem in Nepal is a socio-technicalproblem. The social aspects influencing the construction
and retrofitting of the buildings with the soft storey arei) livelihood of the people, i.e. their business/ parking
and livings ii) economy of the people iii) promotional
system for the implementation. The technical aspects arei) methodology of the construction ii) availability of thematerials. There are many existing technical solutions toaddress the soft storey problem, but many of thesesolutions are not acceptable by the landlords due to theirsocial and economic benefits, as most of these solutions

disturb the business of the landlords. Many othersolutions provide better performance and enough space
for the business purpose, but they are very costly. Thisissue has led to the construction of vulnerable buildings
with inadequate performance during earthquakes.
People need a cost-effective solution with locallyavailable materials which provides enough businessspace and performance during an earthquake.

Figure 1: Typical RC Figure 2: Soft storey
frame
with
infill damage of RC frame
masonry building with Building with open
soft storey
ground floor
The survey suggests that a feasible cost people canafford is within 10% of total cost of the building with thelocally available material, minimum space required forthe business shutter is 3 meters in length and desired
performance level is life safety during a large earthquake.
Following different existing solutions for soft storey
problems are analyzed in according to cost (C), material
availability (A), usability(business space) (U) andperformance (P) [3], [4] ,[6], [7] ,[8],[9],[10].
Applied Element Method [11]has been used for the
study of performance. H=high, L=low
SN Method of strengthening
C A U P
1.
Building with soft storey
L
Retrofitting with the addition of2.
L
infill wall in the open storey
3.
Strengthening all columns and H
beams
4.
Strengthening columns and H
Lbeams of the open floor only
Strengthening columns of the5.
Lopen floor only
6.
Strengthening with steel bracing H L L

50

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 21
7.
8.
9.

Strengthening with RC shear wall
Steel plate jacketing
Carbon fiber wrapping

1

2

4. CONCLUSION

H
L
H L
H L

3

A tool for developing an
optimized solution using RC
infill wall for soft storey
problem incorporating sociotechnicalconstraints
isdeveloped. The figure 5 shows
the sample of the solution
developed.

4

Figure: 5
Sample of optimized solution
5

6

7

8

REFERENCES[1] A. M. DIXIT, “PROMOTING SAFERBUILDING CONSTRUCTION IN NEPAL,” p. 9.
[2] D. Gautam, H. Rodrigues, K. K. Bhetwal, P.
Neupane, and Y. Sanada, “Common structural andconstruction deficiencies of Nepalese buildings,”
Innov. Infrastruct. Solut., vol. 1, no. 1, Dec. 2016.
[3] S. Makran, “Preliminary observations on theorigin and effects of the January 26, 2001 Bhuj
(Gujarat, India) earthquake,” 2001.
[4] D. R. Sahoo and D. C. Rai, “Design andevaluation of seismic strengthening techniques forreinforced concrete frames with soft groundstory,” Eng. Struct., vol. 56, pp. 1933–1944, Nov.
2013.
[5] T. Pokharel and H. M. Goldsworthy, “Lessons
learned from the Nepal earthquake 2015,” Aust. J.
Struct. Eng., vol. 18, no. 1, pp. 11–23, Jan. 2017.
[6] H. B. Kaushik, D. C. Rai, and S. K. Jain,“Effectiveness of Some Strengthening Options for
Masonry-Infilled RC Frames with Open First
Story,” J. Struct. Eng., vol. 135, no. 8, pp. 925–
937, Aug. 2009.
[7] R. Davis, P. Krishnan, D. Menon, and A. M.
Prasad, “Effect of Infill Stiffness on Seismic
Performance of Multistorey RC Framed Buildingsin India,” p. 9.
[8] M. N. Fardis and T. B. Panagiotakos, “SEISMICDESIGN AND RESPONSE OF BARE AND
MASONRY-INFILLED REINFORCED
CONCRETE BUILDINGS. PART II: INFILLEDSTRUCTURES,” J. Earthq. Eng., vol. 1, no. 3,
pp. 475–503, Jul. 1997.
[9] I. Erdem, U. Akyuz, U. Ersoy, and G. Ozcebe,“An experimental study on two different
strengthening techniques for RC frames,” Eng.
Struct., vol. 28, no. 13, pp. 1843–1851, Nov. 2006.
[10] S. Altin, Ö. Anil, and M. E. Kara, “Strengtheningof RC nonductile frames with RC infills: An
experimental study,” Cem. Concr. Compos., vol.
30, no. 7, pp. 612–621, Aug. 2008.
[11] K. Meguro and H. Tagel-Din, “APPLIEDELEMENT METHOD FOR STRUCTURALANALYSIS,” Doboku Gakkai Ronbunshu, vol.
2000, no. 647, pp. 31–45, 2000.
[12] K. Schittkowski, “NLPQL: A FORTRAN
subroutine solving constrained nonlinear
programming problems,” Ann. Oper. Res., vol. 5,
no. 2, pp. 485–500, 1986.

9

Figure 3: Different strengthening options

2. METHODOLOGY
Available methods of strengthening have either very
costly, or very low availability of materials, or very low
usability, or deficient performance. According tomaterial availability, concrete is readily available
material and performance wise strengthening with RC
shear wall has high base shear coefficient than others(figure 3).
The RC infill shear wall is then proposed to optimize to
get a practical and feasible solution according toperformance, cost, and usability. The cost of theretrofitting which includes the cost of materials,
construction and business disturbance is minimized as
an objective function subjected to performance
constraints for collapse prevention, and social
constraints of business space, and material properties.
The optimization problem is an iterative and dynamic
non-linear constrained problem with implicit
performance constraint. The analysis is done byincorporating
non-linear
sequential
quadratic
programming (NLSQP) in Applied Element Method[12].
Figure 4 shows the flowchart of this optimization
scheme.

Figure 4: Flowchart of optimization scheme in AEM

51

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 32

Comparison of Base joint column reactions of Buildings on various slopes and Non linear static
analysis
1

SANA SULTANA , PRADEEP KUMAR RAMANCHARLA2
1
M tech, Civil ,IIIT HYDERABAD, India, ssanasultana15@gmail.com
2
Professor, Civil, IIIT HYDERABAD, India, ramancharla@iiit.ac.in
Keywords: Hill slopes, equivalent static analysis, pushover analysis, base column joint reaction
compared to flat surface, so typical houses built on hilly
regions specially in India, Nepal, Bangladesh etc are of
G+3 to G+5. These buildings are unsymmetrical ingeometry and irregular in stiffness As hilly regions are
more vulnerable to earthquake, so providing safetymeasures to buildings on various slopes is more
important. Recent earthquakes like Nepal earthquake
showed worst effects particularly buildings on slopes as
the buildings on hilly slopes lacks simple and regularconfiguration, adequate lateral strength, stiffness andductility.

1. ABSTRACT
In the world most of the population lives on hills,
mountains, because of scarcity of flat land available. As
the hilly regions are more susceptible to earthquakes andlandslides. Buildings on hilly regions are prone damage
at time of earthquake. So there was a huge loss due to
Nepal earthquake, Nepal is situated near to Himalayas.
Common building typology on hilly regions is G+3, so
G+3 with 3 Bays in X-direction and Y-direction building
is considered on hilly regions of slopes. Slopes
considered for the study of damage pattern are 00, 150,
300, 450. When building is constructed on zero slope orflat surface region after the application of horizontal
loads there is no short column effect as the shear isequally distributed to all the columns. When the building
is on the sloped region shear is dominated in shortcolumn and there is unequal distribution of shear incolumns, so short columns fails first. Equivalent static
analysis is carried out and Base column joint reaction is
calculated on sloped regions and compared with varying
slopes of 00, 150, 300, 450. Base column joint reaction ismore in short column and less at long columns. To
reduce the base column joint reaction at short column
and to transfer base column joint reaction force from one
column to next columns, infill wall is modeled. Afterequivalent static analysis, pushover analysis is carriedout to find the energy in the buildings of varying slopesof 00, 150, 300, 450 with and without infill modeling andenergy curves and compared.
When the building is on the sloped region shear isdominated in short column and there is unequal
distribution of shear in columns, so short columns fails
first. Equivalent static analysis is carried out and Basecolumn joint reaction is calculated on sloped regions andcompared with varying slopes of 00, 150, 300, 450. Basecolumn joint reaction is more in short column and less atlong columns. To reduce the base column joint reaction
at short column and to transfer base column joint
reaction force from one column to next columns, infill
wall is modeled. After equivalent static analysis,
pushover analysis is carried out to find the energy in thebuildings of varying slopes of 00, 150, 300, 450 withand without infill modeling and energy curves andcompared.
2.INTRODUCTION
There is a huge population increase in the past years
and most of the population in the world lives on the hilly
regions either because of land scarcity or beautiful
sceneries. So there is a haphazard construction ofbuildings. Construction at hilly regions is different

LATERAL BEHAVIOUR OF BUILDINGS ON
SLOPES
Nepal earthquake known as GORKHA earthquake(M8.1) of April 2017 and Kangara earthquake (M7.8) of
1905 shillong were the most devastating earthquakes.
Most of the earthquakes triggers due to Himalayan plates.
Earthquake shows worst effects, when a building issituated on hilly regions. As the buildings on slopes dohave unsymmetrical in both horizontal and verticaldirections. Buildings on slopes posses variation of
stiffness and mass.
Dynamic characteristics of building on hills are very
differently from the buildings on the topography, because
buildings are irregular and unsymmetrical in vertical andhorizontal directions. Centre of stiffness and centre ofmass are not coinciding with each other, these type ofbuildings are subjected to torsional behaviour. The short,
stiff columns on uphill side attracts much higher lateralforces and prone to damage.
3.CASE STUDY AND ANALYSIS:A different cases of G+3 buildings on slope angles of 00,
150, 300, 450 are analyzed as per IS 456 and IS1893 in
SAP2000 as shown in figures
Structural element sizes
Beams : 300X300 mm
Columns : 300X300 mm
Slab : 120mm thickMaterial Properties
Grade of concrete : M25
Grade of steel reinforcement bars : Fe415
LoadingLive Load : 3kN/m3
Floor Finish load : 1kN/m3

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 32

On 30 degree slope without infill

1

2

3

4

G+3 Frame
The above building is subjected to Earthquake analysis
of Nepal earthquake
Two types of analyses were conducted equivalent static
analysis and pushover analysis

On 45 degree slope
Frames with masonry infill and different inertias ofcolumns are modeled for equivalent static analysis on
15 degree slope

Equivalent static analysis:
This method is a simplified technique to substitute theeffect of dynamic loading of an earthquake by a static
lateral force on a structure. Total seismic force or baseshear is calculated in horizontal directions of two axes.
This method is the best suited for low rise andsymmetrical buildings.
Frames are modeled for equivalent static analysis

HTML Document

000000000000000000000000000000000000000
Type-1 and Type-2 column sizes are 400X300 mm
BottomType-3 and Type-4 column
1 sizes are 400X500 mm andLeft mmcolumn 2, 3, 4 are 400X300
Right
Frames with masonry infill and different inertias ofcolumns are modeled for equivalent static analysis on
30 degree slope

On 15 degree slope without infill

Type-1 sizes of Column 1- 300X300, Column 2,3,4 300X300
Type-2 sizes of Column 1- 300X300, Column 2,3 400X300, Column 4- 300X300
Type-3 sizes of Column 1- 300X300, Column 2,3 400X300, Column 4- 300X300

53

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 32

Frames with masonry infill and different inertias ofcolumns are modeled for equivalent static analysis on
45 degree slope

Equivalent static analysis on 15 degree frame with infill
and comparison of percentage of column joint shear

Type-1 column 1 – 400X500, column 2&3 – 400X300,
column 4 – 400X500
Type-2 colum 1 – 500X600, column 2 & 3 – 400X300,
column 4 – 400X500
Type-3 all columns 400X300

Equivalent static analysis on 30 degree frame with infill
and comparison of percentage of column joint shear

4. RESULTS AND DISCUSSIONS:
Comparison of percentage of joint base column reactions
with out infill at column -1, column -2, column -3,
column -4
Colu

Percentage

On 15

On 30

On

mns

of

deg

deg

45 degjointscolumnonzero degree
1

5.6

35.4

38.02

37.8

2

7.3

8

10.21

11

3

7.3

2.92

2.24

1.064

4

5.6

2.4

1

0.7

Equivalent static analysis on 45 degree frame with infill
and comparison of percentage of column joint shear

X-axis represents columns and Y-axis represents
percentage of base column reaction

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 32

Pushover analysis:
After designing and detailing the RC frame structure, alinear static pushover analysis is carried out forevaluating structurtal response.
Rc frame with infill masonry and with out infill is carriedout on 00, 150, 300, 450
Pushover curves without infill on Zero degree
X axis represents displacement in mm
Y axis represents Base force in KN
Conclusions:When equivalent static analysis is done to buildingon zero slope every column takes equal shear andcolumn joint base reaction higher at inner columns
than outer columns.

When is building is on slope and analyzed withearthquake loads shorter columns tends to take moreshear force.

That’s why percentage participation of base column
shear is more in short columns in equivalent static

Pushover curves on 15 degree slope.

analysis graphs
With infill masonry base column shear is distributed
to columns where long columns participate lesser inshear.

In case of 15 degrees at least there is a participationof shear of long columns is 2% or 1% whereas in 30
degrees and 45 degrees it s going till 0%

Pushover curves on 30 degree slope.

In case of 15 degrees slope, type-2 and type-4 are
better configurations in taking column base shear.

In case of 30 degrees slope, type-1 and type-3 are
better configurations

Pushover curves of zero degrees has more energy
compared to slopeAs said on 15 degrees in pushover analysis type-2
and type-4 have more area under curve.

Pushover curves on 45 degree slope

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 32

REFERENCES:

Analytical Study and Some Observations From Sikkim

1. Agarwal, P. K. and Shrikhande, M. “Earthquake

Earthquake of September 18, 2011”

Resistant Design of Structure” Fourth Edition, PrenticeHall 2006.
2. Ashwani, K., Pushplata, “Building Regulations for
Hill Towns of India”, HBRC Journal, 2014
3 .Babu, N. J. and Balaji, K.Y.G.D, “Pushover analysis
of unsymmetrical framed structures on sloping ground”
International Journal of Civil, Structural, Environmental
and Infrastructure Engineering Research andDevelopment (IJCSEIERD) ISSN 2249-6866 Vol. 2
Issue 4 Dec - 2012 45-54.
4.Birajdar, B. G. and Nalawade, S. S., “Seismic analysis
of buildings resting on sloping ground”, 13th World
Conference on Earthquake Engineering, Vancouver,B.C., Canada, Paper No. 1472, 2004.
5.Chopra, A. K., “Dynamic of Structures: Theory andApplication to Earthquake Engineering” [M]. 2nd ed.
Upper Saddle River, N.J: Pearson/Prentice Hall, 2007.
6. Fajfar, P., “A nonlinear analysis method for
performance based seismic design”, Earthquake Spectra,
vol. 16, No. 3, pp. 573-592, 2000.
7. IS 1893-2002(Part-1), “Criteria for Earthquake
resistant design of structures Part, General provisions
and buildings”, Bureau of Indian Standards, New Delhi
110002.
8.Sreerama, A. K. and Ramancharla, P. K., “Earthquake
behaviour of reinforced concrete framed buildings onhill slopes”, International Symposium on New
Technologies for Urban Safety of Mega Cities in Asia
(USMCA 2013), Report No: IIIT/TR/2013/-1.
9.Yang, P. and Wang, Y., “A study on improvement of
pushover analysis”, Proceedings of 12th World
Conference on Earthquake Engineering, 2000, Auckland,
New Zealand
10 Y. Singh & Phani Gade, D.H. Lang & E. Erduran“Seismic Behavior of Buildings Located on Slopes - An56

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 69

NUMERICAL STUDY OF A NEW RETROFITTING METHOD FOR WEAK RC FRAME
BUILDINGS WITH MASONRY INFILL WALLS USING PP-BAND MESH TECHNIQUE
S.C.SADINENI1, H.GOKON2AND K.MEGURO3
1

PhD student, Department of Civil Engineering, the University of Tokyo, Japansilpa@iis.u-tokyo.ac.jp (corresponding author)

2

Assistant Professor, ICUS, IIS, the University of Tokyo, Japan

3

Director/Professor, ICUS, IIS, the University of Tokyo, Japan

Keywords: 3D-Applied element method, PP-band mesh, Seismic retrofitting, In-plane isolation
1. INTRODUCTION
Reinforced concrete with masonry infill (RCMI)
buildings are a major part of the building inventory in theurban sprawl. Many of them are either designed only forgravity loads or non-engineered (“weak frames”) inseismically active regions. Non-ductile beam-column
joints, improper rebar splicing, insufficient shear
reinforcement, and low-quality materials are typicalfeatures of the weak RC frames with masonry infills(WRCFMI). The collapse of WRCFMI buildings during
earthquakes has shown that their response is vastly
influenced by the interaction between the bounding
frame and its walls. Not only in-plane interaction ofmasonry infills is a problem but also the out-of-plane
collapse. The effect of masonry infill walls in the weakframe can be defined by the type of non-engineering
defect present in the structure and the material properties.
Masonry infill walls increase shear demand on thecolumn which may result in premature collapse. Also,
the diagonal strut formation of the masonry infill walls
shows a detrimental effect on the beam-column joint. To
mitigate the wall induced damage, many retrofitting
methods have been proposed to strengthen the frames
and isolate the walls. Many of the wall isolation
techniques are not popular as they make infill wall more
vulnerable in the out of plane direction and also giving
the connection between the wall and frame is very
complex and expensive process.
In this paper, we propose a PP-band mesh detailed
wall isolation retrofitting technique which considers theload-bearing capacity of the wall, benefits of wall
isolation, out-of-plane vulnerability, cost, andconstruction complexity.

mortar layer is used between beam and wall as a top
interface. At lower drifts, weak mortar layer cracks andlateral shear transfer from the bounding frame can be
avoided. In this case, transfer of vertical loads from beam
to the wall should not be a problem. Overall theseinterfaces play the key role in effectively mitigating theundesirable interaction between frame and wall at
moderate story drifts. And also, they act as a good energy
dissipation zones.
Finally, to minimize the out-of-plane collapse of thewall due to in-plane isolation, PP-band mesh is provided.
Cracks in the masonry infill due to in-plane forces
drastically reduce the out-of-plane strength, but with PPband mesh wall will regain its strength. PP-band
encourages progressive collapse while keeping the
integrity of the wall [3]. Due to this, during inelastic
stages, an alternative load path will form.

2. METHODOLOGY
The primary objective of this paper is to propose andinvestigate PP-band mesh detailing wall isolation method
for WRCFMI buildings. This proposed strategy isolates
the infill wall from columns and beam (Figure 1). The
flexible soft material is provided in the vertical gaps
between wall and column for fire insulation, namely
polystyrene foam. Due to this isolation, premature failureof the columns can be avoided and keeps the wall intact
before the inelastic state. At higher drifts, when the RC
frame exceeds the width of the gap, higher strength andstiffness can be provided by the infill wall. A thin weak

Figure 1: Layout of PP-band mesh detailed wall
isolation method

3. NUMERICAL STUDY
A three dimensional Applied Element Method (3DAEM) is used to test the effectiveness of the proposed
technique. Using the AEM a structure can be analyzed
from an initial stage of loading until collapse [2].

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 69
presented. In the bare frame building, initially, cracks
started at the end of columns and beam-column joints
and finally building failed due to the brittle failure ofcolumns. With the infilled frame, it is observed that due
to the collapse of the infills in the ground story produceda soft story effect which eventually leads to collapse.

(a)

(b)

(c)

Figure 3: Bare frame:(a) Initial stage; (b) Cracking; (c) Collapse

(g)

(h)

(i)

Figure 2: Simulation results for bare frame, infilled
frame, wall isolation using cellular material: (a), (b), (c)Initial stage; (d), (e), (f) Final stages of cracking; (g), (h),(i) Base shear force-Displacement curves
To validate the effectiveness of the tool to capture theframe-infill interaction and its failure modes, thecalibration of the numerical model in 3D-AEM userinterface was made based on the experimental results
obtained by Tsantilis et al. [1] on the in-plane cyclicloading of isolation of masonry infills in RC frames
using cellular material. The numerical model of the infill
panel is defined using micro modelling approach.
According to the obtained results, isolated specimen
initially behaves like a bare frame, as the drift levels
increases it quickly comes in contact with the wall andbehaves like tight fit infill frame (Figure 2). Tight fit
infill specimen experienced more severe cracks
comparatively with the isolated specimen. Numericalresults show good agreement with the experiment.
Next, to study the effectiveness of the newly proposed
technique to improve the performance of WRCFMI
structures, a two-story two-bay RC infilled box typebuildings(Buildings with bare frame, infilled andproposed retrofitting technique) was selected with nonductile beam-column joints and improper spacing of thestirrups. The response and failure mechanism of abovementioned cases are compared under earthquake loading.
In this paper, the collapse pattern of bare frame building(Figure 3) and infilled frame building (Figure 4) are

Figure 4: Infilled frame:(a) Initial stage; (b) Cracking; (c) Collapse
4. CONCLUSIONSIn the paper, we proposed a novel retrofitting
technique for the WRCFMI frames using PP-band meshdetailed wall isolation approach. By the calibration ofnumerical simulation using the AEM with experimental
results, we can say that the AEM was able to capture thebehavior of masonry infilled frames and the effects ofwall isolation. A 3D numerical analysis of RC bare frameand Infilled frame with non-engineering defects werealso presented. Remaining results will be presented at the
USMCA2018 in Hyderabad, India.
REFERENCES[1] A. V. Tsantilis and T. C. Triantafillou,2018“Innovative seismic isolation of masonry infills using
cellular materials at the interface with the surrounding
RC frames,” Eng. Struct., vol. 155, pp. 279–297.
[2] Meguro, K. & Tagel-Din, H. S. (2002). Applied
Element Method Used for Large Displacement Structural
Analysis. J. Nat. Disaster Sci. 24, 25–34.
[3] Sathiparan, N. & Meguro, K (2013) Shear andflexural bending strength of masonry wall retrofittedusing PP-band mesh. Construction 14, 3–12.

58

USMCA 2018

SESSION 4
URBAN SAFETY

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 33

TERRITORY CLUSTERING ON VISUAL ATTRACTIONS OF MULTI-OBJECTS
Miyuki WAKASUGI1, Yudai HONMA2
1

Graduate Student, Graduate School of Engineering, the University of Tokyo, Tokyo, Japan, miyuki-w@iis.u-tokyo.ac.jp
Associate Professor, Institute of Industrial Science, the University of Tokyo, Tokyo, Japan, yudai@iis.u-tokyo.ac.jp

2

Keywords: visual attraction, multi-objects, territory clustering
1. INTRODUCTION
In this research, we propose a new territory clustering
method which focuses on the visual attractions of multiple
objects. There are plenty of situations to analyze visual
perceptions in urban safety fields. One typical example isevacuation from damaged buildings. It is required toallocate the sign of an emergency exit, but there are also
several obstacles which shield our visibility. It means that
there are both “attractive” objects and “unattractive”
objects in disaster-stricken regions. It is important toorganize such spaces regarding visual perceptions. For
this purpose, we first calculate a visual balance of
attractive vs. unattractive objects. Then we categorize
spaces based on total visual balance and clarify spatial
cluster pattern which characterizes disaster regions.

Next, the length of the visual vector will be described.
Each object has an attractiveness (or unattractiveness)value. It means that attention is attractive if the value ispositive, and unattractive if negative. When negative, thedirection would be the opposite.
It is natural to express the length of the visual vector as
a function of both attractiveness degree of the object andthe distance to the object. In other words, it is nothingother than assuming that there is a spatial interaction
relation between the viewpoint and the object. Thus, thelength of the visual vector 𝒗𝑘 is defined as (5):|𝒗𝑘 | ≝ 𝑆𝑘 exp[−𝛾|𝒑min𝑘 |]Note that |𝒑min𝑘 | expresses the distance from theviewpoint to the object k, because the origin of thecoordinate system is in the evaluation point.
In addition, we suppose that each object has atransparent degree and |𝒗𝑘 | will be decreased based onthat value if it passes through other objects. Examples of
opaque objects are walls and glasses, meanwhile ponds
and furniture would be transparent. As a result, the visual
vector which also incorporates the transparency isexpressed as (6):

2. FORMULATIONLet us calculate visual effects by multiple objects.
Space is a two-dimensional plane, and we suppose a polar
coordinate system (𝑟, 𝜃) . We also assume that theposition of an evaluator is the origin of space O, and wecall it “evaluation point” from now on. In this paper, we
assume that all objects can be represented by polygons,
and the vertex coordinates of each object k are given as𝑀[𝒑1𝑘 , 𝒑2𝑘 , ⋯ , 𝒑𝑘 𝑘 ] . Further, each object has visual
attractiveness (or visual unattractiveness) 𝑆𝑘 .
Let us define a visual vector 𝑣𝑘 to represent viewing
the object k from the evaluation point O. For this purpose,
we have to calculate both direction and length of 𝑣𝑘 (seeFigure 1). First, we state haw to determine the direction.
Since we deal with several types of shape objects
including thin objects or large objects, we give thedirection to visual vector in the direction to the nearest
part of the object. Precisely to say, the direction of 𝒗𝑘 isdefined as follows:arg(𝒗𝑘 ) ≝ arg(𝒑min
𝑘 )

(5)

|𝒗𝑘 | ≝ Π𝑘′∈𝐶𝑘 𝑡𝑘′ × exp[−𝛾|𝒑min
𝑘 |]

(6)

(1)

where 𝒑minis the coordinates of the nearest part of𝑘object k. In the case, 𝑝𝑘min should be either the nearest
vertex of the polygon or the intersection of theperpendicular line to the polygon edge:𝒑min= min(𝒙ϵ𝐶𝑘 |∀𝒙′ ϵ𝐶𝑘 , |𝒙| ≥ |𝒙′ |)
k

(2)

𝑚
𝑚+1
)}
𝐶𝑘 = {𝒑𝑚𝑘 } ∪ {𝒒(𝒑𝑘 , 𝒑𝑘

(3)

Figure 1: set objects as coordinates

Here, 𝒒(⋅) is the intersection of the perpendicular linefrom the viewpoint O to the line segment pp’ which
satisfies (4):𝐎𝒒(𝒑, 𝒑′ ) ⊥ 𝒑𝒑′(4)

Figure 2: generate vectors from the evaluation point59

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 33
where 𝑡𝑘 is a transparent degree of object k (the range is[0,1]) and 𝐶𝑘 is a set of objects which get crossed withthe segment 𝐎𝒑min𝑘 .
As described above, the visual vector for the object k is
described by from (1) to (5). Since there are |𝐾| objects
in the target space, a set of viewing vector (6) is given as
follows:
𝑽 = [𝒗1 , 𝒗2 , ⋯ , 𝒗𝑘 , ⋯ , 𝒗|𝐾| ](7)
Figure5: maximum visual vectors

Figure 3, 4 is an example which is applied the model toBarcelona Pavilion. This building is regarded as one of themost sophisticated Architectures in the world. In the planview of Barcelona Pavilion, we can confirm several
objects affect results, such as ponds and statue (attractive),walls and glass walls (unattractive). As in Figure 1 and 2,
evaluation points are arranged in the plan view (Figure 3),
and the influence of attractive and unattractive objects is
calculated and shown in Figure 4.

Figure 6: visual attractive power relationship
Furthermore, it is also possible to simplify the visual
vectors by synthesizing vectors. The synthetic vector isdefined as𝒗total = ∑ 𝒗𝑘

(9)

𝑘∈𝐾

Figure 3: evaluation points on the plan of Barcelona
Pavilion

Figure 7: synthetic visual vectors
In any cases, by focusing on the "length" and "angle" ofthe vector, the characteristics of the space can be clarified.
Moreover, if it needs to compare the evaluation point O
and the evaluation point O’, it is easy to compare, that is
simply focused on V and V’. The dissimilarity of V and V’
can be calculated in several ways, such as comparing thelength of vectors(9), comparing the angle of vectors(10),and calculating the inner product of vectors(11). Here weassume that the characteristic of V is expressed as 𝒗max :Figure4: generate visual vectors from each evaluation
points
3. VISUAL VECTOR SIMILARITY(7) is a "distribution" of vectors, so we can discuss avariety of things by simply observing a result (Figure 2).
However, to focus on the characteristics more specifically,
we first focus on the maximum vector. The maximum
vector is defined as𝒗max = [𝒗𝑘 |∀𝑘 ′ , |𝒗𝑘 | ≥ |𝒗′ 𝑘 |]||𝒗max | − |𝒗′ max ||max(|𝒗max |, |𝒗′ max |)(10)|arg(|𝒗max |) − arg(|𝒗′ max |)|π(11)𝑑(𝑽, 𝑽′ ) =(8)

Since 𝒗max can be interpreted as a representing visual
vector, the absolute value of |𝒗max | and the argument
arg(𝒗max ) express the features of viewpoint.
To extract the largest visual vector, that means, it is also
possible to determine which object has the largest
influence at each evaluation point. The visual attractive
power relationship is shown in Figure 6.

𝑑(𝑽, 𝑽′ ) =𝑑(𝑽, 𝑽′ ) = −1 × 〈𝒗max , 𝒗′ max 〉(12)For (9) and (10), they are standardized, and the ranges are[0, 1].

60

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 33
4. CLUSTERING
Now, let us explain how to analyze clustering of thespace from the visual vector. The procedure is as follows.
First, we set a plurality of viewpoints O1 , O2 , ⋯ , ON in
the target space. Then, calculate 𝑁 × 𝑁 dissimilarity
matrix between arbitral viewpoints:
𝐷 = [𝑑(𝑽𝑖 , 𝑽𝑗 )]In each of clustering using maximum visual vector orsynthetic visual vector, it can be seen there are areas madeby effects of the visual attraction of ponds or the statue.
In this paper, we made clustering for 2 types, maximum
visual vector and synthetic visual vector, but in both cases,
the one cluster areas are classified in the similar place. It
can be said that the figures clustered based on the lengthof the visual vectors (Figure 8 and 11) show how much the
influence on the direction of the visual strength dependingon the distance from the attractive or unattractive object.
Next, the figures clustered by the angle of the visual
vectors (Figure 9 and 12) can be thought of as theorientation of the face of people who evaluate the spacewhen viewing the object. Finally, the figures are clusteredby the indexes of these two indicators, the angle andlength of visual vectors (Figure 10 and 13) are considered
to be more realistic space. In each cluster it is assumed tobe similar visual recognition.
We think this clustering method can be applied to an
evacuation planning. Setting the evacuation guidance
lights as a visual attractive object allows you to plan the
optimum evacuation route so that visually attracted areas
are continuous.

(13)

It is well known that D is the essential information forvarious clustering methods. For example, if we solve thep-median problem by interpreting the N viewpoints into
both the demand point and the facility candidate point, we
can obtain a representative viewpoint and clustering.
We calculated this dissimilarity matrix for two types ofrepresentative visual vectors (maximum vector orsynthetic vector). For each type, we clustered vectors bya degree of three types, dissimilarity of length only,
dissimilarity of angle only, dissimilarity of angle andlength. Results are shown from Figure 8 to Figure 13. Allof them are clustering into four parts. Figure 8 to Figure
10 are clustering figures about max visual vectors. Figure
11 to Figure 13 are clustering figures about total visual
vectors.

Figure 8: clustering by length of the maximum visual
vectorFigure 11: clustering by length of the synthetic
visual vector

Figure 9: clustering by angle of the maximum visual
vectorFigure 12: clustering by angle of the synthetic visual
vectorFigure 10: clustering by angle and length of the
maximum visual vector

Figure 13: clustering by angle and length of thesynthetic visual vector

6117th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 33
5. visual vectors on the route
The model proposed in section 2 enables us to calculate
the direction of view as the visual vector on the plan.
Therefore, by setting a route of movement, we can also
describe the visual vector when walking on the route.

Figure 14: visual vectors on the route
As an example, we set a route line that goes around theinside of the Barcelona pavilion with a single stroke. It is
assumed that the route passes over the evaluation point set
to calculate the visual vectors and only the vectors on theroute are extracted. Each visual vectors of evaluation
points are set to be influenced by the strongest force
exerted on those points. Based on the number of
evaluation points, the proportion of objects affecting theroute is about 37% for pond1, about 15% for pond2 andabout 10% for the statue.
By applying this idea to the evacuation route, we think
it is possible to analyze the location of the appropriate
guide light.
6. CONCLUSIONS
We focused on the influence of the object differs
depending on the locations of viewpoints, created a
distance matrix, and analyzed a spatial clustering. The
new techniques we proposed in this paper would be auseful tool for various requirements of urban safety
analysis such as determining the layout of emergency exit
signs.
REFERENCES[1] Bill Hillier, (2008), The Social Logic of Space, Reprint
edition, Cambridge University Press[2] Bill Hillier, (2015), Space is the machine: A
configurational theory of architecture, CreateSpace
Independent Publishing Platform62

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 17

A NOVEL TECHNIQUE FOR ESTIMATING EXPANSION OF RESIDENTIAL, COMMERCIAL
AND INDUSTRIAL REGIONS IN INDIAN MEGACITIESPRAKHAR MISRA1 and WATARU TAKEUCHI2
1 Post-doctoral Fellow, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan,

mprakhar@iis.u-tokyo.ac.jp (corresponding author)
2 Professor, Department of Civil Engineering, The University of Tokyo, Tokyo, Japan, wataru@iis.u-tokyo.ac.jp
Keywords: Digital building height, digital surface model, nighttime light, urban morphology, GDP, population
1 INTRODUCTION
Urban land-use maps are important in several applications
such as disaster response simulation, transport planning,
emission inventory, etc. However they are not publicly
available in several developing countries across the world
as they have data restrictions, are outdated or do not exist
as GIS data. Identifying residential, commercial and industrial regions is particularly interesting due to their different
contribution in emissions inventories. High spatial resolution emission inventories have been recommended by IPCC
AR5 report [1] under Tier III approach for emission estimation to overcome the current uncertainties in Tier I approaches that rely mostly on statistical data. Currently noneof the developing countries have used Tier III approach
which is critical to manage their grown urban air quality
issues [2]. Further it is also important to monitor expansionof these land-ue classes along with socio-economic growthparameters.

Figure 1: Overall flowchart to estimate emission parameters and generate annual emission trend

1.1 Objective
The objective of this paper is a) identification of land-use
urban morphology in terms of residential, commercial and Nighttime light: Nighttime light was derived from annual
industrial regions, and b) estimating their expansion func- median composite for the 2014 VIIRS DNB band. Its spation with socio-economic growth.
tial resolution is approximately 15 seconds (750 m).
Socio-economic data: Yearly population projections from
2 METHODOLOGY
United Nations population projections [5]. District level
The flowchart of dataset and methodology employed for es- gross domestic product (GDP) data was downloaded fromtimating expansion of residential, commercial and indus- Government of India’s Open Government Data (OGD) Plattrial regions is shown in Figure 1.
form (https://data.gov.in/).
Training data and classification: Training areas was se2.1 Data location
lected in the form of polygons by identifying residential (R),
Data location consist of 6 Indian megacities (referred as commercial (C) and industrial (I) areas using field visits andTier -1): New Delhi, Mumbai, Chennai, Bengaluru, Hyder- visual interpretation in Google Earth Pro. Thereafter buildabad and Kolkata, and 10 medium sized cities (referred as ing heights and nighttime lights over the training areas were
Tier -2): Agra, Ahmedabad, Allahabad, Amritsar, Kanpur, used as describing features into support vector machine for
Lucknow, Ludhiana, Patna, Raipur and Jaipur. These cities classification.
were chosen due to high presence of fine particulate matter(PM2.5 ) [6].
2.3 Urban expansion model
Following Seto et al. [4] that urban population growth and2.2 Data used
GDP per capita drive urban expansion, we used the followDigital Building height: An original digital building height ing simple model to estimate area (A) :model derived from freely available digital surface datasets
AUM = f (GDPpc , Population)∀UM ∈ R,C, I(1)
for the year 2001 (‘ASTER Global Digital Elevation Modelv2’) and 2011 (‘ALOS World 3D’) was used as height ofbuildings [3]. Figure 2 shows differences in building height 3 RESULTS AND DISCUSSION
for residential, commercial and industrial areas. Its spatial Classified land-use map is shown for a sample region in Figresolution is approximately 30 m.
ure 4. Tall residential buildings could not be identified ow-

6317th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 17
Table 1: Summary of urban expansion equations for areaof residential (R), commercial (C and industrial (I) regions
for Tier 1 and Tier 2 cities.)
Tier Equation
1
1
1
2
2
2

R = 0.0008GDPpc + 0.0021pop − 8.44
C = 9.32log(GDPpc ) + 0.0008pop − 97.73
I = 4.004log(GDPpc ) + 0.0005pop − 42.80
R = 8.17log(GDPpc )+20.43log(pop)−216.93
C = 1.20 × 106 GDPpc + 0.0005pop − 4.88
I = 4.67 × 106 GDPpc + 0.0012pop − 1.40

R2
0.75
0.61
0.83
0.72
0.76
0.81

Figure 2: Digital building height model extracted fromAW3D DSM shows height difference in residential, commercial and industrial areas. Example location shown iswith higher population although underlying drivers of urSouth of New Delhi (28o 29.744’N, 77o 5.138’S).
ban growth in the two types of cities could be different. The
latter may also be true for a reverse relationship of high population converging towards industrial areas since migrationfrom economically backward regions to industrial hubs iscommon in Indian cities. A logarithmic relationship of industrial areas with per capita GDP in Tier-1 cities could also
point to gradual stagnation in new industrial settlements.
4 CONCLUSION
Land-use maps of urban morphology for residential, commercial and industrial regions can be classified using building height and nighttime light with accuracies higher thanFigure 3: Polygons were drawn with help of Google Earth 49% with industrial areas requiring improvement in accuPro to select residential, commercial and industrial areas as racy. Further expansion patterns suggests that commercial
and industrial areas expand differently compared to resitraining data. This location is same as Figure 2.
dential areas in Tier-1 and Tier-2 cities. To ensure accurate land-use area expansion representation, building height
ing to similarity with industrial regions. Accuracy of classi- products from other years are required to be developed.
fication differed for each city. Abundance of heterogeneousclasses in close proximity led to errors, e.g. school build- Referencesing, bridges, overbridges, etc. Generally high accuracy was [1] IPCC. “Summary for Policymakers”. In: Climate
seen for residential areas (87% to 100%) and commercial
Change 2014: Mitigation of Climate Change. Conareas (64% to 95%). Accuracy over industrial areas varied
tribution of Working Group III to the Fifth Assessgreatly from 49% to 97%.
ment Report of the Intergovernmental Panel on CliAs seen in Table (1), land-use area of residential, commate Change (2014), pp. 1–33. arXiv: arXiv:1011.
mercial and industrial regions in Tier-1 cities was corre1669v3.
lated with per capita GDP (ranging from 0.65 to 0.89). In[2] Prakhar Misra, Aya Fujikawa, and Wataru Takeuchi.
Tier-2 cities, land-use area was correlated with both per“Novel decomposition scheme for characterizing urcapita GDP and population size (ranging from 0.69 to 0.77).
ban air quality with MODIS”. In: Remote Sensing 9.8
This implies that more industrial areas are found in regions(2017), p. 812.

Figure 4: Land-use urban morphology map for residential,commercial and industrial areas obtained after SVM classification. This location is same as Figure 2.

[3]

Prakhar Misra and Wataru Takeuchi. “Digital Surface
Model (DSM) Datasets for Built Structure Height Estimation over Indian Cities”. In: International Remote
Sensing Symposium (ISRS). Nagoya, Japan, 2017,
pp. 1–4.

[4]

Karen C. Seto et al. “A Meta-Analysis of Global Urban Land Expansion”. In: PLoS ONE 6.8 (2011). Ed.
by Juan A. Añel, e23777. arXiv: 1203.2655.

[5]

United Nations. UN Population Division. (Visited on
12/24/2017).

[6]

World Health Organization. Ambient (outdoor) air
pollution in cities database 2014. 2014. (Visited on
08/30/2015).

64

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 12

AN INVESTIGATION OF INITIAL CAVITY AND GROUND ARCHING BASED ON MODELTESTS
Y. OHARA1, R. KUWANO2, R. SERA3
1

Student, Institute of Industrial Science, the University of Tokyo, Tokyo, Japan, yuohara@iis.u-tokyo.ac.jp(corresponding author)
2
Professor, Institute of Industrial Science, the University of Tokyo, Tokyo, Japan, kuwano@iis.u-tokyo.ac.jp
3
Section chief, GEO SEARCH CO.LTD., Tokyo, Japan, r-sera@iis.u-tokyo.ac.jp
Keywords: sinkhole, model test, sand
1. ABSTRACT
Sinkholes often occur in urban roads and cause trafficinterruption and sometimes injure or even kill people. It
seems that a sinkhole is usually initiated by the formationof a cavity in the ground, but the mechanism of sinkhole
formation is not fully understood.
In this study, a series of model tests simulating theprocess of cavity formation/expansion was conducted. It
was found that the thickness of covering soil above acavity and width of a cavity seems to have a correlation.

Figure 2: Typical example of the tests
3. RESULTS
3.1 INITIAL CAVITY
In this paper, initialcavity is defined as a cavity
formed immediately after
the first drainage. Also,height and width of a cavity
is defined as shown infigure 3.
Figure 4 shows therelationship between theheight/width of an initialcavity and initial ground

2. MODEL TESTSThe test apparatus used in this study is schematicallyshown in Figure 1. Uniform silica sands of different
grain size (no.3 (D50=1.5mm), no.5 (D50=0.35mm), no.7
(D50=0.15mm)) were used for the model ground. Drysand was placed in the soil chamber and colored sandlayer was put in front every 2.5 cm to observe thedeformation of the ground. The relative density of themodel ground was around 50%.
First, water was supplied to the ground from a watertank through side walls or bottom of the ground. Afterthe ground water level was stabilized, the plug put in the
opening at the center of bottom plate was removed tostart the test. Soil as well as water started to drain
through the opening.
The width of the opening was set 5mm, 10mm or
15mm. Repetition of water supply/drainage lead to the
expansion of a cavity (Figure 2). When the cavity
became wide and approached the surface covering soil
became insufficient to support its weight and eventuallycollapsed (=sinkhole).

Figure 3: Definition ofeach term

Figure 4: Height/width of an initial cavity vs. initial
ground water level

Figure 1: Test apparatus

65

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 12
water level. As for height, it tends to increase with theincrease in initial ground water level. Focusing on thecircle plots and y=x line, it seems that the ceiling of an
initial cavity tends to be the same or a little higher thaninitial ground water level. On the other hand, width of an
initial cavity tends to increase much less steeply thanheight.
3.2 GROUND ARCHING
Ground arching is a phenomenon that force acting
between soil particles transfer in arched shape above
subsidence part to stabilize the structure. It is assumed
that if the thickness of covering soil above a cavity isshort compared to the width of the cavity ground arching
cannot develop and the cavity will collapse[1].
Figure 5 shows the relationship between the thicknessof covering soil above a cavity and the width of a cavity
immediately before collapse. As shown in figure 3, y1
and y2 in figure 5 stand for the minimum and maximum
thickness of covering soil respectively. According tofigure 5, there seems to be correlation between the mean
thickness of covering soil ((y1+y2)/2) and the width of acavity.
This relationship enables us to roughly estimate
whether a cavity is stable or not. If the plot of a cavity isunder the line, it means that the covering soil is not thickenough to stabilize. In other words, ground arching
cannot develop and the cavity is likely to collapse. Since
this linear relationship can be useful to estimate thestability of a cavity, further investigation should be
conducted.

Figure 6: History of cavity expansion.
Line 1 and 2 in figure 5 are steeper than others andthat can be ascribe to their different way of cavity
expansion. As shown in figure 7, vertical shear band wasformed at the moment of cavity expansion in line 1 and 2
and this could lead to the relatively steep decrease in the
thickness of covering soil.

Figure 7: Cavity expansion in line 1 (left) and 2 (right)
4. CONCLUSION
In the model tests simulating cavity formation/expansion,
followings were observed.
1. The ceiling of an initial cavity tends to be the same ora little higher than initial ground water level.
2. The width of an initial cavity tends to increase muchless steeply than height.
3. Immediately before collapse, there seems to becorrelation between the thickness of covering soil andthe width of a cavity. The thickness of covering soil
tends to be larger with the increase in the width of acavity.
4. This relationship enables us to roughly estimate
whether a cavity is likely to collapse or not.
5. A cavity tends to expand horizontally rather thanvertically.

Figure 5: Thickness of covering soil vs. width
3.3 HISTORY OF CAVITY EXPANSION
Based on the field survey conducted at national roads
in Japan, Nakata reported that a cavity tends to expand
horizontally rather than vertically[2]. Figure 6 shows thehistory of cavity expansion in the model tests. Eachgroup of plots connected by line stands for how the
thickness of covering soil and width of a cavity changedin each test. In general, width of a cavity tends toincrease more than mean thickness of covering soil
decreases. It means that a cavity tends to expand
horizontally and this corresponds to the report by
Nakata[2]. It can be said that first a cavity expands
horizontally and then expands vertically.

REFERENCES[1] R. Kuwano, Y. Ohara, and R. Sera (2018), An
investigation of mechanism of cavity expansion andcave-in formation in sand observed in model tests, 53rd
conference by Japanese geotechnical society, Takamatsu,
July 2018[2] Y. Nakata, R. Kuwano, R. Sera (2018), A study on
progress of subsurface cavities under national roads inJapan, Japan Society of Civil Engineers 2018 Annual
Meeting, Sapporo, August 2018 (in Japanese)66

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 20

DISCOM: A ROBUST POST-DISASTER COMMUNICATION INFRASTRUCTURE
A P ADITYA VARMA1, ABHINAV KOLLA2, RISHAAD3, DILIP KUMAR4, PRAFULLA
KALAPUTAPU5,BHARGHAVA RAJARAM6
1 Second Year Student, Civil Engineering, Mahindra Ècole Centrale, Hyderabad, India,

adityavarma170124@mechyd.ac.in
2 Second Year Student, Civil Engineering, Mahindra Ècole Centrale, Hyderabad, India, abhinav170113@mechyd.ac.in
3 Second Year Student, Civil Engineering, Mahindra Ècole Centrale, Hyderabad, India, rishaad170130@mechyd.ac.in
4 Faculty, Civil Engineering, Mahindra Ècole Centrale, Hyderabad, India, venkata.pasupuleti@mechyd.ac.in
5 Faculty, Computer Science Engineering, Mahindra Ècole Centrale, Hyderabad, India,

prafulla.kalaputapu@mechyd.ac.in
6 Faculty, Electrical & Electronics Engineering, Mahindra Ècole Centrale, Hyderabad, India,

bharghava.rajaram@mechyd.ac.in
Keywords: Disaster Management, Communication System, Ad-hoc, Bluetooth network, Emergency, Broadcast, Mobile
Application.
1. INTRODUCTION
3.
S M A RT P H O N E A N D E M E R G E N C YRESPONSE

One of the most immediate and significant impacts offlooding and natural disasters is the sudden and widescale breakdown of communications infrastructure.
When public communication networks fail, the impact
can be widely felt and has the ability to interrupt accessto standard mobile or landline telecommunications, andas an extension, access to the Internet. Locating those
who maybe trapped or injured becomes nearly
impossible for emergency responders, and rescue efforts
are further complicated by the inability to coordinate via
standard methods of communication. Whether thesesystems are completely or just partially knocked offline,
communications systems during a natural disaster can be
the difference between life and death for those affected.

Based on smartphone shipment 2015 release researchsuggests that for 60% of all handheld gadgets are
smartphones and the numbers are still growing and it isgetting more popular among common people. In
smartphones, number of emergency applications are
growing that are beneficial in emergency response. Dueto the innovations in GPS technology, this can be very
helpful in the tracking of assets and also helpful to send
information to emergency management headquarters forthe analysis of destruction caused by the disaster [1]. In a
critical circumstances, number of users use their smart
phones are represented in percentage. 50% users use
their smart phones in emergency situations including
local accidents, 14% users use their smart phones to
notify the emergency management authorities to get help
in case of any disaster, 8% users use their smart phones
for medical emergency, 5% use their phones for
emergency helpline [2]2.
COMMUNICATION INFRASTRUCTURE
FAILURES
Physical Damage to Network Devices: Perhaps the mostcommon cause of communications failures during
disasters is the physical damage to devices orcomponents that make up the network infrastructure.
Hurricane-force winds, floodwaters, and seismic activity
can all create physical disturbances that have power todo significant damage to cities and the vulnerable
communications equipment that’s responsible forsupporting these areas.

Local Accidents
Medical Emergency
Fire Accidents

DisasterHelpline

3%

Network Congestion: When disaster strikes, the “pipes”
that make up our communications networks often
become congested with exceptionally high levels of data
traffic, as those impacted seek to contact family andfriends, emergency personnel work to coordinate relief
efforts, and hundreds more upload pictures and videos ofthe damage.

8%

5%

14%
70%

67

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 20
Chart -1: Usage of Emergency Applications [2]and cellular network to communicate. DisCom
implements a broadcast-based network wherein eachuser broadcasts the availability or demand for certain
essential resources.

4. IDEA OF AD-HOC NETWORKS
Ad hoc networks have been proposed as an appealing
communication technology to deal with the unexpectedconditions emerging during and/or after the occurrenceof a disaster because network connections cannot always
be preserved in a disaster scenario. Ad-hoc networks
allow for the rapid deployment of fiber-like connectivity
in situations where capacity is needed on an expedited
basis, and they allow both victims and emergency
workers to communicate when it is most important.
These network connections can be established quickly,
even in areas where regular infrastructure has been
devastated, by using a wireless transport device atop a
mobile platform such as a COW (cellular on wheels) or a
COLT (cellular on light trucks). The vehicle simply
manoeuvres into the area and can begin transmitting
within a matter of hours, much faster than the time ittakes to repair or replace existing network infrastructure
equipment. In fact, a number of COWs were deployed in
the aftermath of Hurricane Katrina to provide criticalphone service to rescue and recovery workers when thearea’s cellular networks had otherwise been completely
cut off, and allowed the responders to organise theirefforts and focus on the areas most devastated by thestorm. [3]The data received is then mapped with the help of theGoogle Maps API, which now shows a map of allavailable resources in the vicinity. This broadcast packet
is cumulative wherein each user not only broadcasts theirdata, but also the data received from other users in orderto establish a network. The broadcast is repeated at apredetermined interval or on user prompt. If the status of
resources changes with respect to any user, the updated
data is broadcast and the necessary changes are enacted
across all users on this network. DisCom also broadcasts
in a chatbot medium their GPS location, and status.

5. OUR CONCEPTThe failure of communications networks is a common
occurrence during many disaster scenarios, and yet wehave continued to see this preventable sequence of
events play out time after time with deadly, expensive,and potentially preventable consequences withconstructing temporary communication infrastructuresuch as COW and COLTs.

6. CONCLUSION

So in this work, we present DisCom, a simple postdisaster smartphone-based application of lite version
running low on memory which establishes an ad-hoc
bluetooth network for the purpose of communicating the
supply and demand of basic essentials and resources nearusers within a well-defined range with no internet access

The applicability of ad hoc networks in disaster scenarios
is still in an initial phase. Most works done on this idea
are only based on simulations rather than realexperimentation. While DisCom does not focus on68

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 20
security or efficiency, it provides a simple relief
communication infrastructure in the wake of a disaster,
without the need for any additional resources.
REFERENCES[1] Hafsa Maryam, Qaisar Javaid, Munam Ali Shah,
Muhammad Kamran, “A Survey on Smartphones
Systems for Emergency Management (SPSEM)”,(IJACSA) International Journal of Advanced Computer
Science and Applications, Vol. 7, No. 6, 2016, Page 302.
[2] S.Mythili and E.Shalini,“A comparative study ofSmart Phone Emergency Applications for Disaster
Management”, International Research Journal ofEngineering and Technology (IRJET), Volume: 03 Issue:
12 | Dec -2016, Page 394.
[3] When Communications Infrastructure Fails During a
Disaster - Written by Christina Richards
https://www.drj.com/articles/online-exclusive/whencommunications-infrastructure-fails-during-adisaster.html

69

USMCA 2018

SESSION 5
BUILDING SAFETY II

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 44
EFFECT OF INFILL WALL STIFFNESS ON SEISMIC ANALYSIS OF HIGH RISE BUILDING HAVINGMASS IRREGULARITYSUSMITHA YELLA1 and MAGANTI JANARDHANA2
1Formerly P.G. Student, JNTUH College of Engineering Hyderabad, Hyderabad, India,
2Professor, JNTU Hyderabad, Hyderabad, India.

Irregular buildings constitute a large portion of the modern urban infrastructure. In multi storeyed framedbuildings, damage due to earthquake ground motion generally initiates at locations of structural weaknesses present in
the lateral load resisting frames. In some cases, these weaknesses may be created by irregularities in stiffness, strength
or mass between adjacent storyes. Such irregularities between storyes are often associated with twisting of buildings.
There are many examples of failure of buildings in past earthquakes due to iregularities in mass. Irregularities in massarise in buildings due to many reasons like using one floor for both residential and commercial activities, constructionof swimming pool in a floor or use of one floor for storing heavy materials etc. When such buildings are located in ahigh seismic zone, the structural engineer’s role becomes more challenging. Therefore, the structural engineer needs tohave a thorough understanding of the seismic response of irregular structures. Infill panels are widely used as partition
walls as well as external walls of the building to fill the gap between RC frames. The infill walls (non-structuralmembers) may provide considerable stiffness to the building and hence may improve the performance of the RC
building during ground motions. The effects of non-structural infill walls are not included generally during analysis anddesign of reinforced concrete structures. However, these infill walls have considerable effect on the structural response
as studied by many researchers all over the globe. In this paper, a 21-storyed RC frame having mass irregularities in theelevation is considered. The effect of ground motion on RC framed building has been carried out by considering infill
wall stiffness and without the stiffness of infill wall. Equivalent Lateral Force method and Response Spectrum method
are adopted for the seismic analyses. The analysis is carried out using commercially available software package SAP
2000 and comparison of different parameters like storey shear, storey drift, time periods is carried out.
Keywords: Infill wall, Mass irregularity, Base Shear, Storey Drift
1.Introduction :In recent years, some floors of buildings are used
for different purposes like car parking, storing
heavy mechanical appliances, for observatory
towers at top etc. This results in variation of mass,and stiffness at different storyes. When suchbuildings are located in a high seismic zone, thestructural engineer ’s role becomes morechallenging. Therefore, the structural engineer
needs to have a thorough understanding of theseismic response of irregular structures. In recent
past, several studies have been carried out toevaluate the response of irregular buildings.
2.Description of Building :A commercial cum residential building of G+20
irregular building having the base dimension of plan
23.62 m × 25.15 m with stilt floor of 3m height andtypical floor height of 4.0 m is considered for the
analysis.

Figure.1.Typical floor plan of the building_____________________________________
1Email: susmitha.thesmilinggirl@gmail.com
2Email: prof.jmaganti@gmail.com

7017th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 44
Live Load (Roof):

1.5 kN/m2

Stair Case Load –Live:7.734 kN

Stair Case Load –Dead:

30.937 kN

Wall load (230 mm thick):16.0 kN/m

Wall load (115 mm thick):8.0 kN/m

Dead Load (Commercial) :12.75 kN/m2

C.

Section properties :Plinth Beam Size:
Roof Beam Size:
Column Size:

Figure.2.Elevation of the building

Slab Thickness:
Thickness of Wall:

The building has 21 storyes symmetrical in plan with 5bays in X direction and 8 bays in Y directions, and its
plan and elevation are shown in Figs 1 and 2
respectively. The superstructure is modelled using thecommercially available software SAP2000 (v14.0.0)[3] as a space frame.
1.

D.

Type of soil:

MediumImportance factor:

1

Response reduction factor:

3

Damping ratio:

5%

Type of structure:

OMRF

B.

M35
Fe500

E. Infill Walls :The infill walls are modelled as equivalent struts andshown in the Figure 3 and the strut parameters arecalculated using Eq. (1) and shown in Table 1

The parameters and loads considered for the analysis
are as per IS 1893 (Part1)-2002 [1] and are mentioned
below.
III

Material Properties:

Grade of Concrete:
Grade of Steel:Input Data

A. Seismic Parameters:
Seismic Zone:

400 × 500 mm
400 × 650 mm
400 × 750 mm
450 × 1500 mm
1500 × 450 mm
500 × 1500 mm
1500 × 500 mm
100 mm ,150 mm & 250mm
230 mm & 115 mm

The equivalent width (w) of the infill wall proposed by
Hendry [2] is given by

Loads

Unit Weight of Concrete:

25.0 kN/m3

Live Load (Residential):

2.0 kN/m2

Live Load (Commercial):

15.0 kN/m2

Live Load (Cellar):

5.0 kN/m2

θ = slope of infill wall diagonal to the horizontal,
Em= Elastic Modulus of masonry wall= 2720.0 N/mm2,
Ef = Elastic Modulus of masonry of frame material,t = Thickness of the infill wall,h = Height of the infill wall,_____________________________________
1Email: susmitha.thesmilinggirl@gmail.com
2Email: prof.jmaganti@gmail.com

7117th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 44
L = Length of the infill wall,
Ic = Moment of Inertia of the column of the frame,
Ib = Moment of Inertia of the beam of the frame, andw = Width of the Equivalent Strut.

Table 1: Equivalent strut parameters in X and YDirections
Strut

Equival
ent
Width
(m)

Thick
ness
(m)

Strut

X-Direction

Equiv Thick
alent
ness
Widt
(m)
h (m)

Y-Direction

01

2.00

0.23

06

2.50

0.23

02

2.25

0.23

07

2.00

0.23

03

2.00

0.115

08

1.75

0.23

04

2.50

0.115

09

2.35

0.115

05

2.25

0.115

10

2.00

0.115

3.Results and Discussion
The regular building and a building with mass
irregularity were analyzed by adopting linear static anddynamic analyses procedures, using commerciallyavailable software SAP 2000 (v14.0.0). Also effect ofinfill wall stiffness is also studied.
3.1. Results of Linear Static Analysis : The lateralloads in a regular building are relatively lesser whencompared with that of building having mass
irregularity except for the top floor where it is almost
equal. This may be due to increase of overall weight ofthe structure as shown in the Figure 4. With theintroduction of mass irregularity in the structure at 3rd
floor (as per table 5 of IS 1893 (part 1):2002 mass isincreased by 200% compared to the floor at the top),
there is an increase in seismic weight of the floor at thelevel 15 compared to increase in the mass. Lateral load
is not getting changed with the introduction of infill
wall stiffness. This is because mass effect of diagonal
strut is not taken into account.

Figure . 3.Building with infill walls_____________________________________
1Email: susmitha.thesmilinggirl@gmail.com
2Email: prof.jmaganti@gmail.com

72

300

50

75

100

Storye Height (m)Storye Drift (m)Figure.4. Lateral Loads on Storeys of Regular building
and Building having mass irregularity along with infill
wall stiffness

Regular building
Irregular Mass building
Infill (X)Infill (Y)0100Storey shears of regular building are slightly less whencompared with that of building having mass
irregularity as mass of the structure is increased asshown in Figure.5

0.003825

0.002500.0013

0

0.005

150

lateral load (kN)

450

600

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad
Regular building__________________________________________________________________________________________
Paper No. 44
Irregular Mass building
Infill (X)Infill (Y)level 15 there is slight increase in the drift. As per the
IS 1893:2002(part 1), the drift of any floor should not
be more than 0.004 times the storey height. i.e.,
0.016m in this case for a storye height of 4m. The
storye drifts of all the storyes of regular building andbuilding having mass irregularity with and without theeffect of infill wall stiffness are satisfying the drift
limits prescribed by the IS 1893 (Part1):2002.

0

25

50

75

100

50

Figure.6. Inter storye drifts of Regular building andBuilding having mass irregularity along with effect ofinfill wall stiffness.
Irregular mass building
Regular Building
Infill (X)Infill(Y)025

Storye Level (m)75

Storye Height (m)

0

1250

2500

3750

5000

Storye Shear (Fx kN).Figure.5. Storey shears of Regular building andBuilding having mass irregularity along with infill wall
stiffness.
It is observed that that the storey drifts of a regularbuilding is almost equal with building having mass
irregularity till 3rd floor (level 15) where there is nochange in mass as shown in the Fig.6. With theintroduction of mass irregularity in building at storey_____________________________________
1Email: susmitha.thesmilinggirl@gmail.com
2Email: prof.jmaganti@gmail.com

73

The storey displacements of regular building is lesscompared to that of building having mass irregularity
due to difference in mass of the storey as shown in the
Figure 7. Storey displacements of building having mass
irregularity by considering effect of infill wall stiffness
are relatively lesser compared to that of building
having mass irregularity in both X and Y direction.
Further, storey displacements are the least for thebuilding having infill wall in the X direction.

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 44

40

60

The time period of regular building is relatively higher
when compared to that of building having mass
irregularity as shown in the Figure 9. It can also be
observed that with the increase in the stiffness of thebuilding, the modal period is getting reduced.
4

Period (secs)

20

Regular building
Irregular Mass building
Infill (X)Infill (Y)0

Storye displacements(mm)803.2. Response Spectrum Analysis :

0

25

50

75

100

Storye height (m)Figure.7. Storey displacements (max) of Regularbuilding and Building having mass irregularity
including the effect of infill wall stiffness.

3
Regular Building
Mass Irregular
Infill(X)
Infill (Y)

2
1
0

1

2

3

4

5

6

7

8

9 10 11 12Mode Number
From Figure 8 it can be observed that the storey
overturning moments of regular building are more thanthat of the building having mass irregularity.

From the Figure 10, it can be observed that storey
shears of regular building is slightly lesser whencompared with building having mass irregularity as
mass of the structure is increased.

0

25

50

75

100

75
50
25

Storye Level (m)

-3000

100

-1500

Regular building
Irregular Mass building
Infill (X)Infill (Y)

-4500
-6000

Overturning Moments (kN-m)

0

Figure.9. Variation of time periods with number ofmodes of regular and mass irregular building alongwith effect infill wall stiffness.

Irregular mass building
Regular Building
Infill (X)Infill(Y)0

Storye height (m)0Figure.8. Storey overturning moments of Regularbuilding and Building having mass irregularity alongwith effect of infill wall stiffness.

1250

2500

3750

5000

Storye Shear (Fx kN)
Figure.10. Storye shears of Regular building andBuilding having mass irregularity along with infill wall
stiffness. (Response Spectrum Method).

_____________________________________
1Email: susmitha.thesmilinggirl@gmail.com
2Email: prof.jmaganti@gmail.com

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 44
It can be observed from Fig 11 the variation of storey
drifts in response spectrum method.

0.00250.0038i.

ii.

0.0013

Regular building
Irregular Mass building
Infill (X)Infill (Y)0

Storye Drift (m)0.005

4. Results and Conclusions :Based on the analysis of G + 20 storeyed building
having mass irregularity, following conclusions are
drawn.

0

25

50

75

100
iii.

Storye Height (m)Figure.10 Storey drifts of Regular building andBuilding having mass irregularity including effect ofinfill wall stiffness. . (Response Spectrum Method)

iv.

v.

40

60

Regular building
Irregular Mass building
Infill (X)Infill (Y)20

5. References :[1] IS 1893(Part 1): 2002 “Criteria for earthquake
resistant design of structures”, Part1 General
Provisions and building, Bureau of Indian Standards[2] Paulay, T. and Priestley, M. (1992) “Seismic
Design of Reinforced Concrete and Masonry
Buildings”,John Wiley & Sons, Inc., New York
[3] SAP 2000. Integrated Software for structural
analysis and Design, Computers and Structures Inc.,
Berkeley, CA, USA[4] Koalasani.Rajshekar and Maganti.Janardhana(2016) “Effect of infill wall stiffness on seismic
analysis of high rise buildings resting on sloping
ground”, Structural Engineering Convention(SEC-2016).

0

Storye displacements(mm)80

By observing the trend in Figure 11 it is clear that thestorey displacements of regular building is lesscompared to that of building having mass irregularity
due to difference in mass of the storeys.

0

25

50

75

Storey drift is a not only a function of storey
height but also depends on the weight of that
storey. Also introduction of infill wall
stiffness can reduce the storey drifts.
Storey shears of buildings having mass
irregularity are relatively higher than that ofregular buildings. Storey shear of thestructure, if infill wall stiffness are considered,are quite larger than the structure without
infill wall stiffness. Hence, stiffness of infill
walls should be considered for design since it
represents a true picture of the behavior ofstructure.
Displacements of the different storeys forbuilding having mass irregularity are
relatively higher than that of the regularbuilding. For the same building withi n t r o d u c t i o n o f i n f i l l s t i ff n e s s , t h e
displacements are considerably getting
reduced.
Time period is getting reduced with theincrease in number of modes. The time periodof building with mass irregularity iscomparatively lesser than that of regularbuilding as stiffness of the building
considered is higher than that of a regularbuilding.
Time periods of the model with infill walls arelower than the model without infill walls,
because the infill walls further increase theoverall stiffness of the structure and hence
lower the time periods.

100

Storye height (m)Figure.11 Storey displacements (max) of Regularbuilding and Building having mass irregularity
including the effect of infill wall stiffness. . (Response
Spectrum Method).

_____________________________________
1Email: susmitha.thesmilinggirl@gmail.com
2Email: prof.jmaganti@gmail.com

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 45

SEISMIC BEHAVIOR OF FLAT SLAB BUILDINGS IN SEISMIC ZONES BY LINEAR
DYNAMIC ANALYSIS: A COMPARISON BETWEEN THE CONVENTIONAL
BUILDINGS TO FLAT SLAB BUILDINGSDR NARENDER BODIGE1 and A. NARESH2
1Associate Professor, Anurag Group of Institutions, Venkatapur, Ghatkesar, Hyderabad, India, Email:drnbodigece@cvsr.ac.in
2PG Student, Anurag Group of Institutions, Venkatapur, Ghatkesar, Hyderabad, India, Email:atheninaresh@gmail.com

space, easier formwork, shorter construction, flexibility inroom layout, Ease of Installation of building services,
reduced cladding costs and prefabricated services. Thisbuilding is more attractive in recent time in India due tothe fast-growing country in the economy and this brings
demands in increasing of infrastructure facilities alongwith the growth of population and face a shortage of land.
The Major cities in India like Delhi, Mumbai, Hyderabad,Bangalore, Chennai has started to construct the mid-rise tohigh rise flat slab building for commercial use and thisconstruction of activities increase day by day as
exponential form due to more job opportunity andincreasing industrial hubs in an urban centre. Thesebuildings are efficient in resisting gravity load but haveexcessive lateral drift when subjected to seismic loading.
However, past earthquake studies show that manybuildings with flat slab have performed poorly. In
Christchurch earthquake (2011) flat slab building causes
punching shear failure of the slab-column connections.
The columns of structure punched through the concreteslab floor systems, dropping the floors and roof andcompletely collapsing the interior of the building inNorthridge Earthquake (1994). In the Loma Prieta
earthquake (1989) excessive lateral drift observed due toexcessive interior damage, increase P-delta effect andfailure of the slab-column connection. It is mainly due toinadequate resistance for punching shear under theearthquake loading. The seismic analysis of flat building
is studied least touched area and past literature shows thatstudy the basic parameter i.e various aspects andbehaviour of flat slab building under the earthquake
forces. G. Patwari and G. Kalurkar (2016), studied theeffect of RC flat slab with the shear wall at a different
location for various heights of the building. A comparisonof the seismic behaviour of flat slab structure withconventional RCC Structures is done by D.N. Shinde et.al(2016) and N.mircic et.al (2008), studied the bearing
capacity of flat slab with comparison of other models i.eframe, flat slab with shear wall, flat slab strengthened byperimeter beam and flat slab strengthened by shear walland perimeter beam. Flat slab buildings are studies very
limited and not understand Flat slab with different slabcolumn joints with over conventional building andincluding effects due to seismic zone and ground motion

ABSTRACTIn the present situation, a fast growing economy and rapid
urbanization of the country in India leads the requirementof more infrastructure development. The more
employment opportunity is in urban cities which lead tothe fast rate of the construction and more demand forspace requirement of commercial buildings. Flat slabbuilding is more popular in the multistoried building
because of the absence of deep beams, and story height
can be reduced, use of space, easier formwork and shorter
construction time. However, past earthquake studies showthat many buildings with flats have performed poorly. The
flat-slab structural system is significantly more flexible forlateral loads then traditional RC frame system and thatmake the system more vulnerable under seismic events.
This is mainly due to inadequate resistance for punching
shear under the earthquake loading. Unfortunately, manyof upcoming cities are in high seismic zones and need tounderstand the seismic behaviour of the flat slab buildings.
To understand the seismic behaviour of flat slab building,
three model of three dimensional i.e G+3, G+7, and G+11
multistoried building having a flat slab without drop, flatslab with drop, flat slab with perimeter beam, flat slab
with drop and perimeter beam and the conventional slab isconsidered and analyzed using ETABS software. The
performance and behaviour of all the models in IS code
seismic zone-II, zone III and zone-IV have been studied.
The main objective of the present work is to compare thebehaviour of multi-storey buildings having conventional
RC frame and flat slab with different cases and also study
the effect of the height of building. Linear dynamic
analysis for different earthquake ground motion is carriedout and compare with response spectrum analysis.

Keywords: Flat Slab, Conventional frame, ETABs,
Seismic zones, Linear dynamic analysis, Earthquake
ground motions
INTRODUCTION
The flat slab is a reinforced concrete slab supported bycolumns with, or without drops. The columns may be
with, or without, column heads. These buildings are more
popular in the multistoried building because of the absenceof deep beams, and story height can be reduced, use of76

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 45

of low, medium and high rise buildings. Unfortunately,
many of upcoming cities are in high seismic zones andneed to understand the seismic behaviour of the flat slabbuildings. This paper study the comparison of the seismic
performance of low, mid and high rise flat slab with andwithout a drop, and perimeter beam over the conventional
RC storey building for different seismic zones i.e Zone-II,
III and IV. The analysis and design are carried out innumerical software. Dynamic responses of different
models of buildings are carried out for different
earthquakes ground motion.

Zone
Zone factor (Z)Response reduction factor (R)Importance factor (the I)
Soil type
Da amping ratio

II, III & IV
0.1, 0.16 and 0.24
3
1
2
0.05

Table.2 Earthquake Details
Name ofYear
earthquake

Magnitude(Mw)

Bthe huj
ELcentro
Uttarkashi
ChambaChamoli

BUILDING MODELINGIn this paper, five building models with varying height i.elow (G+3), Medium (G+7) and High rise (G+11) buildings
are considered to understand the seismic behaviour of flatslab building over conventional RC Frame Building; themodel-1 consist of conventional frame (CF), Model-2 isflat slab without drop (FS), Model-3 is flat slab with drop(FSD), Model-4 is flat slab with perimeter beam (FSB)
and Model-5 is flat slab with drop and perimeter beam
(FSDB). The symmetrical plan of building with plan sizeof 12m x 15 m and three bays in both x and y-direction
chosen as sown in figure1(a) and. In total fifteen model
were considered for this study and geometry, material
property and loads are listed in the table.1 The analysis
and design are carried out for gravity loads by using
ETABs commercial Software and support are assumed asa fixed base. Drop panel size and drop thickness decide
based on IS 456 -2000. For Linear dynamic analysis fivedifferent earthquake ground motion data chosen based on
tectonic region i.e Bhuj (Gujarat), ElCentro (Imperial
Valley), Chamoli ( Uttarakhand ), Uttarkashi (Garhwal),
Chamba (Himachal Pradesh) and details are shown intable.2.
Table.1: Building details
Geometry Properties
Plan dimensions
12m x 15m
No. of storey
G+3, G+7 and G+11Storey Height
3.6m
Thickness of slab
200mm
Drop size
1.5m x 1.5m
Drop thickness
250mm
Material properties
Grade of concrete
M 25
Grade of steel
Fe 415The density of reinforced
25 kN/m3
concrete
Size of column
450mm x 450mm
Size of beam
300mm x 300mm
Loads
As per IS875-Part-2
Live load
3 KN/m2
Seismic Loads
As per IS 1893-2002

26 January 2001
18 May 1940
19 October 1991
24 March 1995
29 an March,
1999.

7.7
6.9
6.8
5.1
6.8

Time
Interval
(Sec)
0.005
0.02
0.02
0.02
0.02

(a)

(b)

(c)
Figure 1: Building details (a) Plan of Building, Threedimensional view of (b) conventional RC frame with G+3,
G+7, and G+11 buildings the nd (b) Flat slab frame with
G+3, G+7, and G+11 buildings.
RESULTS AND DISCUSSIONS
The main objective of the study is to understand theseismic performance of flat slab building and its
77

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 45

performance compared with RC conventional building.
The analyses and design are carried out using ETABs
software version 2016. Firstly model analysis is carriedout for total twelve building model i.e G+3, G+7 andG+11. The time period and frequency of G+3, G+7 &G+11 building as shown in the table.3, table.4 and table.5
respectively and mode shapes of the G+3 conventionalbuilding shown in Figure.2 . The first mode indicates thenatural frequency of building and all models of modes
time period shown in table.2. In all models, as mode
number increases frequency is also increasing till the 12
modes. After three mode shapes, there is a sudden
decrement in the time period up to 40 % and sudden
increment in frequency as similar to the time period.
Similar results were observed in G+7 and G+11 Buildings.
From the model analysis, it shows that more time period in
the flat slab and less in conventional building and order ofnatural period will increase model-1, model-5, model4,model-3 and model-2 but model-1 time period very closemodel-5 time period. It is observed that time period of theflat slab with drop and perimeter beam is very close toconventional RC building and which gives stiffer than aflat slab with and without a drop. In similar observation
found in G+7 and G+11. For G+3 RC Building, themaximum time period is in flat slab i.e 0.925 sec andminimum is in conventional building 0.719 sec and flatslab with drop and perimeter beam is 0.739 sec. In case of
G+7 RC Building, the maximum time period is in flat slab
i.e 2.0 sec and minimum is in conventional building 1.497
sec and flat slab with drop and perimeter beam is 1.55sec.
Similarly G+11 building, maximum time period is in flatslab i.e 3.15 sec and minimum is in conventional building
2.29 sec and flat slab with drop and perimeter beam is
2.38sec respectively. Time period obtained from IS 18932016 for a moment resisting frame building without brick
infill panels is 0.55 sec, 0.932sec and 1.26 sec for G+3,
G+7 and G+11 storey building respectively. These values
are lesser than the time period obtained from a numericalmethod for all models. It concludes that time period of theflat slab with drop and perimeter beam very close to theconventional building and also similar observation foundas low, mid and high rise building. After model analysis,
response spectrum analysis is carried out for twelve
models and obtained base shear, storey shear, storey
displacement and storey drift for different seismic zones
i.e Zone-II, III & IV using the numerical software andzone factors values are taken from IS 1893-2016. Resultsof Base shear, storey shear, storey displacement, storey
drift is shown in Figure.3 to 6. Results shows that asstorey increase the base shear increase and zone increase
base shear also increases as shown in Figure.3. The
maximum base shear is observed in the conventionalframe (CF) and the minimum is in flat slab without a drop(FS) of G+3, G+7 and G+11 building model. Base shear offlat slab without drop building is reducing by fifteen
percentage of conventional frame building and flat slab
with drop and perimeter beam (FSDB) is reduced by sevenpercentage of conventional frame building for G+3, G+7
and G+11 building model and varying seismic zones. For
G+3 Building, base shear of zone-III and IV are 1.6 and2.4 times of base shear of zone-II. Similar observation
found in G+7 and G+11 storey building. All Building
models i.e G+3, G+7 and G+11 flat slab with drop andperimeter beam of base shear very close to theconventional building and followed by a flat slab with thedrop.
Table.3: Mode Number with respective time period andfrequency of G+3Building.

Table.4: Mode Number with respective time period andfrequency of G+7 Building.

Table .5: Mode Number with respective time period andfrequency of G+11 Building.

Storey shear, storey displacement and storey drift asshown in figure.4, 5 and 6. Sudden increasing storey shear
at below the top floor level for G+3 and as well othermodels, and rest floors increases gradually. Maximum
storey shear in Conventional frame building and minimum78

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 45

in flat slab buildings and FSDB storey shear close to CF
building for G+3, G+7 and G+11. Storey displacement
results shows that as storey increasing, storey
displacement increasing and maximum storey

displacement in flat slab and minimum in Conventionalframe building observed and similar observation in G+7
and G+11 buildings. However in all three zones, zone IIshows less and zone IV showing more results in terms ofbase shear, story displacement, story drift, story shear

Figure.5: Storey drift of G+3 Building with zone-II.

ZONE IIIZONE IV

CF
FS
FSD
FSB
FSDB

ZONE II

CF
FS
FSD
FSB
FSDB

600
500
400
300
200
100
0

CF
FS
FSD
FSB
FSDB

Base shear (kN)

Figure.2: Mode shapes of G+3 conventional building

4 STORY

8 STORY

12 STORY

Building models
Figure.3 : Base shear of buildings models with different
seismic zones.
Figure.6: (a) Maximum displacement of building models
with different seismic zones (b) Maximum drift ofbuilding models with different seismic zones
Linear dynamic analysis
To understand the dynamic behaviour of the buildings,
five major earthquake ground motions of Elcentro,
Uttarakashi, Chamba, Bhuj and Chamoli have been
considered, which are different in their nature of
predominant frequencies. Dynamic linear Analysis isgiven basic idea of the understanding the behaviour of fat
slab building under the action of earthquake groundmotion. In this displacement time history measure at roof
level for all models and results are presented in table 6 andFigure.7(a) is Elcentro ground motion and Figure.7(b) islinear dynamic response at roof level of conventional andflat slab building. When observe the results obtained fromtime history analysis for all 5 models in all three cases (i.e.
G+3, G+7 and G+11 story. Model 1 (4 story conventionalframe) shows less displacement than model 2 (4 story flat

Figure.4 : (a) Storey shear and (b) Storey displacement of
G+3 Building of zone-II.

79

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 45slab). By providing of drop, perimeter beam to the flat slab
(i.e. model 3, model 4, model 5), the displacements are
reduced and this thee models model 5 (flat slab with drop
and perimeter beam) showing less displacement for all
five earthquake data consideration. The flat slab showing
more displacement than all other models. When compare
the flat slab with conventional frame, conventional frame
showing less displacement and when providing drop,
perimeter beam to the flat slab, flat slab with drop andperimeter beam combination showing less displacement
than flat slab. Linear resposnce of individual building
varying ground motion to ground motion.

building to flat slab building and also major earthuake
occurred in india. A compare the response spectrum
results with the linear time history results, Only Chamba
earthquake data shows similar behavior in terms of
response in all five models in all cases. And whencompare the all five earthquake data’s response for allmodels Chamba earthquake data is only giving lessresponse to the structure. In seismic point of view, forconstruction of flat slab structure, flat slab with drop andperimeter beam combination is gives better results. From
results it can concluded that flat slab with drop andperimeter beam showing better results in terms of story
displacement and story drift. So, to avoid seismic failures,
flat slab with drop and perimeter beam are best. When
compare to flat slab without drop and flat slab with drop,
flat slab with drop and perimeter beam is more resistinglateral forces
REFERENCES[1] D.N.Shinde et.al (2016), “Comparative study ofseismic response of flat slab structure and conventional
RC framed structure”, (International Journal of innovativeand emerging research in engineering) volume 3, issue 6,June, 2016.
[2] G. Patwari and G. Kalurkar (2016), “Comparative
study of RC flat slab & shear wall with conventionalframed structure in high rise building”, International
Journal of engineering and research (IJER), volume no.5
issue: special 3, pp. 612-616, 28 Feb. 2016.
[3] N.mircic, R. P. Apostolska (2008), “Seismic
performance of flat-slab building structural systems”.
(14thworld conference on earthquake engineering, Beijing,
China)October 12, 2008.
[4] Francisco Galvis, Eduardo Miranda, Pablo Heresi,
Héctor Dávalos and José Ramón Silos, Preliminary
Statistics of Collapsed Buildings in Mexico City in the
September 19, 2017 Puebla-Morelos Earthquake[5] Bolton, P.A., ed., 1993, The Loma Prieta, California,
Earthquake of October 17, 1989—Public response: U.S.
Geological Survey Professional Paper 1553-B, 69 p.1994.
[6] Preliminary Reconnaissance Report (Earthquake
Engineering Research Institute, Oakland, CA, 1994)[7]. Northridge Earthquake Archived 2004-09-04 at
the Wayback Machine. Southern California Earthquake
Data Center. Retrieved October 6, 2006.
[8] IS 1893 (Part 1) 2002, “Criteria for Earthquake
Resistant Design of Structure,” BIS 2002.
[9] IS 456:2000, “Code of practice for plain and reinforced
concrete”, code practice fourth revision, Bureau of IndianStandards, New Delhi, July 2000.
[10] IS 875 (part 2) – 1987, “Code of practice for Design
loads (other than earthquake)for buildings and structures”,
second revision, June 1998.

Figure.7:(a) Elcentro ground motion and (b) Roof
displacement response of G+3 CF and FS building.
Table 6: Linear displacement response of top storey(mm) for different earthquakes.
S

M
EC
UK
CM
BJ
CL
CF
5.81
6.35
5.39
5.47
6.36
FS
9.28
7.92
7.88
8.08
9.39
FSD
8.06
7.00
6.32
7.37
8.24
4
FSB
7.15
7.10
6.17
6.72
7.25
FSBD
6.87
6.91
5.92
5.98
6.45
CF
12.08
11.1
10.80
18.26
13.82
FS
23.26
17.45
11.15
34.61
21.70
FSD
18.68
14.79
8.77
17.15
19.47
8
FSB
16.95
14.06
9.42
16.88
18.77
FSBD
15.14
13.15
9.082
16.29
16.85
CF
21.33
24.82
17.12
24.60
22.98
FS
43.16
19.45
16.84
47.76
40.68
FSD
39.05
19.05
13.25
28.28
37.67
12
FSB
31.94
20.37
14.76
22.23
35.19
FSBD
27.70
21.95
16.07
20.99
28.94
Note :S-storey, EC-Elcentro, UK-Uttarakashi, CM-Chamba, BJ-Bhuj,
CL-Chamoli

CONCLUSIONS
Flat slab building more attract very recent time in urban
centres due to industrial and infrastructure development.
But recent earthquake, flat slab building shows poor
performance. These building need to understand indepth
analysis and design aspect in seismic forces. In this paper,
we compare the seimic perofrmnace of conventional80

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 52

SEISMIC PERFORMANCE ASSESSMENT OF BUILDINGS LOCATED ON A SLOPINGGROUNDPRADEEP KUMAR PANDRE1, SHREYASVI C2, and KATTA VENKATARAMANA3
1

Former M. Tech Student, Department of Civil Engineering, National Institute of Technology Karnataka, Surathkal,
Mangalore, India, pradeep.pandre@gmail.com
2

Research Scholar, Department. of Civil Engineering, National Institute of Technology Karnataka, Surathkal,
Mangalore, India, shreyasvic@gmail.com (corresponding author)
3

Professor of Civil Engineering, Department. of Civil Engineering, National Institute of Technology Karnataka,
Surathkal, Mangalore, India, ven.nitk@gmail.com
Keywords: Set back building, Step back – Set back building,and base shear. Site-specific response spectrum
obtained from the seismic hazard analysis of theMangalore region [2] is considered for the analysis andthe same has been shown in Fig.4

1. GENERAL INTRODUCTION
The present work comprises of two sets of buildings
namely step back (SB) and step back set back (SB-SB)
buildings resting on the sloping ground. The different
sloping angles considered here are 20˚, 25˚and 30°. The
elevation of different sets of models with a standard
storey height of 3m and bay width of 4m is shown in
Fig. 1-3.

Intensity (g)

0.25
0.2
0.15
0.1
0.05
0
0.3
0.6
0.9
1.2
1.5
1.8
2.1
2.4
2.7
3
3.3
3.6
3.9

0

Time (sec)Fig.1 20˚ Step Back and Step Back-Set Back Building

Fig.4 Site-specific response spectrum of Mangalore
2.1 Natural Period and Base Shear
The natural period of the building decreases with theincrease in the slope of the building for both the cases.
When compared between step back and step back-set
back buildings resting on the same sloping ground, step
back-set back buildings turns out to have a smaller
natural period.
Table 1 Natural period and base shear

Fig.2 25˚ Step Back and Step Back-Set Back Building

Natural Period (sec)
Slope ↓

Fig.3 30˚ Step Back and Step Back-Set Back Building

Base Shear (kN)

SB-SB
0.464

SB

SB-SB

20°

SB
0.59

3052

2575

25°

0.52

0.38

3013

2351

30°

0.5

0.322

2798

2019

2. RESPONSE SPECTRUM RESULTS

2.2 Storey Displacement

The response of the structure is considered in the formof the natural period, mode shapes, storey displacement,

The top storey displacement decreases with the increasein the sloping angle for both the building types

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 52
considered in the study. Similarly, between step backand step back-set back buildings, the latter performs
well with comparatively lesser top storey displacement.

can withstand lesser deformation when compared to thestep back – set back buildings. In addition, the latter canaccommodate higher base shear when compared to theformer.

Table 2 Storey Displacement

Storey
Base
1st
2nd
3rd
4th
5th
6th

20°
0.00
0.07
0.52
2.74
6.70
9.96
11.85

25°
0.00
0.02
0.48
1.64
4.99
8.37
10.43

30°
0.00
0.46
0.17
1.71
4.63
7.52
9.48

20000

Step back-set
back buildings
20° 25° 30°
0.00 0.00 0.00
0.07 0.01 0.32
0.42 0.57 0.11
1.64 0.90 0.93
3.81 2.32 2.31
7.00 4.39 3.68
8.89 6.27 4.90

Base Shear (kN)

Step back buildings

15000
10000
5000
0

-0.2

0

0.2

0.4

0.6

Displacement (m)2.3 Mode Shapes
The first and second mode is significant in translationalmotion in X and Y direction [1]. However, significant
torsion was observed in higher modes and the same has
been presented in Fig. 5.

Fig.6 Base shear v/s roof displacement
4. CONCLUSION
The assessment of 2 building configurations i.e. stepback(SB) and step back set back building (SB-SB)
resting on 3 different sloping angles (20°, 25°, and 30°)
were analyzed. The following observations were madefrom the study.
(a) SB Mode-10(b) SB-SB Mode-10

Fig.5 Mode shape of a step back and a step back-set
back building on 20° sloping groundThe storey displacements in both the building
models are almost same in the lower storeys.
However, with the increase in the storey heightthe difference seems to double and SB-SB
shows lesser displacement.
The SB-SB can accommodate large inelastic
deformation when compared to SB.

Based on these observations it can be inferred that SBSB building configuration performs better (ductile
behaviour) on a sloping ground than SB.

3. PUSHOVER ANALYSISREFERENCES

3.1 Hinges Formation[1]Ghosh, R., & Debbarma, R. (2017). “Performance
evaluation of setback buildings with open ground storey
on plain and sloping ground under earthquake loadings
and mitigation of failure,” International Journal ofAdvanced Structural Engineering, 9(2), 97-110

Hinges assigned to various structural members serve as
an indicator for assessing the performance level of achosen element. Since the size of the column at the
ground level varies with the sloping angle, short column
effect comes into play. These short columns attract
more earthquake forces, as a result, the sequence of
hinge formation begins from the columns in the lower
storey.

[2] Shreyasvi C. & Katta Venkataramana (2017).
“Quantification of seismic hazard for Mangaloreregion”, Indian Geotechnical Conference – 2017, IIT
Guwahatti. (TH-12, no. 502)

3.2 Base Shear v/s Displacement
The behavior of both the building configurations interms of base shear indicated that the step back buildings

82

0.8

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 74

DEVELOPMENT OF CRACK DETECTION SYSTEM FOR IMAGE VISUAL INSPECTION
WITH AI USING SUPER HIGH RESOLUTION CAMERA
Takahiro MINAMI1, Makoto FUJIU2 , Junichi TAKAYAMA3 , Tomotaka FUKUOKA4
Shinya SUDA5, Shuya OKUMURA6 and Kazuo WATANABE7
1Master (Eng), Kanazawa university, Dept. of Environmental Design, taketaka0503@stu.kanazawa-u.ac.jp
Ph.D., Assistant Professor, Kanazawa university, Geosciences and civil Engineering, fujiu@se.kanazawa-u.ac.jp
3Dr., Eng., Professor, Kanazawa university, Geosciences and civil Engineering, takayama@staff.kanazawa-u.ac.jp
4Dr., Informatics, Kanazawa university, Geosciences and civil Engineering, fukuoka@se.kanazawa-u.ac.jp
5WorldLink&Company Co., Ltd SkyLink Japan, s.suda@skylinkjapan.com
6
WorldLink&Company Co., Ltd SkyLink Japan, s.okumura@skylinkjapan.com
7Dr., Agri, Affiliated Assistant Professor, Kyoto university, Environmental Coexistence, isseiw@cseas.kyoto-u.ac.jp
2

Keywords: bridge inspection, diagnostic imaging technology, automatic crack detection
1. INTRODUCTION
In Japan, there are about 730,000 bridges with a lengthof 2 m or longer, and many of these were built during aperiod of high economic growth. Parts that were repaired
during emergencies and bridges placed in harshenvironments age notably. Under these circumstances,
there is a shift from breakdown maintenance that
attempts countermeasures after major damage occurs, topreventive maintenance that extends the healthy lifespanof bridges by taking countermeasures while the damageis mild. To take preventive countermeasures, bridges
must be inspected and diagnosed routinely, and thehealth condition of bridges must be well understood. In
2014, with a comprehensive standard stipulated by thefederal government, the close visual inspection of all
bridges by road maintenance staff was required every
five years.
As issues with the continuing close visual inspectionof bridges are surfacing, the remote imaging system is
expected to become a new inspection method that
replaces close visual inspection. This has led to a large
number of studies [1] [2] [3] [4]. In this study, we
propose a new inspection method to replace the current
close visual inspection. Using images of an entire pierwith 100 million pixels taken with a super-highresolution camera (SHRC), and an inspection
environment similar to that of on-site close visualinspections by human inspectors was created.

Figure. 1: Cracks photographed with SHRC
in; thus, cracks and corrosion of steel reinforcement canbe confirmed.
Using a 52-inch 4K-resolution monitor and designatedsoftware, we created a setting where the entire image ofthe pier, captured with the SHRC, can be observed.
Brightness, saturation, and contrast can be adjusted, andone can smoothly zoom in and out of the image. In thisstudy, we used A0 paper with the entire pier printed as
the media to record the diagnostic results of cracks.
In the diagnostic experimental environment, two staff
with civil engineering degrees but without inspection
experience visually detected cracks in the image of theentire pier.
We performed a diagnostic experiment to determine if
experienced inspectors can identify cracks in the image.
The experienced bridge inspectors were Mr. A (Hakui
City staff) and Mr. B (Ph.D. in engineering, technician inconstruction department/steel structures and concrete,concrete diagnostician); the inspectors zoomed in and outof the photograph of the pier on a display monitor.
We interviewed the diagnosticians about the diagnostic
potential of the images. Their opinions were that they
were able to detect cracks in a similar manner as a close
visual inspection. If we can incorporate this method in an
actual inspection, there is further utility in that theinspection cost can be reduced, and diagnostic results can

2. DIAGNOSTIC EXPERIMENT USING IMAGE
WITH 100 MILLION PIXELSThe target bridge was a double-span steel-weldedbridge with I-beams having a length of 41.30 m and total
width of 4.70 m in Hakui City, Ishikawa Prefecture.
Fig.1 shows cracked and corroded steel reinforcementof the pier photographed from 12.5 m away with theSHRC. Areas marked with red dotted lines indicate
cracks and corrosion of steel reinforcement. Althoughcracks cannot be confirmed in the entire image of thepier, by zooming in, cracks and corrosion of steel
reinforcement can be clearly confirmed. About 0.1mm
cracks could be visually confirmed. Images taken with
the SHRC do not have poor pixel quality when zoomed83

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 74

become more objective. However, there are some resultsthat are difficult to identify regarding whether they aremarks from construction formwork or cracks, and thereis damage that is difficult to diagnose with images alone.
Each detection result detected the lateral crack at thecenter of the pier. The detected positions of the cracks
were mostly the same. However, depending on the
diagnostician, the detection results had slight differences.
The reason for this was the participants’ experience withbridge inspection.

Table 1: Precision of AI crack identification

3. EXAMINATION OF PRECISION FOR CRACKIDENTIFYING AI
In this chapter, we aim to formulate AI that
automatically detects locations of cracks from 100million-pixel images. To formulate AI that is able toidentify cracks by understanding the feature values ofimages that contain cracks, we used the image
recognition service [5]. This allows for the creation of animage recognition engine without an image recognition
logic by tagging uploaded images and formulating AI.
Using a 100-million-pixel image in which cracks wereidentified by experienced bridge inspectors, areas withcracks and without cracks were cut out separately (about
80.9 KB per image) and were used as teaching data.
Images that included the areas of cracks were tagged as“with cracks” and “concrete,” and images without cracks
were tagged “concrete” for learning. In some cases,
images contained grass; therefore, we added the tag“grass.” There were 48 images tagged with “cracks,” 82
images tagged with “concrete,” and 14 images taggedwith “grass,” which were used as teaching data. In thismanner, a crack-diagnosing AI was created.
A post-learning evaluation was performed with two
indexes: precision that how well images were classified,and recall that expressed the number of images that were
accurately identified among all images that should havebeen accurately identified. Table 1 shows a post-learning
evaluation of the AI.
Using the AI to identify cracks, we diagnosed if each
image divided by the mesh contained cracks. The
diagnostic results were evaluated with probability whichis calculated by AI. The probability of cracks containedin the image input in AI, probability of containing
concrete, and probability of containing grass were output.
In this study, we only considered cracks and set a
threshold for convenience. If the probability of cracks
was less than 30%, it was labeled a “low probability ofcrack formation,” 30 to 60% was “moderate probabilityof crack formation,” and 60% or higher was “highprobability of crack formation.” The crack diagnostic
results by AI are shown in Fig.2. For locations that wereidentified to have cracks by humans using the image, theAI often identified these locations as “high probability ofcrack formation.” The AI often identified locations where
cracks could not be visually confirmed as “lowprobability of crack formation.” This indicated that the
automatic detection of locations with cracks by AI may
be possible.

Figure 2: Diagnostic results of cracks by AI
However, areas without visual confirmation of cracks
were misdiagnosed as “moderate to high probability ofcrack formation” if there were boundaries of shadowsand marks of formwork. This was likely owing to a
problem with the teaching data that were used when the
AI was being prepared. An increase or improvement of
the teaching data is necessary.
4. CONCLUSIONS
Using the images taken with a SHRC, we performed adiagnostic experiment on the cracks and verified the
diagnostic potential of the images. As a result, although
there were some crack detection errors between
diagnosticians, the detection results of cracks were
mostly similar.
We prepared an AI that identifies cracks in images
based on the diagnostic results of the cracks. An
examination of the AI’s precision showed that cracks
were identified to a certain degree, indicating thatlocations of cracks may be automatically delineated froman image with 100 million pixels.
REFERENCES[1] Nishimura S, Kimoto K, Matsuoka N, Otani H, Ogata
T, Matsuda H (2013) “The development and evaluationof telemetry in bridge maintenance” J Appl Surv Technol
Vol.24, pp52-61[2] Koch C, Paal S, Rashidi A, Zhu A, König M. Brilakis
I (2014) “Achievements and challenges in machine
vision-based inspection of large concrete structures”
Adv Struct Eng Vol.17, pp303-318[3] Yeum CM, Dyke SJ (2015) Vision-based automatedcrack detection for bridge inspection. Computer-Aided
Civil Infrastruct Eng Vol.30, pp759–70[4] Sinha K, Fieguth PW, Polak, MA (2003) Computer
vision techniques for automatic structural assessment ofunderground pipes. Computer-Aided Civil Infrastruct
Eng Vol.18 pp95–112[5] Custom Vision Service - Microsoft Azure,https://docs.microsoft.com/ja-jp/azure/cognitiveservices/custom-vision-service/ Accessed 2017.12,1784

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 28

USE OF EXISTING COMPONENTS OF STRUCTURE AS TUNED MASS DAMPERO R JAISWAL1 and VIKAS M THAKUR 2
1

Professor, Dept. of Applied Mechanics, VNIT, Nagpur, India, orjaiswal@apm.vnit.ac.in
Asst. Professor, Civil Engg. Dept, JDCOEM, Nagpur, India, vikasmsthakur@gmail.com (corresponding author)

2

Keywords: Tuned Mass Damper, optimum parameters of TMD, Existing component as TMD
1. INTRODUCTION
Mega cities face variety of challenges like, urban
industrial safety, urban traffic safety, waste treatment anddisposal problems, safety against natural calamities likehurricanes, floods, earthquakes, tsunamis etc. This article
deals with safety of civil engineering structures against
earthquake and wind loads. An extreme wind event or anearthquake can severely damage civil engineering
structures like buildings, bridges, towers, chimneys,
water tanks etc. Safety of structures against these loads isessential.
Structural designers have since long used vibration
control techniques to control vibrations of civilengineering structures under wind and earthquake loads.
Vibration control techniques are broadly classified infour types namely: Passive control, Active control, Semiactive control and Hybrid control. Passive control
devices in the form of an additional fixture like viscousdampers, elasto-plastic dampers, and friction dampers
have been used in many applications. Tuned massdampers (TMDs) have been proposed and discussed
since last 120 years. In last so many years, the theory of
TMD has been well-developed and experimented and it
is brought to technological level. Since 1970s, it is being
used in buildings and other civil engineering structures
for controlling the wind and seismic response. Use of
TMD requires deployment of additional mass, stiffnessand damper. In recent past, researchers and engineers
have attempted to use existing components of structures
as TMD. This avoids deployment of additional devices.
This approach is quite attractive, since it eliminates therequirement of any additional mass and also, since theexisting part is used, there are no additional maintenancerequirements. While using the existing components, one
has to suitably provide the required stiffness and explore
the possibility of providing additional damping. Further,
depending on the damping available for this existing
component, one can suitably tune the TMD frequency.
Six such applications, wherein existing components are
deployed as TMD are reviewed in this paper. Further,based on research performed at VNIT Nagpur India, useof existing component as TMD is proposed for elevatedwater tanks and for RC chimneys.

supported on 28 rolling pendulum bearings which
provide the required stiffness (Figure 1). These bearings
rest on low load bearing RC floor which is also used formaintenance of bearings. This roof garden has mass
which is 5.8% of building mass and with respect to 1st
modal mass, TMD has almost 17% mass. The optimum
frequency ratio is 0.39. Optimum damping ratio is 0.465
which is achieved with the help of viscous dampers
which are located with each bearing (Figure 1). Througha numerical simulation it is shown that such a TMD
leads to 45% reduction in peak displacement and around
23% reduction in peak acceleration of main building.
Rolling pendulum bearing deployed in this application isrobust since there will be no permanent displacement,
and TMD (roof garden) regains its original position after
vibrations.

Figure 1. Roof-garden TMD in Portasiena Linear
Building, Siena, Italy [1]Next application is described by Kidokoro [2]regarding Swatch group’s building, Nicolas G. Hayek
Center. This is a 14 story building constructed on 2007 in
Tokyo, Japan installed with TMD derived from floorslabs at various levels of building. The floor slabs aremounted on slider and rubber bearings on the corbel
extending from columns of main structure (Figure 2 and
3). The plan dimension of building is 12.6m x 31.2m.
The TMD system is implemented by disconnecting slabs
of four upper floors (9th, 10th, 12th and 13th floor) fromthe main structure (Figure 4). All four floors together
have mass 10% of building mass. Through non-linear
time history analysis it is shown that this TMD leads to
37% reduction in seismic forces.

2. REVIEW ON EXISTING STRUCTURES
WHERE COMPONENTS ARE USED AS TMD
Matta and De-Stefano [1] have reported use of roof
garden mass as TMD for a 6 story Portasiena Linear
building at Siena, Italy. The plan dimension of building
is 26m x 42m. The roof garden is created on a RC slab

85

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 28
Nagase and Hisatoku [3] have shared details of ice
thermal storage tanks used as TMD in 37 story Crystal
Tower office building, completed in 1990 at Osaka,
Japan. The tanks are suspended with cables from frame
girder at the roof (Figure 5). The weight of each tank is
90 tonnes and four such tanks are placed in larger
dimension of building and two tanks are placed in shorter
plan dimension. The mass ratio of damper to effective
mass of building in longer direction is 2.5% and in
shorter direction it is 1.3%. The length of cable is kept
variable between 3.5m and 4.5m in longer plan direction
and between 3m and 4m in shorter plan direction. Oildampers are provided to absorb tank swinging motion
and to damp the building sway motions. The damping
ratios are chosen more than the optimum values. The
damping ratio in longer direction is 0.12 and it is 0.09 in
shorter direction. The wind tunnel test and modal
analysis have shown that this damper can reduce windinduced motions by 50%. After deployment of TMD thisbuilding has witnessed two extreme loading events. One
is Typhoon 9019 on 19th September 1990. During thisevent, dynamic response is recorded. Then, throughnumerical simulation, it is shown that recorded response
is 50% less than the response without this TMD. The
Second event witnessed by this building is earthquake of
24th September 1990. Again through numericalsimulation it is shown that due to presence of TMD,
seismic response has decayed rapidly.

Figure (2a) Section view of Rubber bearings [2]Figure (2b) Section view of Slider bearings [2]Figure 3. Plan view of TMD floor [2]SMD systems located at
9, 10, 12, and 13

Retail floors hung from above
to create atrium space

Figure 5. Ice storage tanks as pendulum type TMD [3]Tadashi [4] has shown details of ice thermal storagetank TMD in 31-story Proctor & Gamble Japan
headquarters, constructed near Kobe in 1993. Here also
like in crystal tower, ice thermal storage tanks hanging
from rooftop was used as TMD mass (Figure 6). Massratio was 1% and each tanks weighs 90 tonnes. Dampers
were principally designed to protect structure fromstrong wind motions.
The 36-story Sea Hawk Hotel completed in 1995 andlocated in Fukuoka, Japan was fitted in with thependulum type TMD. Here water tank of weight 132

Figure 4. TMD at Nicolas G. Hayek Center, Tokyo,
Japan [2].

86

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 28
tonnes is used as mass damper. Dampers are designed toreduce the torsional vibrations of building due to the
maximum wind speed of 86 Kmph [4].

3. RESEARCH WORK AT VNIT ON USE OF
EXISTING COMPONENT AS TMD
In recent past, under two sponsored R & D projects at
VNIT, Nagpur attempts have been made to use existing
components of structure as TMD. This has been
attempted for two structures, i.e. elevated water tank withframe staging and tall RC chimney. In the case ofelevated water tank on frame staging, the TMD isderived from roof slab and columns inside the container[6]. Here, roof slab is laterally detached from wall
(Figure 8). Thus roof slab with column inside thecontainer acts as TMD. For an elevated water tank of 350
m3 and staging height of 12m, it is shown that such TMD
leads to about 20% reduction in base shear. This TMD is
not yet implemented nor has any experimental
verification been done.
In the case of tall RC chimney, the maintenanceplatform is used as TMD. In the tall RC chimney,
maintenance platforms are provided at regular intervals
along the height. One such platform at the top level wasused as TMD (Figure 9a and 9b). For this purpose it was
proposed that bearing will be inserted at the support ofthe platform. This mass of platform acts as TMD mass,and the stiffness and damping is provided by bearings.
The effect of such a TMD was studied for along-windand across-wind response. A 273 m tall RC chimney wasconsidered and the top most platform was converted into
TMD with mass ratio of about 1% and TMD damping istaken as 5%. It is shown that such TMD leads to about
25% reduction in base shear. Thus, for tall RC chimneys,use of maintenance platform as TMD offers a good
option to suppress along-wind and across-wind response[7].

Figure 6. Conceptual model of Building with pendulum
type TMD [4]Hoang et al. [5] proposed retrofit scheme in the formof TMD for Minato bridge in Osaka, Japan. Span ofbridge is 510m. Old existing bearings of the bridge were
replaced by a new floor deck-isolation system (Figure 7).
Floor deck-isolation system comprise of sliding bearings
and rubber bearings. Damping is achieved with the helpof sliding bearings which act as linear viscous damperand rubber springs increases period of bridge and act aselastic spring. Floor decks and isolation system together
form a large mass TMD, making mass ratio 77%. In theprocess of design of TMD, a 3-D Finite element model
was made and Kanai-Tazimi spectrum was used to model
earthquake. The optimally designed TMD based on
Kanai-Tazimi spectrum were shown effective for groundmotion time histories of similar frequency content.

Figure 7a. Floor deck-isolation system of Minato Bridge
in Osaka, Japan [5].

Figure 8. Proposed TMD for elevated water tank [6]Figure 7b. Longitudinal view of Minato Bridge in Osaka,
Japan [5].

87

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 28
for experimental verification of such TMDs for elevatedwater tank and RC chimney.
REFERENCES[1] E. Matta and A. De Stefano, (2009) “Seismic
performance of pendulum and translational roof- garden
TMDs,” Mechanical Systems and Signal Processing,23(3), 908-921.
[2] R. Kidokoro. “Self Mass Damper (SMD): Seismic
control system inspired by the pendulum movement ofan antique clock,” 14th World Conference on Earthquake
Engineering. Beijing, China, 2008.
[3] T. Nagase and T. Hisatoku, (1992) “Tuned-pendulum
mass damper installed in crystal tower,” The structuraldesign of tall buildings, Vol. 1, 35-56.
[4] Nagashe T. “Earthquake records observed in tallbuildings with tuned pendulum mass damper,” 12th
World Conference on Earthquake Engineering.,
Auckland, New Zealand, 2000.
[5] Hoang N, Fujino Y, Warnitchai P, (2008) “Optimal
Tuned Mass Damper for seismic application andpractical design formulas,” Engineering Structures, 30,
707 -715.
[6] Jaiswal OR. “Simple tuned mass damper to control
seismic response of Elevated Tank,” 13th World
Conference on Earthquake Engineering. Vancouver,B.C., Canada, 2004.
[7] K R C Reddy, O R Jaiswal, P N Godbole, (2011)“Wind Response Control of Tall RC Chimneys”, Journalof Wind & Structures, Vol. 8(1), 1-9.

Figure 9a. Geometric details of maintenance platform[7]

Figure. 9b. Details of maintenance platform andelastomeric bearing as TMD [7]4. DISCUSION
Use of TMD is now quite common and has been
implemented in many buildings, bridges and otherstructures. Of late, efforts are made to use existing
components of structure as tuned mass damper. In thisapproach, the damping of TMD is either kept same or
greater than that of the main structure. This approach ofusing existing part of structure as TMD has certain
advantages such as there is no need of deployment ofheavy extra mass and space in structures. This TMD
certainly helps in energy dissipation. Six suchapplications are reviewed in this paper. These
applications are for buildings and bridge. In case ofbuilding [1], roof garden is mounted on bearings to act as
TMD. In other type of application, utility equipments
such as ice thermal storage tanks or water tank aresuspended with cables to act as pendulum type TMD. In
bridge floor deck-isolation system is converted to TMD.
Use of existing part as TMD is not yet outlined forstructures other than buildings and bridges. Under
sponsored R & D projects at VNIT such approach of useof existing components of structure as TMD been carriedout for two structures, i.e. elevated water tank on frame
staging and tall RC chimney. It is shown that such TMD
is effective in reducing dynamic forces. There is a need88

USMCA 2018

SESSION 6
TOOLS AND TECHNIQUES IN
DISASTER MANAGEMENT

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 04

SHEAR CHARACTERISTICS OF VERY LOOSE VOLCANIC SOIL CAUSING SLOPE DISASTER
Itsuki Sato1andReiko Kuwano2
1
2

Master Student, The Universty of Tokyo,Institute of Industrial Science, Tokyo, Japan,i-sato@iis.u-tokyo.ac.jp
Professor, The Universty of Tokyo,Institute of Industrial Science, Tokyo, Japan, kuwano@iis.u-tokyo.ac.jp

Keywords: Volcanic soil, Cementation, Particle crushing, Landslide, Slope disaster
1. INTRODUCTION
Soil having a high void structure derived fromvolcanoes is distributed widely in various places in Japan,
and it caused some slope disasters in the past (Table 1).
The past large-scale slope disasters include Ontake landslide with a slack surface of loose pumice stone layer
caused by the 1984 WesternNagano Prefectureearthquake, gentle slope disaster caused by the pumicelayer of Minamiaso village due to the 2016 Kumamoto
earthquake (Figure 1), slope disaster of Izu Oshima
where the slope that had been evaluated as safe in thehazard map collapsed due to the torrential rain caused byatyphoon, the case of the 2008 Iwate-Miyagi Nairiku
earthquake where sediment flowed over a long distanceon a gentle slope with a gradient of 1° to 2° due todeposition of loose non-plastic volcanic ash soil withcementation.In this research, focusing on the fact thatslope disasters such as muddy flow and long-distanceflow are triggered by volcanic pumice layers with highvoid, extremely loose soil with volcanic cementation was
reproduced by adding cement in the laboratory, and its
strength characteristics was investigated by performing
CD tests and CU tests at several confining pressures.

2. SPECIMEN PREPARATION
In general, the micro-structure and fabric of naturally
deposited volcanic soils are neither homogeneous nor
isotropic, and it is hard to collect a sufficient number of
undisturbed samples repeatedly with equivalent quality.
Thus, artificial samples of extremely loose soil were
produced in the laboratory to understandfundamental
behaviorsof such specific soils systematically.
In this study three types ofsamples having cementation
were prepared as follows:(1)mix DL clay, which is non-plastic fine, and ordinary
portlandcement at specificmixture ratios(Table 2).
(2) add specific amount of water (Table 2) and mix itwith the material enough for 2 minutes.
(3)using suction, pour the mixture loosely into a moldwhose diameter is 5cm and height is 10cm to achieve theweight calculated to be the designed void ratio (Table 2).
(4)keep molds in a moist curing box for 7days.
(5) put them in a drying oven for 24 hours.
(6) start experiments immediately after taking samples
from the drying oven.
By followingthis procedure, a lot of specimens having
almost same cementation and density were prepared to
conduct experiments systematically.
Table 3 showsaveraged values of the saturated density(ρs), the dry density (ρd) and the void ratio (e) of eachspecimentype prepared in the laboratory. The loose DL
clay specimen was also prepared for a better comparison
with the three specimen types (namely, A, B, and C),
thatexhibit higher void ratio values than the loose DL
clay. Specimen A is standard (reference) sample, B hasless cementation than A due to smaller amount of cement,
and C has higher void ratio than A.

Table 1: Typical Japanese volcanic soils1),2),3),4),5)
Kanto Loam

Shirasu

MasadoScoriaCementation

Yes

Yes

No

Yes

Crushable

No

Yes

Yes

Yes
Small

Particles
ρ

Small

Small

Small

Maximume

3.38

1.68

1.11

1.23

Viscosity

Large

Small

Small

Non-plastic

Table 2:Contents of artificial specimens
Specimen

Mass ratio
DL clay:Cement:Water

A
B
C

Designed void ratio

85:15:25
90:10:25
85:15:25

2.1
2.1
2.7

Table 3:Material properties of prepared specimens

Figure 1:Landslide at Takanodai of Aso in Kumamoto
earthquake (2016)89

Specimenρs（g/cm3)

ρd（g/cm3)

e

A

2.69

0.89

2.02

B

2.66

0.89

1.99

C

2.69

0.75

2.61

Loose DL clay

2.65

1.03

1.58

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 04
3.RESULTS AND DISCUSSIONS
The volume change duringthe initial consolidation
stage is illustrated in Figure 2. Specimen A shows low
volumetric strain at low confining pressure levels similar
to loose DL clay, but its compressibility changes
suddenly at around 150kPa and increases after thesudden jump. It is hypothesized that cementation
between particles was lost at the pressure level. The
larger compressibility observed afterthe loss of
cementationcompared with loose DL clay implies that
extremely loose structure was ascribed to this highcompressibility. Specimen B also exhibits a sudden jump
due to loss of cementationat around 70kPa followed by asimilar compressibility with specimen A, which had
similar void ratio. As for specimen C, loss of
cementation was not observed, probably because
specimen C had a high void ratio and cementation was
too weak to retain against theinitial back pressure.
CD test results of specimen A are shown inFigure 3.
At confining pressuresof50 and 100kPa,prior to the lossof cementation, a peak strength was observed at a small
strain. After cementation was lost, specimen A showed
greatly loose behavior. At all confining pressures,significant negative dilatancy was observed.

confining pressure levels

Figu
re4:CU test results of specimen A at several confiningpressure levels
Referring to Figure 4for CU test results of specimen A,
in the case of low confining pressures, 50kPa and
100kPa, the specimen type showsa peak strength at a low
axial strain as observed in CD tests. In all cases, thedeviator stress reaches a residual (steady) state when theaxial strain reaches 20%. It is hypothesized that once
extremely loose soil’s cementation is lost, the strain candevelopdramatically in a short time in the field.
4. CONCLUSIONS
Extremely loose soil kept by cementation exhibits
greatly high shear strength and low compressibility when
cementation is kept. However, once cementation is lost,
high compressibility and significant negative dilatancy
can be observed. In undrained compression tests, after
the shear strength reachesits peak and the cementation is
lost, a brittle behavior can be observed in which the shear
strength converges to a residual state.

Figure 2: Volumetric strain during consolidation stage

REFERENCES[1]H. Murata, M. Hyodo, N. Yasufuku: Compressive andshear characteristics of undisturbed decomposed granite
soils paying attention to the degrees of weathering,
Journal of JSCE, 382 / III-7, pp. 131-140, 1987.
[2]O.Kusakabe,Y.
Maeda,M.
Ohuchi,T.Hagiwara:Strength - deformation characteristics of an
undisturbed scoria and effects of sample disturbance:
Journal of JSCE, No. 439 / III - 17, pp. 69 - 78, 1991.
[3] J. Yang, N. Moroto: Shear strength of undisturbed
volcanic cohesive soils undergoing cementation: Journalof JSCE, No. 617 / III-46, 175-189, 1999.
[4]T. Nishioka, S. Shibuya: Engineering Properties ofThree Local Soils and their Engineering Applications:
the Japanese Geotechnical Society, 65-1 (708), 2017.
[5]S. Miura, K. Yagi:Mechanical behavior and particle
crushing of volcanic coarse-grained soils inJapan,Characterization and Engineering Properties of
Natural Soils p 1169 - 1204, 2003.

Figure 3:CD test results of specimen A at several

90

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 24

A STUDY OF PENETRATION RESISTANCE VALUE AT LOOSE AREA UNDER THE CAVITY:EXPANSION PROCESS OF SUB-SURFACE CAVITY
M.OKAMURA1, M.ABE2, K.KITAMURA3, H.NISHIYAMA4, R.HATAKEYAMA5 and R.KUWANO6
1Engineer, Disaster Reduction Department, GEO SEARCH Co., LTD., Tokyo, Japan, m-okamura@geosearch.co.jp(corresponding author)
2
Section Chief, Disaster Reduction Department, GEO SEARCH Co., LTD., Tokyo, Japan, m-abe@geosearch.co.jp
3
Associate director, Road and River Department, Fujisawa City, Kanagawa, Japan, fj0-dorokasen-s@city.fujisawa.lg.jp
4Section Chief, Road and River Department, Fujisawa City, Kanagawa, Japan, fj0-doiji@city.fujisawa.lg.jp
5Senior Unit Chief, Road and River Department, Fujisawa City, Kanagawa, Japan, fj-doiji@city.fujisawa.lg.jp
6Professor, ICUS, IIS, the University of Tokyo, Tokyo, Japan, kuwano@iis.u-tokyo.ac.jp
Keywords: road cave-in, sub-surface cavity, expansion, penetration resistance
1. INTRODUCTION
A collaboration among Fujisawa city, IIS Univ. ofTokyo and GEO SEARCH address the countermeasureagainst road cave-in through various approaches inFujisawa city since April 2017. Road cave-in causes
traffic accidents / disturbances, especially in emergency
situations. The purpose of this collaborative study is toinvestigate the mechanism of cavity formation andexpansion. Thus, the study is important in maintaining
road function safety. The study includes the monitoring
surveys of sub-surface cavity using GPR (Ground
Penetrating Radar) every 6 months, the detailed
investigation of subsurface cavity, and regional
evaluation based on the result of the surveys. As a part ofthe study, some of surveyed cavities were observed indetail by open-cut method. This paper describes the
expansion process of sub-surface cavities.

After removing the pavement, digging up to the top of
the cavity and measuring the size of cavity, the value ofpenetration resistance of the ground below the cavity wasmeasured by a portable cone penetrometer (Fig. 1). The
ground condition below the cavity is one of valuable
information that shows the expansion process of thecavity. And the reason for using a portable cone
penetrometer is that it is easy to understand the groundconditions accurately. Next, based on the result of thepenetration test, the ground was further dug down to thepoint where the cavity originally generated. During the
digging, the condition of the ground was carefully
observed. After the causes of cavity were identified,
repair works were carried out. In this study, all of ten
cavities that investigated in detail were located in a sandlayer by washing out due to damaged sewage pipes cracked or broken (Fig.2). However there weredifferences in ground conditions such as the presence ofgroundwater.

2. PURPOSE AND METHODS OF PENETRATIONRESISTANCE TEST OF GROUND BELOW THE
CAVITY
Because there are various mechanisms of cave-in
formation, an identification of the cause of the subsurface cavity is essential for reliable repair. In this study,
the factors of cavity formation and the ground conditions
were investigated in detail at ten cavity-locations.

Cracked sewer joint

Figure 2: Damaged sewer joint
3. RESULTS AND DISCUSSION
The relevance between the value of looseness below thecavity and the occurrence of cavity is consideredaccording to the ground condition.
Case-A is a typical cavity that caused by washing out
and expanded in a short period in a sand layer. The
washing out of the sand occurred from small damaged
joint of sewage pipe. As shown in Table 1, the result ofpenetration test, the soil below the cavity was uniform
and very loose between the bottom of cavity (GL-0.63m)

Portable cone penetrometer

Sub-surface cavity

Figure1: Portable cone penetration test91

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 24

and the ground water level (GL-3.5m). The similar
conditions were observed at other three sites in this study.

which are the fluctuation of water level and type ofground. A cavity in highly permeable model groundexpands with the fluctuation of water level. In actual
ground, it corresponds to the fluctuation of groundwaterin a sand layer. The process is that a cavity expands
upward while repeating the collapse of upper sand withthe fluctuation of water level. It may be suggested thatthe non-uniform penetration resistance is the sign ofrepeated sand collapse, although it should be noted thatthe non-uniform cone penetration resistance can becaused by the presence of gravels.

Table 1: Outline of Case-A

A
Exist
Corrupted Sewage pipe
Cause
(GL-2.45m)
Sandy soil
GroundDeep(GL-3.5m)
G.Water
Penetration value and Around cavity (m)CASE
LooseArea

0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3
3.1
3.2
3.3
3.4

0.20
0.63

Table 2: Outline of Case-B

As(Pavement)
Crushed
stone

B
Exist
Corrupted Sewage pipe
Cause
(GL-1.64m)
Sandy soil
GroundShallow(GL-1.45m)
G.Water
Penetration value and Around cavity (m)CASE
LooseArea

CavitySand(Sub-grade)

2.43

3.50

00
0.1
0.1
0.2
0.2
0.3
0.3
0.4
0.4
0.5
0.5
0.6
0.6
0.7
0.7
0.8
0.8
0.9
0.9
11
1.1
1.1
1.2
1.2
1.3
1.3
1.4
1.4
1.5
1.5
1.6
1.6
1.7
1.7
1.8
1.8
1.9
1.9
22
2.1
2.1
2.2
2.2
2.3
2.3
2.4
2.4

point of cause

Sewagepipe
φ1650
GroundWater

Case-B is another typical cavity that expanded slowly
in sand and gravel layer with high groundwater level (Fig.
3). As shown in Table 2, the ground water level was GL1.45m. It appeared between the bottom of cavity (GL0.30m) and the damaged point of sewage as the factor of
the cavity (GL-1.64m). The penetration resistance valueof below the cavity was not uniform. Although it went up
and down, the overall trend becomes larger with thedepth. The similar type of cavities and loosening wereobserved at other two sites in this study.

0.12
0.30

As(Pavement)
Crushed stone(Sub-base)CavitySand and gravell(Sub-grade)
1.45
1.64

point of cause
Sewagepipe
φ800

Ground Water

4. CONCLUSION
The finding of this study based on the detailed
investigation in actual ground is that the penetration
resistance value may reveal a process of cavity
expansion.
It is difficult to investigate the cause of cavity underroad maintenance work in short time in usual way.
Consequently, this consideration based on actual cases
seems to be a lead to great breakthroughs in research into
the causes and mechanisms of cavity.
If the process of expansion of cavity is estimated bysimple method, it helps to solve the issue to maintainroads in optimum approaches.
REFERENCE[1] R. Kuwano, R. Sera, Y. Ohara. 2018. Model tests tosimulate formation and expansion of subsurface cavities.
Proc. of 9th international conference on physicalmodelling in geotechnics, ICPMG2018, pp.1087-1092.

Figure 3: Sewer pipe and ground water (CASE-B)
Previous researches by laboratory model tests[1]reported two key factors for the expansion of cavity,92

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 66

AN INVESTIGATION OF URBAN SAFETY IN YANGON’S BACK DRAINAGE SPACE:
IDENTIFICATION OF EXISTING CHALLENGES AND ROLES OF STAKEHOLDERSCONSIDERING THE POTENTIAL AS URBAN COMMONS
T. MATSUSHITA1, E. ROELL2, A. KUBOTA3, and K. MEGURO4
1

Project Researcher, International Center for Urban Safety Engineering, Institute of Industrial Science, the University ofTokyo, Japan, matsu-t@iis-u-tokyo.ac.jp (corresponding author)
2
Founder & Director, Doh Eain,emilie@doheain.com
3
Project Professor, Department of Urban Planning, the University of Tokyo, Japan, ak@td.t.u-tokyo.ac.jp
4
Professor & Director, International Center for Urban safety Engineering, Institute of Industrial Science, the Universityof Tokyo, Japan, meguro@iis.u-tokyo.ac.jp
Keywords: Back Drainage Space, Yangon, urban safety, urban commons, stakeholders
1. BACKGROUND & OBJECTIVE
Yangon’s cityscape is transforming at an unprecedented
speed in rapid urban development which started since thedemocratization of the country in 2012. The city is facing
typical problems caused by increasing urban population,such as traffic congestion and lack of housing, as anincreasing number of new development projects withlarge scale commercial buildings and high-rise
condominiums are springing up in the city. Despite therapid transformation, the Central Business District (CBD)
of Yangon still holds the appearance of the original gridplan built during the colonial period giving a sense of
nostalgia to visitors today.
After the British colonized the city in 1852, a new city
plan of wide roads in a grid pattern was implemented with
an emphasis on the importance of proper drainage systems
as Yangon was suffering from frequent floods. Back
Drainage Space (BDS), a 15-foot wide back alley with
open gutters and underground sewage facilities, was built
behind buildings as a part of the scheme to provide
sufficient space for air ventilation and light to keep the city
sanitary and protect the city from disasters such as floodand fire. In the early days, the space not only served its
purpose but residents used it for unintended purposes suchas a social space or passage. However due to a lack ofproper maintenance, the space became dirty and the local
authority closed access to BDS in the 1980s. Over nearly
three decades that passed while BDS became unused,some residents kept throwing trash into the alley, causing
most residents to keep their doors and windows closed.
Recent democratization has brought various changes to
Myanmar. Urban areas especially had to accommodate
growing needs in response to rapid social and economic
development. BDS became a place of social
experimentation, initiated by a social enterprise / NPOcalled Doh Eain which promotes the utilization of BDS asa space for the community. The local government has
begun to take action by cleaning and repairing BDS
around the city at the same time. This movement of placemaking has inspired many and brought great
encouragement, increased the level of public interest andshown promising positive support by the government.
There are approximately 180 BDSs in Yangon today.
Comprising a large part of the urban infrastructure andcityscape of central Yangon, there is a serious need toreexamine the function and spatial quality of BDS in theface of Yangon’s urban renewal. Considering thepotential of BDS and searching to find ways in which
BDS can be utilized as urban commons in the future, theauthors conducted a series of field surveys with residents
and the authorities to grasp the history, understand thecurrent condition of BDS and to examine effects of ongoing place-making activities.
2. METHODOLOGYThis research is based on a series of field surveys
conducted between 2016 and 2018. Due to a lack ofofficial records or documentation to comprehend thehistorical background of BDS, the authors started byconducting semi-structured interviews with residents in
the CBD. Based on the findings, some issues wereselected as themes for Focus Group Discussions (FGDs),
such as intended use and management of the space, inorder to get a deeper understanding of the subject as wellas people’s perception and desires regarding BDS. In
addition to the qualitative research, household surveys
were conducted in areas where projects were implemented
by Doh Eain to measure the project impacts, along withocular surveys to get quantitative data of target
communities. While the interviews and FGDs wereconducted with residents and ward officers who wereactively engaged with the activities, as they were selectedby the ward officer or members of the community,
household surveys were conducted to randomly selected
residents including those residents who were not actively
engaged or had no interest in the project. This allowed fordiverse views and perspectives on BDS and the project.
Ocular surveys of two BDSs with all buildings facing the
BDS were conducted to grasp the actual condition of thebuilt environment such as the number of stories and units,building period and condition of the means to access the
BDS, such as staircases and doors at the back of thebuildings connecting to BDS. The survey questions are
categorized into five themes: history, current conditions,community profile, project participation and preference
and management. This paper focuses on some key
findings related to urban safety and identifies existing
challenges and the roles of stakeholders are discussed as a
critical factor in considering the potential of the space asurban commons.
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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 66

3. PROCESS OF A PLACE-MAKING PROJECTDoh Eain implemented the Alley Garden Project,
together with community members and authorities in six
locations in the CBD, during 2017 and 2018. Multiple
stakeholders include residents, the ward and townshipofficers, parliamentary members, five departments fromthe city government called Yangon City Development
Committee (YCDC) and Doh Eain. BDS is under thejurisdiction of YCDC and each one of those fivedepartments within YCDC has responsibility for specificmanagement tasks regarding BDS. The project’s
implementation process was created based on a principleof people’s participation which encouraged the formationof a resident committee for project administration andmanagement as well as the participation of the residents
in the activities such as meetings and design workshops.
The funding structure of the project is a unique model
developed by Doh Eain with 20% of the total cost of the
project implementation provided by residents themselves
while the remaining 80% is provided by Doh Eain.

city government to regulate the residents to maintain anduse the staircase properly. It can be said that the unsanitarycondition of BDS did not encourage the residents to gain
accessibility. For the rest of buildings which have nostaircase, they are considered to be non-conforming
buildings and in the majority of cases, they were built
before the government mandated buildings to be built withemergency staircases.
Ocular surveys revealed that most non-conforming
buildings without staircases were under four stories high,and likely to have been built during the colonial period orunder the Burma Socialist Programme Party, the military
regime led by Ne Win, while modern buildings that areusually over seven stories high had some means of egressinstalled. The latter are likely to have been built either
after the regulation was in place or just out of common
practice or necessity before or after the regulation. There
were two types of egress observed, one that is built into
the building with space for the staircase and the other thatis only attached on the surface of the building like a ladder,obviously not as safe as the former. There is a big
challenge to fix this situation because of 1) a lack offinance to pay for the repair or to install new staircases by
the owners and 2) a difficulty in getting consensus among
many owners of different units of a single building.
Therefore, the old, deteriorated structures andcomplicated ownership patterns of buildings may hinder
the changes necessary for BDS to be used safely as urban
commons. The survey revealed that in spite of living in
deteriorated old structures, 51% of the residents are notconcerned about natural disaster such as earthquake or fire
and this low level of awareness suggests that it may bedifficult for residents to invest in necessary renovations.
On the other hand, although the owners are responsible for
upgrading their own property, as this issue concerns theliving safety of many citizens especially in the CBD, thecity government may be required to take a more activerole in encouraging some sort of resolution. The alleyway
project may be a good opportunity to facilitate this sincerecognizing the usefulness and well-being of BDS may
convince stakeholders such as residents and city
government to take action towards securing theaccessibility of BDS.

4. FINDINGS
In summary, the surveys revealed that the project brought
positive impact overall by increasing the usage of BDS
from nearly zero to 50%, improving the residents’
perception about BDS and encouraging communication
among different stakeholders. However, despite its
success in increasing the usage of BDS, the survey
revealed that the participation level in the project by theresidents was low, mainly limited to the committee
members and the ground floor residents directly affectedby the changes.
The key findings related to urban safety are categorized
into five sub-themes of current conditions: accessibility,
safety, security, density and ownership. In terms ofaccessibility, even though many residents thought thatBDS became useful after the project, it revealed that mostresidents do not have direct access to BDS from their units
due to a lack of emergency staircases. Most old buildings
have no rear staircase while most high-rise buildings haverear staircase but unused and most ground floor units haveback doors but often closed or unused. Regarding thesecurity, most people feel safer after the project but somesecurity measures need to be considered if the usage of
BDS increases and if it becomes open to public. The
survey also revealed that most buildings are owned bymultiple owners and neighborhood with new high-risebuildings are1.5 times more populated than neighborhoodwith old buildings.

6. CONCLUSION
The study revealed that the project to utilize BDS for thecommunity brought positive impact to the community
while also bringing attention to the existing safety issuesof lack of emergency accessibility. Further study isneeded to investigate alternative solutions involving
multi-stakeholders to improve the condition to bringvarious public benefit.

5. ANALYSIS: EXISTING CHALLENGES ANDROLES OF STAKEHOLDERS
A lack of accessibility to BDS is caused by a number ofreasons. As this can be a serious safety threat in case ofdisaster, it is important to investigate the causes for suchsituations. For buildings which have a staircase but it isunused, it is due to deterioration caused by a lack ofmaintenance or misuse of the space as personal storage by
the residents and also by a lack of law enforcement by the

ACKNOWLEDGEMENT
We would like to thank the residents, local authorities,
volunteers and Doh Eain for their support and cooperationin this study. The field study was made possible by theopportunity provided by the SATREPS programsupported by JST and JICA.

94

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 26

A SIMPLIFIED NUMERICAL MODEL TO EVALUATE POST-EARTHQUAKE INITIALSITUATION ASSESSMENT TOOLS AND TECHNIQUES
M.S. HOSSAIN1, K. CHAITANYA2, M. NUMADA3, N. MORIMURA4 and K. MEGURO5
1
Graduate Student, Department of Civil Engineering, UTokyo, Tokyo, Japan
2
Assistant Professor, IIS, UTokyo, Tokyo, Japan
3
Associate Professor, ICUS, IIS, UTokyo, Tokyo, Japan
4
Professor, Department of Emergency and Critical Care Medicine, UTokyo, Tokyo, Japan
5
Professor, ICUS, IIS, UTokyo, Tokyo, Japan
Correspond to M.S. HOSSAIN (shak-h@iis.u-tokyo.ac.jp)
Keywords: Emergency response, post-earthquake initial situation assessment, simplified numerical model
1. INTRODUCTION
The estimates of UNISDR reveal that around 1.35
million people were killed by natural disasters from 1996
to 2015, while more than half of them have died due toearthquakes [1]. Large-scale catastrophic events likeearthquakes represent one of the greatest challenges toemergency response system [2]. It is also well known
that earthquake emergency response is nothing but fightagainst time as the time passes the possibility of finding
alive trapped victims goes down [3]. However, the mostfundamental activities to save lives include initialsituation assessment, forming teams for emergency
response, securing emergency routes and IC networks,
search and rescue, evacuation, damage assessment andmaintain public relations [4]. As the first task ofemergency response is the initial situation assessment, in
this research a simplified numerical model has beendeveloped to evaluate post-earthquake initial situationassessment tools and techniques. Further, the model was
verified by the 1995 Great Hanshin Awaji (Kobe)
earthquake disaster on firefighting activities.
2. SIMPLIFIED NUMERICAL MODEL
The model consists of three main parts, which are input,
system/process, and output. Figure 1 shows the flowchartof the simplified numerical model.
Input: The input components are further divided into
scenario input and system input. Scenario input includes
affected areas, number of trapped victims at eachaffected area, the total number of the fire station andfirefighters (i.e., first responders) for this particular area
and travel time from the fire station to affected area.
The system input refers to all the possible tools andtechniques, which are smartwatch (proposed), remotesensing, uncrewed aerial vehicles, emergency call, social
media, fast reconnaissance survey, and mass media togather information, i.e. damage and trapped victims of
the affected area. Based on observations and expert
concerns, it is assumed that smartwatch will follow a
straight line pattern. The remote sensing and UAVs will
follow stair-step type pattern, emergency call and social
media will follow exponential type pattern, fastreconnaissance survey and mass media will also follow‘S’ type pattern to transmit trapped victims location anddamage level of the affected area to the emergency
manager (Incident Command Center).
System / Process: The first step of the system / process isto estimate maximum information at each time.

Figure 1: Flowchart of a simplified numerical model
The second step of the system or process is to calculate
the estimated trapped victims at each location and time.
The following equation has been used to calculate
estimated trapped victims.
𝑬𝒔𝒕𝒊𝒎𝒂𝒕𝒆𝒅 𝑻𝒓𝒂𝒑𝒑𝒆𝒅 𝑽𝒊𝒄𝒕𝒊𝒎𝒔 = 𝑻𝒓𝒂𝒑𝒑𝒆𝒅 𝑽𝒊𝒄𝒕𝒊𝒎𝒔 × 𝑴𝒂𝒙𝑰𝒏𝒇𝒐

When information about the trapped victims becomes
available then, the third step is to allocate resources. In
this study total fire station represents total resources unit.
An equation has been proposed in this study to allocate
the resources unit, which is given below:
𝑨𝒍𝒍𝒐𝒄𝒂𝒕𝒆 𝑹𝒆𝒔𝒐𝒖𝒓𝒄𝒆𝒔 𝑼𝒏𝒊𝒕=((𝐄𝐬𝐓𝐕[𝟏] − 𝐄𝐱𝐓𝐕[𝟏]) × ∑𝐧𝐅𝐒𝐭 × 𝐌𝐚𝐱𝐈𝐧𝐟𝐨)(∑(𝐄𝐬𝐓𝐕[𝐢] − 𝐄𝐱𝐓𝐕[𝐢]) )𝑬𝒔𝑻𝑽 = 𝑬𝒔𝒕𝒊𝒎𝒂𝒕𝒆𝒅 𝑻𝒓𝒂𝒑𝒑𝒆𝒅 𝑽𝒊𝒄𝒕𝒊𝒎𝒔
𝑬𝒙𝑻𝑽 = 𝑬𝒙𝒕𝒓𝒊𝒄𝒂𝒕𝒆 𝑻𝒓𝒂𝒑𝒑𝒆𝒅 𝑽𝒊𝒄𝒕𝒊𝒎𝒔
𝒏𝑭𝑺𝒕 = 𝑵𝒐 𝒐𝒇 𝑭𝒊𝒓𝒆 𝑺𝒕𝒂𝒕𝒊𝒐𝒏 (𝑵𝒐 𝒐𝒇 𝑹𝒆𝒔𝒐𝒖𝒓𝒄𝒆𝒔 𝑼𝒏𝒊𝒕)
𝑴𝒂𝒙𝑰𝒏𝒇𝒐 = 𝑴𝒂𝒙𝒊𝒎𝒖𝒎 𝑰𝒏𝒇𝒐𝒓𝒎𝒂𝒕𝒊𝒐𝒏95

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 26

The fourth step of system/process is to extricate
trapped victims. The following equation is used to
extricate trapped victims:
𝑻𝒓𝒂𝒑𝒑𝒆𝒅 𝑽𝒊𝒄𝒕𝒊𝒎𝒔 𝑬𝒙𝒕𝒓𝒂𝒄𝒕𝒊𝒐𝒏 =post-earthquake damage and / or trapped victim
information’s to incident commanders) from the affectedarea to the incident command center (ICC) have been
considered only from emergency call and fastreconnaissance survey.
Figure 3 shows the number of saved lives at actual caseand model case. In the real case, Kobe firefighters
rescued 735 alive victims, while the model gives 744
alive victims [5]. However, in the case of day basis save
lives, the difference between actual and model result is
less than 10 persons expected day two.

𝒏𝑭𝑺𝒕 × 𝒎𝑭𝑺𝒕 × 𝒅𝒕
𝑬𝒎𝒉𝒏𝑭𝑺𝒕 = 𝑵𝒐 𝒐𝒇 𝑭𝒊𝒓𝒆 𝑺𝒕𝒂𝒕𝒊𝒐𝒏 (𝑵𝒐 𝒐𝒇 𝑹𝒆𝒔𝒐𝒖𝒓𝒄𝒆𝒔 𝑼𝒏𝒊𝒕)
𝒎𝑭𝑺𝒕 = 𝑵𝒐 𝒐𝒇 𝑭𝒊𝒓𝒆 𝑭𝒊𝒈𝒉𝒕𝒆𝒓𝒔 𝒊𝒏𝒗𝒐𝒍𝒗𝒆𝒅 𝒕𝒐 𝒆𝒙𝒕𝒓𝒂𝒄𝒕𝒊𝒐𝒏 𝑻𝑽

𝒂𝒕 𝒆𝒂𝒄𝒉 𝑭𝒊𝒓𝒆 𝑺𝒕𝒂𝒕𝒊𝒐𝒏
𝒅𝒕 = 𝒕𝒊𝒎𝒆[𝒊 + 𝟏] − 𝒕𝒊𝒎𝒆[𝒊]𝑬𝒎𝒉 = 𝑬𝒙𝒕𝒓𝒊𝒄𝒂𝒕𝒆 𝑴𝒂𝒏 𝑯𝒐𝒖𝒓𝒔

The final step of system/process is to use survival
probability. The following survival probability has beendeveloped based on the 1995 Great Hanshin Awaji
earthquake disaster firefighters data (Figure 2) [5].
𝑺𝒖𝒓𝒗𝒊𝒗𝒂𝒍 𝑷𝒓𝒐𝒃𝒂𝒃𝒊𝒍𝒊𝒕𝒚(%) = 𝟎. 𝟎𝟏𝟎𝟓 × 𝒕𝒊𝒎𝒆𝟐 − 𝟏. 𝟗𝟕𝟔 ×𝒕𝒊𝒎𝒆 + 𝟗𝟕. 𝟎𝟓𝟖

Figure 3: No of save lives
4. CONCLUSION AND FUTURE WORK
A numerical model has been developed in this researchthat has a potential to help the earthquake emergency
response system. Investigating the previous earthquakes
and emergency response, learning to know that rapid
initial situation assessment after an earthquake is the oneof most essential task to increase number of save life of
the trapped victims by allocating the resources efficiently
and appropriately over time. This proposed model can beused by emergency stakeholders to know the robustnessof their post-earthquake initial situation assessment tools
and techniques, which will help them to take timely
initiatives for awareness and preparedness for proper
response. However, further study is necessary to include
the randomness in the information dissemination ofvarious post-earthquake initial situation assessment aswell as the resource constraints along with information
availability in simplified numerical model.

Figure 2: Survival Probability
Output: The final output of the proposed model is thenumber of saved life at each location and each time. The
following equation has been used to know the number ofsaved lives:
𝑵𝒐 𝒐𝒇 𝑺𝒂𝒗𝒆𝒅 𝑳𝒊𝒗𝒆𝒔 = 𝑵𝒐 𝒐𝒇 𝑬𝒙𝒕𝒓𝒊𝒄𝒂𝒕𝒆 𝑻𝑽
× 𝑺𝒖𝒓𝒗𝒊𝒗𝒂𝒍 𝑷𝒓𝒐𝒃𝒂𝒃𝒊𝒍𝒊𝒕𝒚

3. MODEL VERIFICATION
To verify the simplified numerical model, data offirefighter activities during 1995 Great Hanshin Awaji
earthquake disaster have been used. In total Kobe
firefighters extricated 1886 trapped victims from ten
affected area of Kobe city [5]. There were 29 fire stations
in Kobe city and total 1298 full time firefighters. Basedon trapped extracted by Kobe firefighters. The extricate
man hours (man hours need to extricate one trapped
victims) have been assumed to 8 man hours up to victims,
from 12 to 24 hours 12 man hours, from 24 to 48 hours
30 man hours, from 48 to 72 hours 35 man hours, from72 to 96 hours 61 man hours and from 96 to 120 hours
119 man hours [5]. Travel time from fire station toaffected area have been considered from one to fourhours with the assumption that less severely affected area
took less time and high severely affected area took higher
time. The information index (which is the availability of

5. REFERENCES[1] CRED & UNISDR. (2016) Poverty and Death:
Disaster Mortality1996-2015. Report[2] Chan, T. C., Killeen, J., Griswold, W. and Lenert, L.
(2004), Information Technology and Emergency
Medical Care during Disasters. Academic Emergency
Medicine, 11: 1229–1236. doi:10.1197/j.aem.2004.
[3] M. Statheropoulos, A. Agapiou, G. Pallis, K. Mikedi,
S. Karma, J. Vamvakari, M. Dandoulaki, F. Andritsos,
and C. P. Thomas, \Factors that affect rescue time inurban search and rescue (USAR) operations," Natural
Hazards, vol. 75, no. 1, pp. 57-69, 2015.
[4] “Total Process of Disaster Management" [Online].
Available: http://www.numa.iis.u tokyo.ac.jp/1.svg[5] Fire Fighter Activities in 1995 Great Hanshin Awaji
Earthquake. Kobe city Fire department, 1995.

96

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 73

DEVELOPMENT OF FLOOD INUNDATION MAPPING TECHNIQUE IN ASIA WITH AHI-8,
MODIS AND AMSR2 MEASUREMENTS
Wataru Takeuchi1 , Kwak Youngjoo2 and Jonggeol Park3
1

Professor, Institute of Industrial Science, The University of Tokyo, Japanwataru@iis.u-tokyo.ac.jp (corresponding author)
2
Principal researcher, ICHARM-UNESCO, Japan
3
Associate Professor, Tokyo University of Information Science, Japan
ABSTRACTIn cloudy area of the Earth, MODIS limits the sensor’s ability to quantify biophysical processes in heterogeneous landscape. A passive microwave sensor AMSR2 is not subject
to cloud contamination although its spatial resolution is relatively coarse. In this paper, a new spatial and temporal adaptive data fusion model algorithm is presented and demonstrated to blend MODIS and AMSR2 to predict daily land
surface water coverage. The MODIS 8 day composite 1km
normalized difference water index (NDWI) and AMSR2 daily
16km normalized difference frequency index (NDFI) are used
to map land surface water coverage (LSWC) which is effective to monitor agriculture and flood monitoring issues. It
was found that the algorithm accurately predicts daily LSWC
of AMSR2 at an effective fractional coverage close to that of
MODIS.
Index Terms— Data fusion, image enhancement, agriculture and flood monitoring

The Normalized Difference Water Index (NDWI) is asatellite-derived index from the visible (VIS) and Short Wave
Infrared (SWIR) channels derived from Moderate resolution
imaging spectro-radiometer (MODIS) [Takeuchi ]it et al., 2004].
The SWIR reflectance reflects changes in both the vegetationwater content and the spongy mesophyll structure in vegetation canopies, while the VIR reflectance is affected by leafinternal structure and leaf dry matter content but not by watercontent. NDWI can monitor flood patterns at finer spatial resolution than AMSR2 at the expense of cloud contamination.
The complementary nature of the measurements in the optical and microwave domain implies a need for integratingthem for improved coverage in space and time. The potential
for synergistic analysis of microwave and optical data to monitor land surface water coverage observations has been identified earlier [Mori, et al., 2009]. The more precise calibration
between AMSR2 and MODIS was conducted to find the relationship between AMSR2 and MODIS for land surface water
coverage (LSWC).
1.2. Objective of this project

1. INTRODUCTION
1.1. Needs for better information
Land surface water coverage is one of the critical parameters
for agriculture and flood monitoring. The dynamic nature ofthis parameter ideally requires observations with high temporal and spatial resolutions. In cloudy area of the Earth, opticalsensor limits the sensor’s ability to quantify biophysical processes in heterogeneous landscape. A passive microwave sensor is not subject to cloud contamination although its spatial
resolution is relatively coarse.
Advanced Microwave Scanning Radiometer for Earth
Observation System (AMSR2) presents a potential for flood
and waterlogging monitoring and soil moisture estimation
because of the ability of the microwave signal to penetrate
through cloud and provide an all-day data and its sensitivity
to surface water [Li et al., 2016]. It can fast reveal large-scale
flood patterns.

97

In this paper, a new spatial and temporal adaptive data fusion model algorithm is presented and demonstrated to blend
MODIS and AMSR2 to predict daily land surface water coverage.
2. METHODOLOGY
2.1. A flowchart and data used in this study
Cloud free MODIS 8-day composite of VNIR and SWIR
channels are used to compute the normalized difference water index (NDWI). NDWI are carefully interpreted to choosewater or inundated area and it was found that 0 was thethreshold to distinguish land and water with NDWI image.
NDWI images in 1km resolution were aggregated into 16km
by spatial average and they were defined as land surface water
coverage (LSWC). AMSR2 daily mosaics including 18.7 and17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 73
23.8GHz are used to compute normalized difference polarization index (NDFI). Then NDFI derived from AMSR2 were
calibrated with MODIS derived LSWC. Finally daily LSWC
were derived from the calibration model solely from AMSR2
NDFI.

A fairy good agreement could be found between AMSR2NDFI and MODIS NDWI. From AMSR2 NDFI and MODISNDWI maps, we knew that the area was absolutely coveredby waterlogging.
3.2. Calibration of MODIS LSWC as a function of AMSR2
NDFI

2.2. Land surface water coverage mapping
MODIS is used to monitor flood patterns at finer spatial resolution than AMSR2. The SWIR reflectance reflects changes
in both the vegetation water content and the spongy mesophyll structure in vegetation canopies, while the VIR reflectance is affected by leaf internal structure and leaf dry
matter content but not by water content. We used normalized
difference water index (NDWI);V IS − SW IR(1)V IS + SW IR
where VIS represents the reflectance value of visible
channel and SWIR short wave infrared, respectively. MODIS
channel 1 is used as VIS and channel 7 as SWIR. NDWI isdefined by extending the idea of NDVI with the combination of VIS, NIR and SWIR channels and each index has thesymmetric expression as a function of VIS, NIR and SWIR.
AMSR2 is used to monitor flood patterns at more frequent
time resolution than MODIS. When atmospheric transmission is near to 1, we can obtain Normalized Frequency Index(NDFI) as follows [Takeuchi et al., 2006];
N DW I =T B18.7V − T B23.8V(2)
T B18.7V + T B23.8V
where T B18.7V and T B23.8V are the brightness temperature of vertical (V) polarization at 18.7GHz and 23.8GHz.
NDFI is less affected by atmospheric conditions and is notdependent on the soil temperature. The rise of water level inrivers, lakes and reservoirs caused a severe flood and waterlogging disaster. NDFI provides a sensitive indicator of thepresence of surface water and it has a good capability to distinguish the water surface and land surface.
In order to access the reliability of the AMSR2 derived
NDFI, we have selected MODIS data with 1km spatial resolution 8-days composite acquired almost at the same satellite
pass time with AMSR2 data to compare with NDFI.
N DF I =Because the emitted microwave signal is sensitive to both
the water and the soil moisture at or near the soil surface,
the fractional water coverage estimated by using passive microwave data AMSR2 is a combination of water are and wet
soil area. However it is impossible to distinguish the wetness and flooding effects solely by AMSR2 coarse resolution.
MODIS NDWI images are used to map water area and they
were aggregated into AMSR2 resolution by spatial averaging
defined as MODIS LSWC.
Figure 2 shows a comparison between AMSR2 NDFI and
MODIS LSWC. NDFI indicates both water and wet soil area
whereas LSWC represents water area only. In this sense wedefined that the envelope curve at the outer edge represents
the water area only. As indicated by a linear line in Figure 2,
AMSR2 LSWC was calibrated as a function of NDFI.
3.3. Flood and water logging monitoring AMSR2 LSWC
According to the principle that the higher AMSR2 LSWC values will be associated to a relative increase of both water areaand soil moisture, we have chosen the other two flood prone
areas in Asia including Ganges delta and Mekong delta.
Figure 3 shows daily changes of LSWC at flood prone
areas in Asia including Ganges delta (24.8N, 91.0E) andMekong delta (11.0N, 105.3E). According to those data, wefound that land surface water coverage dropped down to zerofrom 60 to 120 days of year in dry season and flooding season
starts at 150 days of year and continued until 360 days of year
in Ganges delta. Mekong delta has more clear discrepancy
between dry and season at 220 days of year.
Figure 4 shows seasonal changes of LSWC at flood prone
areas in Asia including Ganges delta (24.8N, 91.0E) andMekong delta (11.0N, 105.3E). Brighter area indicates highabundance of water coverage at that pixel.
4. CONCLUDING REMARKS

3. RESULTS AND DISCUSSIONS
3.1. Comparison of MODIS NDWI and AMSR2 NDFI
imagesIn order to access the reliability of the AMSR2 NDFI maps,
we selected MODIS NDWI as a comparison. Figure 1 shows
a comparison of AMSR2 NDFI and MODIS NDWI maps inAmazon river flooded area observed at September 30, 2006.
A flood area is located in the middle reaches of the Amazon
river and it is one of the most biggest flood plain in the world.

98

This study demonstrated a new spatial and temporal adaptive
data fusion model algorithm to blend MODIS and AMSR2 to
predict daily land surface water coverage. The MODIS 8 daycomposite 1km normalized difference water index (NDWI)
and AMSR2 daily 16km normalized difference frequency
index (NDFI) are used to map land surface water coverage(LSWC) which is effective to monitor agriculture and flood
monitoring issues. A fairy good agreement could be foundbetween AMSR2 NDFI and MODIS NDWI. From AMSR2

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 73(a) AMSR2 NDFI (16km)(b) MODIS NDWI (2km)

Fig. 1. Comparison of AMSR2 NDFI and MODIS NDWI maps in Amazon river flooded area observed at September 30, 2016.
100

moisture retrievals for improved fire risk monitoring.
Proceedings of the SPIE, 6298, 62981B.

MODIS LSWC (%)

80[Li et al., 2016] Li Xi and Wataru Takeuchi, 2016. Landsurface water coverage estimation with PALSAR and
AMSR-E for large scale flooding detection. Terrestrial,
Atmospheric and Oceanic Sciences, 27(4), 473-480.

60[Mori, et al., 2009] Mori, S., W. Takeuchi and H. Sawada,
2009. Estimation of land surface water coverage(LSWC) with AMSR-E and MODIS. Proceedings of
2nd joint student seminar at AIT: Bangkok, Thailand.

40

20[Sippel, et al., 1994] Sippel, S. S. K. Hamilton and J. M.
Melack, 1994. Determination of inundation area in the
Amazon river flood plain using the SMMR 37 GHz Polarization difference, Remote Sens. Environ, 70-76, 48.

0
0

0.01

0.02
0.03
AMSR-E NDFI (Unitless)

0.04

0.05

Fig. 2. Comparison between AMSR2 NDFI and MODIS
LSWC. NDFI indicates both water and wet soil area whereas
and LSWC represents water area only.

NDFI and MODIS NDWI maps, we knew that the area wasabsolutely covered by waterlogging. A comparison between
AMSR2 NDFI and MODIS LSWC shown that NDFI indicates both water and wet soil area whereas LSWC represents
water area only. We defined that the envelope curve at theouter edge represents the water area only and AMSR2 LSWC
was calibrated as a linear function of NDFI. Finally AMSR2LSWC daily values were used to map flood prone areas and it
was found that the algorithm accurately predicts daily LSWC
of AMSR2 at an effective fractional coverage close to that of
MODIS.
5. REFERENCES[Dasgupta et al., 2006] Dasgupta, S. and J. J. Qu, 2006.
Combining MODIS and AMSR-E-based vegetation

99[Takeuchi ]it et al., 2004] Takeuchi, W. and Y. Yasuoka,
2004. Development of normalized vegetation, soil andwater indices derived from satellite remote sensing data.
Proceedings of 25th Asian Conference of Remote Sensing (ACRS): Changmai, Thailand.
[Takeuchi et al., 2006] Takeuchi, W., D. Komori, T. Oki andY. Yasuoka, 2006. An integrated approach on rice paddy
irrigation pattern monitoring over Asia with MODIS andAMSR-E. Proceedings of the AGU: San francisco, USA.
[Temimi, et al., 2007] Temimi M, R. Leconte R and F. Brissette, 2007. Flood and soil wetness monitoring over the
Mackenzie River Basin using AMSR-E 37 GHz brightness temperature. J. of Hydrology, 333(24): 317-328.
[Zheng, et al., 2008] Zheng Wei, C. Liu, Z. Xin and Z. Wang,2008. Flood and Waterlogging Monitoring over HuaiheRiver Basin by AMSR-E Data Analysis. Chin. Geogra.
Sci., 18(3) 262-267.

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 73(a) Ganges delta (24.8N, 91.0E)(b) Mekong delta (11.0N, 105.3E)

Fig. 3. Daily changes of LSWC at flood prone areas in Asia.

(a) Jan(b) Feb(c) Mar(d) Apr(e) May(f) Jun(g) Jul(h) Aug(i) Sep(j) Oct(k) Nov(l) Dec

Fig. 4. Monthly changes of LSWC in Ganges delta centered at (24.8N, 91.0E). Brighter area indicates high abundance of water
coverage at that pixel.

(a) Jan(b) Feb(c) Mar(d) Apr(e) May(f) Jun(g) Jul(h) Aug(i) Sep(j) Oct(k) Nov(l) Dec

Fig. 5. Monthly changes of LSWC in Mekong delta centered at (11.0N, 105.3E). Brighter area indicates high abundance ofwater coverage at that pixel.

100

USMCA 2018

POSTER PRESENTATIONSSEISMIC SAFTEY OF STRUCTURES

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 03

EFFECT OF ASPECT RATIO AND ELEVATION PROFILE ON MODE SHAPES OF TALLBUILDING
P. D. VELANI1 and P. K. RAMANCHARLA2
1

PhD Student, Earthquake Engineering Research Center, City, International Institute of Information TechnologyHyderabad, Hyderabad, India, pulkit.velani@research.iiit.ac.in (corresponding author)
2
Professor of Civil engineering and Head of Earthquake Engineering Research Center, International Institute ofInformation Technology-Hyderabad, Hyderabad, India, ramancharla@iiit.ac.in
Keywords: Tall buildings, aspect ratio, time period, torsion
1. INTRODUCTION
Due to rapid urbanization, many tall buildings arecoming up not only in metros(tier 1) but also in tire 2 and3 cities. On the other hand, it’s clearly known that largepart of the country i.e. around 56% are of India’s landmass is prone to moderate to severe earthquake events.
Also it’s clearly evident from past earthquakes such as
Bhuj 2001, many multistory buildings over 200 km awayfrom the epicenter i.e. in Ahmedabad suffered severely.
Design of high-rise buildings is not same as the design of
low-rise and mid-rise buildings Bureau of Indian
standards has come up with special code IS 16700[1]which gives provisions for designs of Tall buildings. To
understand and implement the provision of this code
sufficient experience and expertise is required.
In this paper one such provision, about torsion
irregularity stipulates that the first two modes ofvibration should be translation modes and the torsion
mode cannot be earlier than the third mode of vibration,is discussed. Observation on how buildings withdifferent aspect ratios result in giving radically different
first natural periods is outlined.

Figure 1: Type of building elevation adopted inparametric study
Table 1: Common data used in parametric study
Parameters
Values/Details
Functional Use

Commercial building

Structural system

Structural Wall System

Location

Seismic Zone IV

Soil TypeType II (Medium Soil)

Concrete Grade

Cladding

M30 to M60
Main steel: HYSD 500
Ties/Stirrup: HYSD 415
1 kN/m2
Typical Floor: 4 kN/m2
Roof: 1.5 kN/m2
2 kN/m2

Parapet wall

4.6 kN/m

Steel Grade
Floor Finish
Imposed Load

2. METHODOLOGY
The phase 1 of parametric study consists of design ofrectangular tower (type 1 as per Figure 1), to beconstructed in seismic zone IV, serving as a commercial
building in India. The total height of building is
considered in such a way that it will qualify as a tallbuilding as per IS 16700. This tower has been analyzed
and designs as per applicable Indian codes for reinforced
concrete building. The response spectrum method ofdynamic analysis is carried out and relevant safety
checks for fundamental period, inter storey drift etc.
were verified.
In phase 2, two alternate towers of type 2 and type 3
were analyzed and designed. The elevation of overall
tower type was maintained as shown in Figure 1. And thesize of towers was selected by ensuring approximately
equal usable carpet area of all three types. Further, allthese towers were analyzed and design in ETABS andobservation is made based on the time period values andbase shear arrived.

Figure 2: 3D FEM Model of Type of building elevation
adopted in parametric study
3. RESULTS AND DICUSSION
Starting with some initial plan dimensions and initialstructural member’s size iterative analysis and design
procedure was adopted. The building were analyzed anddesign as per IS 1893:2016 and IS 16700:2017. The final

101

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 03
fundamental natural period values arrived are tabulated
in Table 2. The gradual decrease in period was found infor type 1 to type2 and from type 2 to type 3 tower. Thisis very natural as selection of elevation profile of type 2
and type 3 will lead in increase in base dimension thereby reduction of natural period of first mode. This period
will decide the factor by which design base shear arrived
from response spectrum will be scaled up. This scaling
up of fore will lead to design of stiffer elements in abuilding which will further tend to reduce the period andthis iteration goes on for couple of times till all themembers are having capacity more than the demand.

REFERENCES[1] IS 16700 (2017) Criteria for Structural Safety of Tall
Concrete Buildings, Bureau of Indian Standards, New
Delhi, India[2] IS 1893(Part 1) (2016) Criteria for Earthquake
Resistant Design of Structures, Sixth revision, Bureau ofIndian Standards, New Delhi, India

Table 2: First three natural modes of building in two
translations and one rotational direction

Direction

XDirection

YDirection

Rotation

ModeTime Period (sec)Type 1

Type 2Type 3

X1

1.72

1.139

0.911

X2

0.452

0.318

0.254

X3

0.203

0.144

0.115

Y1

1.593

1.054

0.896

Y2

0.419

0.307

0.261

Y3

0.196

0.146

0.124

Z1

1.422

0.928

0.631

Z2

0.373

0.299

0.203

Z3

0.169

-

0.092

4. CONLCUSION
It was observed that as for the same built up area:
1. Type 2 and type 3 tower gives more freedom tostructural engineer for placement of lateral load
resisting members. And there by overcoming thetorsional mode as a predominant mode ofvibration.
2. Going for type 2 and type 3 elevations profile
will also tend to reduction in overall height ofbuilding. Such structural gives more stability as
it gives wider base width.
3. Type 2 and type 3 towers is resulting in stiffer
and stable structure, helping to achieve the life
safety goal of infrastructure.
4. Structural engineer have freedom to take help ofinitial wider floors for resisting lateral load of
the tower. This component of overturning
resistance, referred as backstay effect, is criticalin high-rise buildings.
The future work can be done by verifying the statedconclusion for more number of buildings with varying
height and for different seismic zone of India.

102

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 27

ANALYSIS OF HILL SLOPE BUILDING FOR TWIST VARIATION WITH CHANGE IN ASPECTRATIO
RAHUL SURESH VISHWAKARMA1, PRADEEP KUMAR RAMANCHARLA2
1

Student, Earthquake Engineering Research center, IIIT Hyderabad, Hyderabad, India,
rahul.vishwakarma@research.iiit.ac.in (corresponding author)
2
Professor, Earthquake Engineering Research center, IIIT Hyderabad, Hyderabad, India,
ramancharla@iiit.ac.in

Keywords: Hill slope building, twist, Aspect ratio, Axial load
1. INTRODUCTION
Buildings on hilly region are asymmetrical due to its
increase in size of columns in valley direction. Because ofthis asymmetry there is eccentricity in the structure This
leads to torsion and twist in the structure. This twist issmaller but gives a large axial forces on the beams of thefloor which are near to ground level. In this paper we will
see twist variation of each floor in the building. Whichcan be further used for the best aspect ratio of the building.

the center of the stiffness and center of rigidity cause
eccentricity in the structure. The lateral load is taken by
center of mass so the floor will rotate about center ofStiffness.
Changing the length of the building along the ridge
direction will increase the stiffness of the frames along
valley direction and also decreases the twist.
3.ANALYSIS
An earthquake Chamoli of frequency 50Hz was taken andis normalized to 1g was applied across the valley direction
to see the behavior of the building .
The length of the building was changed from 9m to 60m
with the interval of 3m for first 10 values and then doubled
the length for the last aspect ratio.

2.DETAILS
We will be dealing with three storey building above
ground, slope of the ground as 30o ,40o,45o As show in the
figure 1. And will be changing length of the building inridge direction and will see the changes in the twist

FIGURE2: Maximum axial forces in beams due to twist
As shown in the figure 2 these are the maximum axial
load on the ground floor beam(0 level) with three l/b ratio
1,15/9,30/9 the twist value decreases with the increase inaspect ratio.

FIGURE 1: Plan and elevation of the building
When earthquake attacks such hilly buildings there are
two type of the motion one is translation and one isrotation. This rotation and twist can be calculated by using
diagonal vectors. For finding the rotation two vectors aretaken, First vector is the opposite corner points of thebuilding in its initial state and second is same two opposite
corner points of the floor after the deformation(maximum
displacement because of earthquake) .

Table 1: How the twist in the structure effected the axial
load in 0th level beam for 30o slope
Effect of Aspect ratio on twist andAxial forces on beam
Aspectratio
Axial
Twist (O)forces(maximum)(kN)
9/90.0649183
15/90.0345156
21/9
0.024713930/90.0177123
60/90.0054118

Stiffness plays the important role in twist. As each frame
along the valley has different stiffness so center of rigidity
is near to shorter column as it will be more stiff. So centerof mass will be in the middle of the floor. Difference in103

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 27

The above graphs shows the variation with power function
by the relations
y= ax-bwhere a and b are positive integer This is valid forx(aspect ratio)>1 for hilly buildings.
The parameter a,b depends on the position of center ofrigidity or eccentricity and the height of the floor.

From Table 1 and figure 4 we can see that how twist effectthe axial forces of the 0th level beams.The decrease in
twist decreases the Axial forces These axial forces can pullout the beam in the 0th level which can lead to key element
failure. So we need to decrease the twist value. So thereis need to know the configuration of the building for lesstwist.
Twist variation of the figure with three slope angles areshown in figure 3

The twist variation for 30o slope for all three floors withthe aspect ratio is shown in the figure 4

Twist(degree)

Twist(degree)

0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0

y = 0.0726x-1.281
R² = 0.9798

Top floor

0.06

3rd floor

2nd floor

0.04
0.02
0

0
0

2

4

6

Aspect Ratio

0.08
0.06

y = 0.086x-1.372
R² = 0.9759

0.04
0.02

20

4. CONCLUSIONS• Small twist can cause large axial forces in the
ground floor beams.
• Decrease in twist decreases the axial load in the
ground floor beams. As shown in the Table 1• Twist decreases by a power function withincrease in aspect ratio as shown in figure 3.

0

2

4

6

8

Aspect Ratio(b)
Twist(45o)0.1

REFERENCES[1] Y.Singh ,Phani Gade, 15WCEE ,Seismic Behaviourof Building Located on Slopes-An Analytical Study andSome Observations From Sikkim Earthquake of
September 18,2011[2] A.R Vijaya Narayanan,Rupen Goswami and C.V.R.
Murty, 15WCEE 2012 Performance of RC Buildings
along Hill Slopes of Himalayas during 2011 Sikkim
Earthquake.
[3] Aditya B. Deshmukh and Rupen Goswami, ICJ 2018
Use of Walls in controlling detrimental effects of stiffness
irregularity in RC building on Hill slopes.

0.08

0.06

y = 0.0855x-1.38
R² = 0.9793

0.04
0.02
0

2

15

The above graph is for the twist variation of the floors as
we can see in the graphs the bottom floor has less twist
values as compare to floors above it. This difference in thetwist for every floor will be constant after an aspect ratio .
The idea was that it will be the best aspect ratio for thebuilding but as we see in the graph this happens for aspectratio more than 15.which is much larger value. So more
conclusion will me made in the upcoming months.

0.1

0

10

FIGURE 4: Twist variation for the floors in the building

Twist(40o)05Aspect ratio

8(a)Twist(degree)

Twist variation for 30o

0.08

Twist (30o)

4

6

8

Aspect ratio(c)

FIGURE 3:Twist Variation

104

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 30

ANALYSIS OF REINFORCED CONCRETE BUILDING FOR STRONG COLUMN AND WEAK
BEAM BEHAVIOUR
SWAPNIL NAYAN1, PRADEEP KUMAR RAMANCHARLA2
1 Student, Earthquake Engineering Research center, IIIT Hyderabad, Hyderabad, India,

swapnil.nayan@research.iiit.ac.in (corresponding author)
2 Professor, Earthquake Engineering Research center, IIIT Hyderabad, Hyderabad, India,
ramancharla@iiit.ac.in

Keywords: Strong column weak beam, hinges, Area moment of Inertia, moments
1. INTRODUCTION

additional value of 1.4 is considered for the analysis as itis prescribed in IS 13920 : 2016. The structures consistof same beam and column dimensions carried throughout
the structure.

The complete failure and collapse of reinforced
concrete building during an earthquake occurs due to thefailure of the column elements. This is due to the factthat column elements are responsible for the load transferof the structure to the footing hence making it the mostimportant structural element to minimise life loss. To
avoid the failure of column elements, IS 13920 : 2016
recommends that buildings should follow ‘Strong
Column and Weak Beam’ (SCWB) design. It states thatthe total flexural capacity of beam (Mb) should be lessthan that of the column (Mc) at a joint. It is a way todesign the building such that ‘Plastic Hinges’ form inbeam elements of the structure rather than the column
elements. The formation of plastic hinge dissipates theenergy of the earthquake. Moreover it is desirable thatthese hinges form in the top storeys of the structure
rather than the bottom stories. Hence by the formation ofthese plastic hinges in the beam, the structure can takelarger deformations without collapse.

Table 1: Details of structure
Sno.
Ic/Ib
ColumnDimensions
(mm)
1
0.25
425 x 425

Beam
Dimension(b x d)(mm)
600 x 600

20.50

425 x 425

505 x 5053

0.75

425 x 425

475 x 4504

1.00

425 x 425

425 x 42551.25

450 x 450425 x 4256

1.40

440 x 440

405 x 4057

1.50

450 x 450405 x 405

2. DETAILS OF THE STRUCTURE

8

1.75

425 x 425

370 x 370

A 6 storey 2 dimensional bare frame structure inearthquake zone IV, with soil type I ( Rock or hard soils )and fixed base is considered. Initially a 6 storey (3Dimensional ) structure with 4 bays each in x and y
direction is designed according to IS 456 : 2000, IS 1893
: 2016, IS 13920 : 2016 is designed and checked for theload combination given in IS 1893 : 2016, given below:i) 1.2[DL + IL ±! ELx]
ii) 1.2[DL + IL ±! ELy]
iii) 1.5[DL ±! ELx]
iv) 1.5[DL ±! ELy]
v) 0.9DL ±! 1.5ELxvi) 0.9DL ±! 1.5ELy
A single frame in the XZ direction is then selected forthe analysis.
As moment distribution at a joint is directly proportional
to the area moment of inertia (I) and modulus ofelasticity (E) of the element, section sizes of the beams
and columns are varied such that the ratio of area
moment of inertia of column (Ic) to that of the beam (Ib)changes from 0.25 to 2 with an increment of 0.25. An

9

2.00

450 x 450

380 x 380

3. ANALYSIS
Pushover analysis is carried out on each structure toobtain the maximum base shear and roof displacement
before collapse. The values from the pushover analysis isthen used to construct fragility curve for the structures toobtain the maximum value of spectral acceleration (Sa)for the structure. This is done by changing Ic/Ib ratio as
Mc and Mb are directly proportional to Ic and Ib
respectively.
4. FRAGILITY CURVEThe area under the pushover curve gives the total energy
dissipated in the structure. A damage parameter (D) isdefined as the ratio of inelastic energy to the total energyof the structure.[1] The damage parameter is then plotted105

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 30
against Sa at different steps. The value of D ranges from0 ( no damage ) to 1 ( complete collapse ). The value of
Sa at D = 1 shows the Spectral acceleration at which
complete collapse occurs.
5. RESULTS

Sno.

Ic/Ib

3

0.75

Sa,max (g) Sa,max (g)un-cracked cracked
1.805
1.322

4

1.00

2.021

1.008

5

1.25

2.321

1.128

6

1.40

2.036

0.979

7

1.50

2.269

1.062

8

1.75

1.977

0.939

9

2.00

2.146

0.980

6. CONCLUSION• Comparison of values of Sa,max for cracked and uncracked section shows that the value of Sa,max forcracked section is significantly lower than it uncracked counter part.
• When cracked section properties are considered,maximum Sa value occurs for Ic/Ib = 0.75. This is incontradiction with SCWB philosophy.
• When un-cracked section properties are considered,maximum Sa value occurs for Ic/Ib = 1.25, followedby 1.50.
!
• Results show that although code prescribes Mc/Mb ≥1.4 but the actual value of Mc/Mb at which thestructure dissipates the most energy may be different.

Fig 1: Fragility curve for different values of Ic/Ib for
un-cracked section properties.

7. REFERENCES[1] Pradeep Kumar Ramancharla, Rajaram Chenna,
Swajit Singh Goud, Ajay Kumar Sreerama, Gugan
Vignesh, Bhargavi Sattar (2014), Report No: IIIT/TR/
2014/-1 “Hazard, Vulnerability, Risk Assessment of
Himachal Pradesh ”[2] Mitesh Surana, Yogendra Singh, Dominik H. Lang(2018) “Effect of strong-column weak-beam design
provision on the seismic fragility of RC frame buildings”
Fig 2: Fragility curve for different values of Ic/Ib for
cracked section properties.

[3] ATC 40, “Seismic evaluation and retrofit ofConcrete buildings” Volume 1[4] IS 456 (2000) “Plain and reinforced concrete - code
The maximum value of Sa for different values of theratio Ic/Ib is given in the table below for both cracked
and un-cracked section properties:of practice” Fourth revision[5] IS 1893 (2016) “Indian standard criteria forearthquake resistant design of structures, part 1”
General provisions and buildings (sixth revision)

Table 2: Maximum Sa for different Ic/Ib
Sno.
Ic/Ib
Sa,max (g) Sa,max (g)un-cracked cracked
1
0.25
1.231
0.828
2

0.50

1.765

[6] Is 13920 (2016) “Ductile design and detailing of
reinforced concrete structures subjected to seismic forces- code of practice” (First revision)

1.016

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 35

DAMS AND EARTHQUAKES
HARITHA BENDAPUDI1, PRADEEP KUMAR RAMANCHARLA2
1

Student, Earthquake Engineering Research center, IIIT Hyderabad, Hyderabad, India,
haritha.bendapudi@research.iiit.ac.in (corresponding author)
2
Professor, Earthquake Engineering Research center, IIIT Hyderabad, Hyderabad, India,
ramancharla@iiit.ac.in
Keywords: dam, earthquake, strengthening, peak ground acceleration.
1. INTRODUCTION
The Koyna dam has been a topic of much query andanalysis in the past few decades. The Koyna earthquake
which occurred on December 11th,1967 near Koyna dam,which was stable and nonseismic, left everyone baffled.
Through the coming years many researchers haveexamined the reaction of Koyna ground motion on thedam via many techniques. In 1973, Anil K. Chopra and P.
Chakrabarti examined the response of the dam to strong
ground motion recorded during Koyna earthquake by
FEM analysis and anticipated the cracking on themonoliths based on stress results. They concluded thatthe present design criteria of Koyna should be improved
to prevent the damage which occurs due to tensilestresses which develop during earthquakes. [1]Later, D. K Paul and A. R. Chandrasekaran foundthrough a study that the apparent modulus of elasticity ofconcrete increase in the event of dynamic shaking. [2] It
has also been found that system’s dynamic stiffness is
40% more that static stiffness. Response of the dam has
been analyzed under Static Pushover method andIncremental dynamic method by Nik Zainab et al [3]which proved D.K Paul et al’s results. The response of
concrete gravity dams to dynamic loading have beenstudied all over the world taking Koyna dam as reference.
Its unconventional cross section has caused the
maximum tensile stresses developing at the neck of thedam, which thus incurred maximum cracking. [4] O.Omidi
and V. Lotfi have found that water compressibility anddamping mechanism affect the seismic safety evaluationof the dam[5]..Sushi Gupta and I.D. Gupta have calibrated
the attenuation relation for earthquake peak groundacceleration of Koyna region.[6]The aim of the present study is to study the response of
Koyna dam to static loading (inertia forces andhydrostatic loading) and the response of Koyna dam todynamic loading (horizontal and vertical earthquake
loads). The forces developed and the displacement at theneck of the dam are studied and compared. Then the
PGA of the ground motion is increased to see the effectof difference in the response of the dam.

Monolith 17 is the tallest and most cracked. Through thefrequency analysis in ABAQUS, the frequency of thefirst 4 modes has been found as 18.86 rad/sec, 49.97
rad/sec, 68.16 rad/sec and 98.269 rad/sec (3 Hz,7.9
Hz,10,8Hz and 15.6 Hz) [7].
Under the action of static forces, the dam uniformly
deforms to the right thus the dam face bends at an angle
to the reservoir.

FIGURE 1: displacement of dam due to static loads(deformation factor 2E+3).
Compared to typical gravity dams, Koyna dam faces
more deformation due to its cross-section [4].
Under the action of Koyna earthquake acceleration, thedam further deforms. Hydrodynamic forces act on the
dam due to the water in the reservoir. Westergaards
equation has been considered to compute thehydrodynamic forces.

Where P is the hydrodynamic pressure, hw is the heightof water in reservoir and y is the length of ordinate.
The earthquake acceleration and the results of the
dynamic analysis are as shown in Figure 2 and Figure 3.

2. ANALYSIS OF KOYNA DAM UNDER STATICAND DYNAMIC LOADINGThe static analysis of the dam has been done by Finite
Element Method in ABAQUS. 2D stability analysis of
the dam has been done on monolith 17 of Koyna dam.

The peak ground motion of horizontal earthquake
acceleration is almost 0.5g. The peak ground accelerationfor vertical acceleration is 0.3g.

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 35

By increasing the peak ground motion, it has been foundthat the maximum displacement occurs between time t =3.4 sec to t = 4 sec in all cases
Based on that, the values of the peak deformation at theneck node are taken for each peak ground accelerationand the results are tabulated below.
3. CONCLUSIONSThe 2D finite element analysis of the dam is pertainable
since the monolith has constant cross-sectional
dimensions and material properties. Fourier accelerationof ground acceleration, it can be seen that the frequencyof the dam coincides with prominent frequency of theearthquake. The stresses developed in the dam arehighest near the neck portion while the displacements arehighest near the crest. The dam has been nominally built
to resist gravity loads. The earthquake loading has
caused damage due to development of high tensilestresses near the neck of the dam. From the above results
it can be concluded that with an increase in peak groundacceleration, the displacement of the dam increases andthe stresses produced at the base of the dam are very high.
Taking into account the fact that seismicity of
Koynanagar increased after the dam was built, we may
say that it may further increase in the future. Hence it isimportant for us to strengthen Koyna dam by considering
higher PGA values too.

Figure 2: (Anti-clockwise from left top) Horizontal
ground acc, Horizontal Fourier amplitude, Vertical
Fourier amplitude, Vertical ground acceleration

REFERENCES[1] Bulletin Of The Seismological Society Of America. Vol. 63, No. 2,
Pp 381-397.April 1973 THE KOYNA EARTHQUAKE AND THE
DAMAGE TO KOYNA DAM BY A. K. CHOPRA AND P.
CHAKRABARTI.
[2] Identification Of System Parameters Of The Koyna Dam From
Accelograms Recorded On The Dam. D.K Paul And A.R
Chandrashekaran Aand S.L Bhingre Paper No. 1710 Eleventh World
Conference On Earthquake Engineering.
[3] Incremental Dynamic Analysis of Koyna Dam under Repeated
Ground Motions by Nik Zainab Nik Azizan et al, published in IOP
Conf. Series: Materials Science and Engineering 318[4] The earthquake experience at Koyna Dam and stresses in concrete
gravity dams BY A. K. chopra and P. Chakrabarthi, Article in
Earthquake Engineering & Structural Dynamics · January 1972
[5] Plastic damage analysis of Koyna dam with different damping
mechanisms with dam water interactions By O. Omidi and V. Lotfi,
published in WCEE 2012[6] The Prediction of Earthquake Peak Ground Acceleration in Koyna
Region, India By Sushil Gupta and I.D. Gupta, Published in 13th World
Conference on Earthquake Engineering Vancouver, B.C., Canada
August 1-6, 2004 Paper No. 1437.
[7] ABAQUS. (2012). Analysis User’s Manual Volume 3: Materials(Abaqus 6.12). SIMULIA, Dassault Systèmes Simulia Corp.,
Providence, RI, USA.

Figure 3: Displacement of Koyna dam under dynamic
loading.
TABLE 1: Max displacement of node corresponding toincrease in peak ground acceleration
S no.

1
3
4
5
6

PGA
(both
verticalandhorizontal
direction)
0.3g
0.5g
0.6g
0.8g
1g

Max.
displacement

Max. stresses attoe (×106 N/m2)

0.309m0.352 m0.504m
0.815 m1.023m1.909
2.2268
2.83
3.63
3.766

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 61

RECOMMENDED FIELD INVESTIGATIONS FOR EARTHQUAKE SAFTEY OF LOW, MEDIUM
AND HIGH-RISE BUILDINGS IN DIFFERENT SOIL CONDITIONS
E. KEERTHANA1, R. PRADEEP KUMAR2
1

MS Student, Civil Engineering, International Institute of Information Technology, Hyderabad, India,
e.keerthana@research.iiit.ac.in (corresponding author)
2
Professor, Civil Engineering, International Institute of Information Technology, Hyderabad, India,
ramancharla@iiit.ac.in
Keywords: Geotechnical Investigations, Structure, Soil
1.

INTRODUCTION
Structures are supported by soil or rock at its base,and before construction of any proposed project it isnecessary to understand the behavior of its base medium.
Stability and strength provided by the soil or rockdepends on the load applied by the type of structure at its
base. Engineering properties and index properties of thesoil are obtained from different soil tests and similarly
properties of rocks obtained from rock tests. Dependingon the site suitability respective field tests need to be
adopted. Overall organization of activities to find the site
conditions based on the physical properties of soil orrock together called as geotechnical investigations.
Soil plays one of the important roles during seismic
events because of cyclic loading experienced by soil withdifferent frequencies. From some of the past seismic
events it is observed that failure of super structure wasalso due to failure of sub-structure, for not considering
the soil at the foundation level as shown in figures 1, 2 &3. For example, Niigata 1964 earthquake, in which oneof the major causes of damage was failure of foundation
caused by loss of bearing capacity due to liquefaction ofsand or by ground movement where structures were
supported by different soil strata [1]. The study ofgeophysical aspects of the soil at the site are not only
useful for the safety of super structure against gravity,
but also against the dynamic loading conditions at its
base.

Figure 2: Mexico City Earthquake 1985

Figure 3: Kocaeli Earthquake 1999
0.5% of the total cost of the project [2]. Geotechnicalinvestigations are necessary to provide information forstructural engineers in design and construction to make aproject most cost effective. These site investigations are
not economical but also provide safety which is more
important aspect of any project.
2.

SOIL EXPLORATION TESTS BASED ON
STANDARD CODES
IS1892:1979 is the Indian standard code of practicefor subsurface investigations for foundations. This code
mainly deals with subsurface investigations forfoundations of multistoried buildings to determine
sequence, extent, nature and engineering properties ofeach soil stratum for site affected by proposed project [3].
In this code, current methods of subsoil exploration
methods are classified based on type of soil formation.

Figure 1: Niigata Earthquake 1964
Geotechnical investigations are economical whencompared to the additional expenditure required for any
unfavorable ground conditions previously undiscovered
and found during or after the construction. The cost ofsite investigation is relatively small, usually less than109

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 61
Table 1
S.No Method
Reconnaissance Methodsi) Geophysical1
Electrical resistivity
method2

3

Seismic refraction
methodii) SoundingStandard penetration test

4

Static cone penetrometer
test
Dynamic cone
penetrometer test
Exploratory Methods
Shell and Auger

5

Hand Auger

6

Simplified mud boring

7

Wash Boring

8

Percussion drilling

9

Rotary drilling

10
11

12
13
14

i) Explanatory samplingOpen tube sampler andsplit tube sampler
Double tube core barrel

Detailed Investigationsi) Undisturbed samplingThin walled tubes 50 to
125 mmPiston type sampler
Samplers with special
core retainers

15

Sand sampler

16
17

Solidification methods
Open cuts and trenches

18ii)Bearing capacity tests
Plate load test

Type of formation

Alluvial deposits
weathered andfissured rock,buried channels andground waterDo

Sand withoutboulders
Do
All types offormations

Clay and sandy
formations
19
Load tests
Rocks
20
Vane shear test
Soft and sensitive
clays
Engineering properties of soils are obtained from thefield tests mentioned by the code. The capacity of thesoil not only depends on type of formation but also
depends on proposed project and type of structure.
Eurocode 7 [4] also suggests these field tests based on
the site requirements.

Non – cohesive
soils withoutboulders
Primarily used incohesive soils
Primarily used incohesive soils

3. CONCLUSIONS
From past literature study on geotechnicalinvestigations states mainly, the field tests based on typeof soils. The ability of the soil to resist loads depends on
the type of soil and also on type of structure. Under
dynamic loading conditions soil shows the complex
behavior [5] so it is very important to consider type ofsoil while designing structures in seismic zones.
Structural design has to consider possible real site
conditions, even under dynamic loading conditions. Soilbehavior under different loading conditions are given by
the field tests proposed by standard codes. All the fieldtests given in standard codes may not be required for the
given site conditions, only specified field tests need to be
performed based on proposed project and soil conditions.
This paper is mainly on the field tests required for thedifferent height of buildings founded on different type ofsoils. In this paper, type of soils is considered according
to IS 1893 (Part 1):2016. In this code soil has been
divided into three types as hard, medium and soft soil
mainly based on standard penetration number (N) [6].
Table 2
S. No Soil Type
Remarks
1
Rock or Hard Soils
N >30
2
Medium or Stiff Soils
10 <N<30
3Soft Soils
N<10
Mainly three types of buildings are considered in thispaper, they are low (5-storey), medium (10-storey) andhigh-rise (20-storey) buildings. This paper suggests the
structural and geotechnical engineers with field tests
necessary for low, medium and high-rise buildings
founded on hard, medium and soft soils respectively.

All types of soils
specially soil of
mixed typeAll soils except
sands and gravels
above water table
Silts and sands ormixed soils
especially below
water table
Soft to stiffcohesive soils andfine sand except
gravel and boulders
Rocks and soils
with boulders,
except clay or loose
sandRocks, fissured
rock and all soils
except cobbles andboulders
Cohesive soils andsilts
Coarse sand andgravels; mostsuitable for softrocks like shale andany weathered rockformation.

REFERENCES[1] Japan National Committee on Earthquake
Engineering, Niigata Earthquake of 1964
[2] H. N. Wazoh., S. J. Mallo., (2014) “Standard
Penetration Test in Engineering Geological Site
Investigations – A Review,” The International Journal ofEngineering and Science. (IJES) Vol 3 pp 40-48

Soils of medium
strength
Clays and silts
Do

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 61[3] IS: 1892-1979, Indian Standard Code of Practice for
Subsurface Investigation for Foundations.
[4] Eurocode 7: Geotechnical Design – Part 1[5] Miguel P Romo, Manuel J Mandoza and Silvia R
Garcia., (2000) “Geotechnical Factors in Seismic Designof Foundations State-of-the-Art Report.” 12th World
Conference of Earthquake Engineering. (12WCEE)[6] IS: 1893(Part 1)-2016, Indian Standard Criteria for
Earthquake Resistant Design of Structures.

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 64

FINITE ELEMENT ANALYSIS OF PUNCHING SHEAR OF REINFORCED CONCRETE FLAT
SLAB
S. AGRAHARI1, P.K. RAMANCHARLA2
1
2

Student, EERC, IIIT Hyderabad, Hyderabad, India, saurabh.agrahari@research.iiit.ac.in
Professor and Head, EERC, IIIT Hyderabad, Hyderabad, India, ramancharla@iiit.ac.in

Keywords: Flat Slab, Lateral loading, Finite Element Method, Concrete Damage Plasticity model, Punching shear.
1. ABSTRACT
Flat-slab building structures has significant advantages
over slab-beam-column structures because of the freedesign of space, shorter construction time and costeffective aspects. In the present situation of building
construction around the world, Flat slab is becoming
widely popular in the multi-storied buildings. However,many buildings with flat slab have performed poorly
under the earthquake loading and therefore it isconsidered vulnerable under punching shear. The designcode which is followed is not adequate for the punching
shear of flat slab buildings under lateral loading.
To understand the behavior of building with flat slab
subjected lateral loads, a numerical study is performed. A
three-dimensional finite element analysis of reinforced
concrete flat slab with software ABAQUS using theconcrete damage plasticity model is presented. A
reinforced concrete flat slab with and without column
head and drop panel along with the columns is modelled.
A study is performed for understanding the linear andnonlinear behavior of flat slab subjected to lateral staticand dynamic loads.

3. CONCLUSIONS
Flat slab with the column head performs much betterin the dynamic earthquake loading than flat slab withdrop panel.
Punching shear capacity of flat plate increase byconsidering the column head and it reduces its
vulnerability to lateral load to a great extent.
There is no much improvement in the punching shear
capacity by using the flat slab with drop panel.
REFERENCES[1] S. Agrahari and P.K. Ramancharla., (2017).
Understanding The Behavior of Flat Slab by Linear andNonlinear Finite Element Analysis., USMCA, Sendai[2] D.C. Dechka., (2001). Response of shear-studreinforced continuous slab-column frames to seismic
loads., Calgary, Alberta[3] A.S. Genikomsou , M.A. Polak., (2015). Finite
element analysis of punching shear of concrete slabs
using damaged plasticity model in ABAQUS.,
Engineering Structures., Canada[4] A. Kabir and C.D.S. Islam., (2012) Nonlinear finite
element analysis of Reinforced Concrete Plates in
Punching shear.

2. RESULTS
Three flat slab systems are modelled, which are flat
plate, flat slab with drop panel and flat slab with column
head according to the IS 456 code. Analysis is carried onby taking load as the Elcentro earthquake ground motion
and finally their punching shear stress values arecompared.
Table 1: Maximum Punching shear value of flat plate,flat slab with drop panel, flat slab with column head.

Flat slab
Systems
Flat plate
Flat slab
with drop
Flat slab
with head

Maximum Punching shear
stress value (absolute value)
Along load
Across load
direction
direction
0.79
0.34
0.6

0.23

0.44

0.16

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 67

Effect of Soil Structure Interaction on progressive
Collapse analysis of transmission Tower
Anshu Singh RAJPOOT
Earthquake Engineering Research Centre, IIIT-Hyderabad, India
anshusingh.rajpoot@research.iiit.ac.inandPradeep Kumar RAMANCHARLA
Professor & HeadEarthquake Engineering Research Centre, IIIT Hyderabad
ramancharla@iiit.ac.in
ABSTRACTTransmission towers play an important role in the operation of a reliable electrical powersystem that is considered as a lifeline system. Many studies and recent earthquakes investigations
have revealed that, many structures mostly transmission towers performed poorly during wind andearthquake load. Besides many contributing factors for damage, Size, depth of footing and different
type’s soil mainly structures on soft soil has also massive effect on structures. In case oftransmission towers it should be in a straight line at some fixed distance irrespective of soil at thatparticular place. It is common practice in many earthquake prone areas around the world to analyse
the structure using fixed base analysis. This is mainly due to lack of awareness regarding
importance of SSI. In order to understand this phenomenon, a study has been performed to show thedifference in response when the structure is on soft soil compare to fixed base.
Two case studies have been performed to understand the above phenomenon. A 400 KV
transmission tower has been design with proper section. In first case base of transmission tower
assumed as fixed base. In second case a proper soil domain with infinite elements has been modelusing acoustic element which is good for wave propagation. Finally progressive collapse analysis(birth to death analysis) has been performed on both the case studies. Both the case studies revealthat there is great difference in response due to SSI. In second case, it was observed more numberof elements is getting failed as compare to first case.
Keywords: Soil structure interaction, Finite element method, infinite soil elements, performance oftransmission tower.
Results
In case of Fix base Earthquake has been applied at base of footing as shown in figure-3. But while
in second case (where soil domain has been modeled) Earthquake can be apply at two places. Either
it can be at top of the surfaces as shown in figure-4, or it can be at base of the soil after modifying
time history at particular depth of the soil as shown in figure-5. In all three cases maximum stressvalue has calculated at three different heights i.e H=5m , H=25m and H=55m.

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12-14 December 2018, IIIT Hyderabad
0ctober
2010, Kobe, Japan__________________________________________________________________________________________
Paper No. 67

Figure-1 : 400 Kv transmission tower

Figure-2: Infinite soil model

Figure-3

Figure-4

Figure-5

Table-1 : Stress values at different height in above cases.

Type

Stress at 5m(Mpa)

Stress at 25m(Mpa)

Stress at 55m(Mpa)

EQ applied at footing

340

180

22

EQ applied at top surfaces

220

80

15

EQ applied at top surfaces

320

260

25

In First case (earthquake is applied at footing) full force is transferred to footing and footing totower. In third case (EQ applied at bottom surfaces) here also force is transferred from bottom to
top and soil, effect the stress value mostly at mid height of transmission tower as shown in table-1.
But in second case (EQ applied at top surfaces) here force is distributed in tower as well in soil
that’s why stress value is less compare to other cases.

New Technologies for Urban Safety of Mega Cities in Asia
114

USMCA 2018

SESSION 7
MAINTENANCE AND REHABILITATION

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 02

IMPORTANCE OF MAINTENANCE TO EVALUATE AND MAINTAIN SAFETY
OF CIVIL STRUCTURESTAKETO UOMOTO1
1

Position, Professor Emeritus, University of Tokyo

Keywords: Importance of Maintenance, Safety Evaluation, Maintain Safety, Civil Structures, Durability Design1.

as we experienced in tunnels for both railways andhighways. Considering these situations, this paper
explains what is happening now in Japan and how we are
dealing with the problems through research andengineering.

Introduction

On March 11, 14:46, 2011, the massive “Great East
Japan Earthquake” hit the country of Japan just off the
Pacific coast. The magnitude of the earthquake wasreported as 9.0, and shook Japan from Hokkaido to
Nagoya City. The disaster was tremendous comparedto Hanshin-Awaji Great Earthquake which took place inJanuary 17, 1995. A large difference can be seen in not
only the vibration of the ground caused by theearthquake, but the tsunami and nuclear power plant
accident. Such earthquake disasters are occurring quite
frequently compared to other countries. The data showsthat the earthquake energy occurring in Japan is morethan 10% of the whole earth.

2.

General Maintenance Methods used till Now

The maintenance of concrete structures has been done
mostly by the owners of the structures. In case of
public structures, such as roads, bridges, ports, tunnels,
railways, etc., .the ministries or public organizations
maintain the structure after the structures are completed.
For the time being, the methods for the maintenancediffer according to the owners of the structures.
Although there are some differences, the main concept ofthe maintenance can be summarized as follows:
1) Periodic inspection and evaluation of deterioration
degree2) Detailed inspection and decision making
3) Repairing and strengthening of deteriorated structures

On the other hand, population of Japan is estimated toreduce rapidly from now on because of fewer babies in a
family (approximately 1.2 children per family) thanneeded to sustain the present population. Althoughhigh technologies have been developed in recent years, it
is sure that fewer engineers will have to take care of thishuge amount of structures from now on, which has neverexperienced in the past. Due to reduction in theeconomic growth, the budget for both construction andmaintenance will be reduced in the future.

For periodic inspections, the inspectors inspect thestructures visually, sometimes with the help of binoculars
and hammers, once a year or once in several years
according to the importance and time after the structure
is completed.
The inspectors are mostly trainedengineers with experiences. The detailed inspection isdone when the estimated degree of deterioration exceeds
certain limit, or when some new phenomenon is foundduring the periodic inspection. The detailed inspection
is done by visual inspections with the aid of nondestructive tests or taking core samples out from theinspected structure. The purpose of the inspection is todecide the cause of the deterioration and also to evaluate
whether repair and/or strengthening is needed or not.

Considering these situations, the maintenance ofexisting structures in Japan must be done with thefollowing conditions:
1) Rapid increase of existing structures reaching the ageof 50 years after construction,2) Less amount of engineers to maintain the structures,
3) Less amount of budget to maintain existing structures.
Although there are many hazards in every country,
concrete structures are expected to be safe for long
period of time. These structures may deteriorate bymany causes including chemical reactions, physical loads,
freezing and thawing, etc., as time passes by.

To repair or strengthen the existing structures, it isimportant to design and select sufficient methods andmaterials.
The most popular repair method forcorrosion of steel bars due to carbonation is to eliminate
the carbonated concrete and replace it by new concrete
and apply coatings with and without FRP sheets. But incase of steel corrosion due to chlorides from thesurrounding environment, the high chloride concentrated
portions of concrete are taken out, anti-corrosive
treatment is applied to the surface of the bar, andIf the structure is deteriorated before the hazards, thestructure may easily collapse and it would be difficult tomaintain the safety of the people. In order to keep thesafety of urban area, it is important to study andinvestigate not only on hazards but also on durability
aspects of existing structures. Even a small amount of
concrete spalling may cause large scale traffic accidents

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 02
polymer cement mortar is generally used to repair theconcrete before coating the concrete surface.

recommended to use other countermeasures such as
Epoxy-coated bars (See Figure 1), etc...

3. Standard Specification of Concrete by JSCE
The main proposals of the “Standard Specifications
2007” are the following two items:
1) Propose a new method to design and construct new
concrete structures that can be used for specified lifetime
without large amount of maintenance cost.
2) Propose an effective and economical system tomaintain existing concrete structures with small numberof engineers and workers.
The concepts of the new Standard Specifications arebriefly explained in the following chapters.

Figure 1: Epoxy–coated steel bars used for thereinforcement of concrete slab

3.1 Durability design of concrete structures for new
structures

3.2 Methods of maintenance proposed by JSCE

Performance-based durability design was introduced
to “Standard Specification of Concrete Structures” by theConcrete Committee of JSCE in the year 2000 and betranslated to English version in 2005 (JSCE, 2005c).
Although durability of concrete structures wasconsidered important in the previous specifications,performance-based design method was not used. The
previous specifications described the importance of
durability by proposing that the concrete structures are
durable for a long time when specified materials, mixes,
covers, etc. are used. But these specifications did not
mention about the duration of service time, etc.

The methods used in the Standard Specification arebasically the same as the conventional method. The
differences are that the new method requires maintaining
the structure within their required performances
throughout their service life. Firstly, the listed below
issues have to be clearly specified.
1) To maintain a structure, performances required forthe structure must be clearly defined.
2) The performances required for general structures
are “safety”, “serviceability”, “hazards to the public”,“aesthetics and landscape” and “durability”.
And the basic principles of maintenance works are as
follows:(1) Structures must be maintained according to a
designated maintenance category by formulating amaintenance program to retain the performance within
the specified tolerances throughout their service life. And
maintenance system includes adequate “initialinspection”, “deterioration prediction”, “inspection”,“assessment/judgment”, “remedial action”, and “record”.
(2)
To maintain a structure, in addition to theassessment and evaluation at the time of inspection,assessment and evaluation must be made throughout theservice life of the structure based on prediction ofdeterioration.
(3) To predict the deterioration, required performancesof the structure must be clearly defined, and also thedesign service life must be made clear.
(4)
The records on design, construction, initialinspection, deterioration prediction, periodical inspection,assessment and/or evaluation, and remedial actions must
be kept throughout the service life.

The proposed performance-based new durability
design can be summarized as follows:
1) The concrete structure must be quantitatively
checked whether the structure possesses required
performance within the designed period.
2) The degree of deterioration of the structure inservice for a specified cause must be specified.
3) To maintain the structure above the specified
degree of deterioration, the required performance mustbe specified.
To examine the performance on durability, a kind oflimit state design scheme was introduced for the
durability of concrete structures. (For the details, pleasetake a look at the specification.)
Generally, performance of concrete has to be verified
to satisfy the required performances. Not only resistances
against deterioration but also mechanism properties ofconcrete have to be verified.
According to the specification, minimum concrete
cover thickness to prevent corrosion of reinforcing steel
differs according to the type of cement to be used, watercement ratio of concrete, years of service and exposed
condition (wet or dry) of the structure to be constructed.
When the structure is designed for long period of time,
the cover thickness may become too large, and it is

One of the difficulties is how to predict the degree ofdeterioration at the end of their service lives. There areseveral researches being done to predict the deteriorationin numerical manner.
In the published Standard,116

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 02
several numerical prediction methods are introduced as
references for structures suffering cyclic fatigue loads,
carbonation induced corrosion and chloride induced
corrosion. In case of cyclic fatigue, S-N curves areused to predict the service life. In case of carbonationinduced and chloride induced corrosion of steel bars,
diffusion equations for carbon dioxide and chloride areused to predict the degree of corrosion. Using theseprediction methods, deterioration degree can be
estimated to certain degree. But for other deterioration
problems, which has not been studied numerically, aquantitative model has not been proposed yet. To deal
with the problem, a qualitative method, namely “Grading
method”, is introduced in the Standard.
4.

Large amount of cracks were observed inside the tunnel
constructed more than 30years ago running under a river.
The inspector insisted that the cracks are formed by theground force acted on the tunnel linings due to false
concrete work during the construction.
But theinspected results show that cracks are concentrated insome specific areas. Comparing the distribution of thecracks and the settlement of tunnel, a good relation
occurred between
total amount of settlement after 30
years and the height of the ground surface (See figure 3).
From these results, the main cause of the cracks formedin the tunnel were uneven settlement of the tunnel due toconstruction of new dikes and water pools in the riverafter the construction of the tunnel.

Problems in the Actual Existing Structures

One example of the problem is as follows: When acivil engineer is asked by the owner to check the safetyof an old existing structure, one of the largest problems isthat there are neither drawings nor construction recordsof the structure available. No problem may occur incase of important facilities, which is maintained withgreat care. But in case of normal structures, the owners
do not know the importance of these documents.

Figure 3: Distribution of cracks and total amount ofsettlement of a tunnel

To deal with the problem, NDI is not enough.
Fortunately, our structures are not too old, and they aremostly designed and constructed by the method specified
by JSCE, AIJ or other associations. Considering these,
the only way is to re-design the structure again using themethodologies used at the time of construction. Figure
2 shows an example of re-designed bridge pierconstructed about 35 years ago. From the figure, it ismuch easier for a civil engineer to check the safety of thestructure under several hazards. It will become more
important for the owners and engineers to keep these
documents throughout the service life of a structure.

5. Concluding Remarks
To sustain existing structures, durability of thestructure is important. One good method is to constructdurable structures, but for the existing structures,
maintenance is the only way to deal with the problem.
Although concrete committee of JSCE has set up a goodsystem for maintenance of existing concrete structures,
there are still many things to be done: not only
researches but also education to the students andengineers about durability and maintenance.

REFERENCES[1] Concrete Committee of JSCE, Standard
Specifications for Concrete Structures-2007 “Design”.
JSCE, Tokyo.
[2] Concrete Committee of JSCE, Standard
Specifications for Concrete Structures-2007, “Materials
and Construction”. JSCE, Tokyo.
[3] Concrete Committee of JSCE, Standard
Specifications
forConcrete
Structures-2007“Maintenance”. JSCE, Tokyo.
[4] Okazaki, S., 2005. Development of monitoring
system for RC bridge based on restoration design method.
Thesis submitted to the University of Tokyo for Masterof Engineering degree.
[5] Uomoto,T., Katsuki, F., Takeuchi, M., Suzuki, S.;
Effect of Surface Structures on Underground Concrete
Tunnels, 2009

Figure 2: Re-designed reinforced concrete pier of abridge (Okazaki, 2005)[4]Another problem is that the inspectors may makemistakes in deciding the main cause of the deterioration.
One example is shown below.

117

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 37

NATURE OF THE CORROSION PRODUCTS IN TENSIONED REINFORCING BARS
P.K. BEHERA1, P.K. KATIYAR2, S. MISRA3 and K. MONDAL4
1

PhD student, Department of Civil Engineering, IIT Kanpur, Kanpur, India, bprasannakumar99@gmail.com

2

PhD student, Department of Materials Science & Engineering, IIT Kanpur, Kanpur, India, prvan@iitk.ac.in

3

Professor, Department of Civil Engineering, IIT Kanpur, Kanpur, India, sud@iitk.ac.in

4

Professor, Department of Materials Science & Engineering, IIT Kanpur, Kanpur, India, kallol@iitk.ac.in

Keywords: Reinforcing bars, reinforced concrete, corrosion, tensile stress, accelerated tests, test method
INTRODUCTION

products were monitored over a period of time using
various techniques, such as polarization resistance,
FTIR spectroscopy, etc.

Corrosion of reinforcing bars in reinforced concrete(RC) has attracted the attention of both – structural
engineers and corrosion scientists. It is now known that
corrosion results in the formation of different corrosion
products on the surface of rebar, depending on several
factors such as the state of the steel surface, availabilityof oxygen and water, nature of the surrounding
concrete, etc. Study on the evolution of different
corrosion products and how the composition of theserusts affect the critical corrosion for the onset of
longitudinal cracks were carried out by Behera et al.
[1]. Further, several studies have been carried out toestablish the mechanism of corrosion and thetransformation of corrosion products over a period oftime. It has been established that the ratio of α/γ* (i.e.
α-FeOOH / (γ-FeOOH + β-FeOOH + Fe3O4)) influences
the further degradation of steel [2]. One other factor thathas been explored to some extent, especially in thecontext of high strength steel wires and strands in prestressed concrete construction, is the effect of stresslevels and composition and properties of the steel on its
susceptibility to corrosion [3]. It is interesting to notethat though reinforcing bars in normal reinforced
concrete construction are also subjected to reasonably
high levels of tensile strains inside concrete, virtuallyno published material is available on the effect ofstresses on corrosion susceptibility. It should be notedthat apart from the action of structural loads, tensilestresses in bars may arise due to bending and cranking,even before the bar is embedded in concrete.

RESULTS AND CONCLUSIONS
The results indicate that the behavior of stressed andunstressed samples is quite different, and the level oftensioning also affects various aspects of corrosion.
The results highlight the importance to carry out
more extensive work in the area to better understand thecorrosion in different segments of steel within any RC
structure, and validate the results from sampling anddata collection from the field.
ACKNOWLEDGEMENT
The support of staff in different laboratories at IIT
Kanpur is gratefully acknowledged.
REFERENCES[1] Behera, P.K., Moon, A.P.K., Mondal, K., and Misra,S., (2016), J. of Materials in Civil Engineering, ASCE,
V.28, No.12, p. 04016158-1-12.
[2] Choudhary, S., Garg, A. and Mondal, K., (2016), J.
of Materials Engineering and Performance, Springer,
Vol. 25(7), pp.2969-2976.
[3] Lee B.Y., Koh K.T., Ismail M.A., Ryu H.S. andKwon S.J., (2017), Advances in Materials Science andEngineering, Article ID 8575816.

EXPERIMENTAL DETAILSThe mild steel bars were stressed to different levels
and subjected to accelerated corrosion using standard
salt-fog chambers with an appropriately designed
wetting and drying cycle. The corrosion and corrosion

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 51

EXPERIMENTAL INVESTIGATION ON HEALING OF MICROWAVE-HEATED BITUMINOUS
CONCRETE MIXTURES
N. S. L. APARNA1, K. SUDHAKAR REDDY2
1

Doctoral research scholar, Department of Civil Engineering, Indian Institute of Technology Kharagpur, Kharagpur,
India, lakshmiaparna93@gmail.com
2
Professor, Department of Civil Engineering, Indian Institute of Technology Kharagpur, India,ksreddy@civil.ernet.in
Keywords: Fatigue cracking, self-healing, Microwave heating, Indirect tensile strength
1. INTRODUCTION
India, with a wide road network of 56.03 lakh
kilometer [1], has majority of its roads constructed as
flexible pavements with bituminous mixtures. Major
distresses in these pavements include permanent
deformation (rutting) along wheel path and fatigue
cracking originating both from top and bottom of thebituminous layers. Fatigue cracking occurs mainly due tothe repeated application of loads. It not only reduces theload carrying capacity of the pavement but also
aggravates the damage due to ingress of moisture into thepavement through the cracks. Thus, these cracks need to
be sealed / repaired periodically for better performanceof pavement. Bituminous mixes have the intrinsic
property of healing the damage with time andtemperature and thus are expected to heal by themselves
during hot summers and long rest periods resulting in theextension of service life. Self - healing of bituminous
mixtures depends on several factors which mainly
include the climatic condition of the pavement which ispractically difficult to control.
Thus, improving the self - healing capability ofbituminous mixtures is an area that caught the attentionof several researchers. As self – healing increases withincrease in the temperature of mix, inducing heat into the
mixture is proven to be a feasible way of improving
healing [2, 3]. Heating by means of induction heating
and microwave heating have been explored byresearchers to enhance the healing characteristics ofbituminous mixtures. The present study aims at using
microwave heating, a faster heating method and which
produces smaller thermal gradients [4], for healing ofbituminous mixtures with different rest periods.

1200 W at full power was used as the source formicrowaves (Figure 1).
Table 1: Properties of binder used in present study
Property

Value

Penetration

38 penSoftening point

55 oC

Ductility>100 cm

Mixing temperature at viscosity of 170 cP

170 oC

Compaction temperature at viscosity of
280 cP

157 oCA split mould fabricated with 1.5 mm thick aluminum
sheet with a suitable base plate was used to hold thespecimens for keeping them in the microwave oven sothat only the upper surface is exposed to the penetrationof microwaves and thus simulating the practicalcondition of heating in the field.

Figure 1: Microwave oven with single split mould
2.2 Sample Preparation
Marshall method of compaction with 75 blows on eachface of the specimen (recommended for high volume
roads by Asphalt Institute MS-2) was used to compact
the mixture containing aggregates, binder and additive.
Steel wool was chopped into smaller pieces (3 mm – 5mm) and added to the mixture of aggregates and bitumen.
Mixtures were prepared to have a design air void content
of 4% and steel wool (5% by weight of binder was added
to the mix. Cylindrical samples of 100 mm diameter
were cast for healing study.

2. EXPERIMENTAL METHODS
2.1 Materials and Equipment
The binder used in this study was graded as VG40
as per IS 73 2013 and was supplied by Jalnidhi bitumen
Ltd. Table 1 gives some properties of the binder used.
BC 2 aggregate gradation was used to prepare the mixes
according to [1] and the aggregates used were of basaltic
nature. To improve the microwave absorbing capabilityof mix, steel wool of grade 000 (diameter of 0.035 mm)
was selected as an additive after some preliminary
investigations as it has higher microwave absorption
compared to other coarser grades and is easier to mix. A
microwave oven (Bajaj 1701MT DLX), capable ofproducing microwaves with 2.45 GHz frequency, rated

3. EXPERIMENTAL METHOD
3.1 Healing cycle
Experiments in this study were conducted in three phases.
They are; testing of samples to measure Indirect Tensile119

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 51
Strength (ITS) followed by heating and further healing of
the broken samples and testing the healed samples tomeasure ITS as described below.
The characterization of bituminous mixtures in terms ofindirect tensile strength was done by the Marshallspecimen along a diametric plane at a constant rate of 51
mm / min. acting parallel to and along the vertical
diametrical plane of the specimen through two loading
strips as per ASTM D 6931. The broken samples were
kept inside the split mould and placed inside themicrowave oven maintained at full power. Temperatureof the exposed top surface was measured at regularintervals till it reached a range of 95 oC to 100 oC. The
samples were taken out of the oven and were removed
from the mould and allowed to heal for different
durations; 3, 18 and 24 hours. The recovered indirect
tensile strength at the end of the healing period strength
at the end of rest period was measured. Immediately after
heating, images were also taken with an Infrared cameraon the top surface of the samples and along the depth toobserve the heating uniformity.

terms of the temperature gradient from top surface tobottom surface. There exists an average gradient of 30 oC
over a depth of 60 mm. Figure 2 shows the temperature
profile on the top surface of the heated sample inferring
the basic heating phenomenon of microwave i.e.,
generation of heat from within.
4.3 Healing properties
Effect of healing periods on healing efficiency of
mixtures was studied and table 3 shows that withincrease in rest period, healing index was increased.
Table 3: Healing indices after different rest periods[1]

St = IDT strength, kPa
P = Maximum load, N
T= Specimen height immediately before test, mm
D = specimen diameter, mm
ii. Healing index: The healing index of each sample
at the end of each healing cycle, HI was defined as
the percentage of ITS recovered at the end ofhealing cycle.
HI = (ITSf / ITSo) X100

Healing

ITSf

Healing

index

=

(kPa)

period (hr)(kPa)

(ITSf / ITSo) X100

1168
1211
1190

3
18
24

605
833
866

(%)

52
69
73

CONCLUSIONS The feasibility of heating bituminous mixes by
microwave method has been demonstrated in thisstudy. An average temperature gradient of 0.5 oC/mm was also observed along the depth of thespecimen.
 The duration of healing period has been found tohave an effect on the healing characteristics of themixes.
 The information generated from the present study
will be useful for identifying the conditions to be
adopted for microwave heating and healing of thecracks in field bituminous layers. For this, it ishowever required that a more detailed laboratory
investigation is to be done followed by field
validation of this recommended conditions.
 Enhancement of healing by Microwave heating
would not only increases the serviceable life of thepavement and reduces the life cycle cost but also
aids in sustainable construction and maintenancepractices by reducing the waste generated due tothe milling of cracked pavement.
REFERENCES

3.2 Parameters evaluated̠ from the experiments
i. Indirect tensile strength: Indirect Tensile Strengthof bituminous mixtures is calculated as follows.
(ASTM D 6931)
St = 2000P / (π x T x D)

ITSo

[2]

ITSf = ITS of the sample after healing
ITSo = ITS of normal sample
4. ANALYSIS AND DISCUSSION
4.2 Heating properties
The average time required for bringing the surface
temperature of the mix to 95 oC to 100 oC with themicrowave oven used in the study is 4.5 minutes.
Uniformity of heating along the depth was measured in[1]Ministry of Road Transport Highways “Specifications
on Road and Bridge works” (2013), fifth revision.
[2] Liu, Q., Schlangen, E., van de Ven, M., van Bochove,G., van Montfort, J., (2012) “Evaluation of the induction
healing effect of porous asphalt concrete through four
point bending fatigue test” Constr. Build. Mater. 29,403e409.
[3] Menozzi, A., Garcia, A., Partl, M.N., Tebaldi, G.,
Schuetz, P., (2015) “Induction healing of fatigue damage
in asphalt test samples”. Constr. Build. Mater. 74,
162e168[4] Gallego J., Val M. A., Contreras V. and Paez A.
“Heating asphalt mixtures with microwaves to promote
self-healing.” Constr. Build. Mater., 42, 1-4, 2013.

Figure 2: Infrared image of a heated sample

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 80

STUDY OF FRESH AND HARDENED PROPERTIES OF CONCRETE IN PARTIAL
REPLACEMENT USING FLY ASH AND LIMESTONE POWDER
M.C. YUVANKARTHICK1, M. ANANTHKUMAR2, and S. BARATHI KUMAR3
1

Student, Civil Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, yuvankarthickmc@gmail.com
Assistant Professor, Civil Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu,
m_ananthkumar@cb.amrita.edu (corresponding author)
3
Student, Civil Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, barathifdr@gmail.com
2

Keywords: Fly ash, limestone powder, flexural strength, compressive strength, workability,for 24 hours and after 24 hours it was demoulded andwas placed for curing. The concrete specimens were
cured for 1day, 7days and 28days, in order to determine
1day, 7 days and 28 days compressive strength. The test
on fresh concrete i.e. the slump cone test was done
immediately after mixing of concrete in the concrete
mixer.

1. INTRODUCTION
In the modern world the demand for cement has
increased dramatically since being the important
constituent of widely used concrete. The production of
cement causes co2 emission and degradation of natural
resources. To reduce this effect partial replacement of
cement with various supplementary cementitious
materials are carried out. One of them is fly ash. It wasnoted that fly ash usage reduces early strength,
workability and increases high heat of hydration. Thus, tocounteract these effects we introduced super plasticizers.
In our study we tried to make the concrete moresustainable by using fly ash and limestone powder alongwith other usual materials of conventional concrete. A
total of 9 concrete mixes were taken by varying thepercentage of limestone powder, fly ash, cement and fineaggregates. Tests were conducted to asses workability,
compressive strength, density and flexural strength.

Testing of samples:Workability- To find the workability of the sample slump
cone test was conducted. Freshly prepared concrete wasfilled in the cone shaped container with three-layer
tamping. Slump was measured by noting the differencein height to that of mould.
Density- It was calculated as the ratio of weight byvolume of the hardened concrete specimen.
Compressive strength- the concrete cubes was tested withthe help of Compressive Testing Machine. Once theconcrete block fails and the load at which the failure
occurs is displayed on the dial, the machine functioning
is stopped. Compressive strength was calculated as theratio of failure load by area under compression.
Flexural strength- the specially cast flexural beams wereused. It was tested with the help of Flexural Testing
Machine. Once the concrete block fails and the load at
which the failure occurs is displayed on the dial, themachine functioning is stopped.

2. MATERIALS
Ordinary Portland cement, fine aggregate, coarse
aggregate, fly ash, limestone powder.
3. METHODOLOGY
Concrete mix design:
The concrete mix design was done for M30 grade
concrete. And the resultant ratio was found out to be 1:
1.34: 2.87 by weight. To study the influence ofLimestone and fly ash in concrete, ten different mixes
including one control mix were used. S- controlled mix
0% L (limestone powder) and 0% F (fly ash),
M1-15%L 0%F, M2-30%L 0%F, M3-0%L 25%F,
M4-0%L 50%F, M5-15%L 25%F, M6-15%L 50%F,
M7-30%L 25%F and M8-30%L 50%F.

4. RESULTS
Workability:
The concrete mixes with fly ash alone showed
reduced workability and limestone powder replacement
alone showed slight improvement in the workability
compared to that of control mix. The mixes with both
limestone powder and fly ash replacement (M5, M6, M7
and M8) showed changes based on the percentage of
replacement. The workability was maximum at M6(15%L & 50%F) among the mixes with both cement andfine aggregates partially replaced.
Table 1: Workability variation in milli meters (mm).
Mix
S
M M M M M M M M
design
1
2
3
4
5
6
7
8
Worka 76 77 82 30 5
58 62 41 45
bilityCasting and curing of concrete specimen:
Nine concrete cubes of size 150x150x150mm were
casted for each of the above mix, to check forcompressive strength and density of concrete. Threeflexural beams of dimension 750x100x100mm were
casted for each mix. The concrete specimens were casted
using steel moulds and compacted using needle vibrator.
The cast specimen was kept in an ambient temperature121

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 80
workability to a usable range. The usage of limestone
powder to improve workability is viable and economical
option as limestone is a raw material already available inthe cement industries. Density did not vary much ascompared to that of conventional concrete. The
compressive strength of the mixes with fly ash
replacement alone showed good improvement. All themixes with both limestone powder and fly ash showed
better strength almost at all stages compared to thecontrol mix. M6 showed the highest strengths among themixes with both fly ash and limestone. The 7 days
strength and 28 days strength showed an improvement of
38% and 34% in compressive strength respectively. The
flexural strength among the concrete with both thereplacement materials (LS & FA) reached its maximumin M6 concrete. The flexural strength was 4.96 MPa at 28
days of curing which is 24% increase compared to theconventional concrete.
Hence M6 concrete can be used in structural
construction without any loss in strengths. This also
improves the energy efficiency of the concrete, reduces
the CO2 emission and improves fly ash usage.

Density:
The density of the hardened concrete can explain themechanical properties of the concrete to some extent. M5
is found to be higher for both limestone powder and fly
ash replacement.
Table 2: Density variation.
Mix
S
M1
M2
designDensity 2530
2539
2524
(kg/m2)
M5
2532

M6
2515

M7
2521

M3

M4

2527

2515

M8
2513

Compressive strength:
Compressive strength of the hardened concretes wastested using compression testing machine at stages of 1day, 7 day and 28 day to understand the strength gain of
the concrete. M6 was found suitable with the highest
strength after 7 days, 28 days and comparatively equal
strength after 1 day. It was also greater then theconventional mix after 28 days.

REFERENCES

Table 3: Compressive strength variation for 1, 7 and 28
days in (Mpa).
Mix
S
M M M M M M M M
Design
1
2
3
4
5
6
7
8
1 day
23 25 24 22 21 24 23 22 22
7 days31 31 31 38 43 37 42 38 37
28 days 40 40 37 52 59 49 54 45 57[1] Parvati V. K and Prakash K.B, (2013) “Feasibility
Study of Fly Ash as a Replacement for Fine Aggregate inConcrete and its Behaviour under Sustained ElevatedTemperature,” International Journal Of Scientific &Engineering Research, Vol.4, Issue 5, pp 87-90.
[2] Rafat Siddique, (2002) “Effect of fine aggregate
replacement with Class F fly ash on the mechanicalproperties of concrete,” Cement and Concrete Research,
Vol 33, pp 519-547.
[3] Shirish V. Deo1and Arun D. Pofale2, (2015)“Parametric Study for Replacement of Sand by Fly Ashfor Better Packing and Internal Curing,” Open Journal of
Civil Engineering, Vol 5, pp 118-130.
[4] Dale P. Bentz, Taijiro Sato, Igor de la Varga and W.
Jason Weiss, (2012) “Fine limestone additions to regulatesetting in high volume fly ash mixtures,” Cement &Concrete Composites, Vol 34, pp 11–17.
[5] A Jayaraman, (2014) “Experimental Study on Partial
Replacement of Natural Sand with M- Sand and Cementwith Lime Stone Powder,” International Journal of
ChemTech Research CODEN (USA): IJCRGG ISSN:
0974-4290, Vol.6, No.2, pp 948-954.
[6] Dale P. Bentz, Ahmad Ardani , Tim Barrett , Scott Z.
Jones, Didier Lootens, Max A. Peltz , Taijiro Sato, Paul
E. Stutzman , Jussara Tanesi and W. Jason Weiss, (2014)“Multi-scale investigation of the performance of
limestone in concrete,” Construction and Building
Materials, Vol.75, pp 1–10.
[7] Rafat Siddique, (2014) Utilization of industrial
by-products in concrete, Procedia Engineering, Vol 95,
pp 335-347.

Flexural strength:
Flexural strength of the concrete with limestone powder
replacing cement is low at 28days compared to theconvention control mix. On the other hand, fly ash
replacement improved the flexural strength linear to its
content. In the mixes with limestone and fly ash
replacement, the strength improved for fixed limestone
and varying fly ash content. The flexural strength ismaximum for M6 with 15% L and 50% F (4.96 MPa).
Table 4: Flexural strength variation in (Mpa).
Mix
S
M1
M2
M3
DesignFlexural 4
3.36
2.88
5.12
strength
M5
4.48

M6
4.8

M7
3.68

M4
5.6

M8
3.84

5. CONCLUSION
The workability of concrete mix containing fly
ash alone was very low. But on the addition of superplasticizer like limestone powder improved the122

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 46

A CASE STUDY OF EXTRADOSED CREEK BRIDGES IN WESTERN COAST OF INDIA
Mohammed Younus Ahmed1
1

Manager, Transportation Roads and Bridges (TRB),Voyants Solutions Pvt. Ltd., Hyderabad, India, eMailengrahmed786@gmail.com
Keywords: Cable-stayed bridges, Extradosed Bridge Synamic analysis Creek Bridge
1. INTRODUCTION
During the past decade , Extradosed bridge
construction has experienced an upsurge in India . Extradosed bridge range from spans 125m to 250m .As
navigation is compulsory through the Creek . Four creek
bridges namely at Dighi (2.875 km) , Dabhol (1.204
km )and Jaigad (2.650) on the western coast of India
have been proposed with extradosed span . Each on thecreek bridge have been given extradosed span of 160m inthe middle of the bridge .
The pylon height above the deck level is 36m . The
difference between the bed level and the normal waterlevel throughout the year is 15m -17m, a verticalclearance of minimum 12.5m is required for navigationof ships . The bridges are provided with pile foundation
and are falling under India’s second highest seismic zone
i.e. Seismic Zone IV . The soil strata upto a depth of 20m
is completely sand.
The bridges are designed with cantilever construction
method. The structural behavior response spectrum
analysis , eigen value analysis, deflections , cable stayforces are compared
A Extradosed bridge, which is intermediate to Girder
Bridge and a cable stayed bridge, adds substantial
prestress to the deck because of the shallow pylon, arefound to be economical for spans upto 250m. Dynamic
response prediction has been the matter of research formany authors, in particular as the structural design ofmany structures is governed by the earthquake load cases
or combinations thereof.
The intrados is defined as the interior curve of an arch, orin the case of cantilever-constructed girder bridge, thesoffit of the girder. Similarly, the extrados is defined as
the uppermost surface of the arch. The term ‘extradosed’
was coined by Jacques Mathivat [1] to appropriately
describe an innovative cabling concept he developed for
the Arrêt-Darré Viaduct , in which external tendons wereplaced above the deck instead of within the cross-section
as would be the case in a girder bridge. To differentiatethese shallow external tendons, which define the uppermost surface of the bridge, from the stay cables found ina cable-stayed bridge, Mathivat[1] called them‘extradosed’ prestressing.
Some features of extradosed bridge as given below:• External appearance resembles
cablestayed bridge – but structural characteristics
are comparable
to
those
of
conventional girder bridge

•
•

•
•

The Girder Depth are lesser than that ofconventional girder bridges
The stay cables (prestressing tendons outside
the girder) need no tension adjustment
necessary for cable-stayed bridges, and can betreated as usual tendons as in girder bridges
The height of pylon is half as that of cablestayed bridge and hence easier to construct
With small stress fluctuation under live load
the anchorage method for stay cables can besame as that of tendons inside girder andthereby achieve economy.

Figure 1: Figure showing cable arrangement for
Girder, Extra- dosed and cable stayed bridge
The reduced cable inclination in an extradosed bridge
leads to an increase in the axial load in the deck and adecrease in vertical component of force at the cableanchorages. Thus, the function of the extradosed cables
is also to prestress the deck, not only to provide verticalsupport as in a cable-stayed bridge. Extradosed bridges
are characterized by a low live load stress range in thestay cables.
With the rapid increase in span length, combined trend
and also trend of using high strength materials have resulted in slender structures and a concern is being raisedover dynamic behavior of such structures, in case of cable supported structures it is more pronounced as thisfurther includes vibrations of cable elements also. An
accurate analysis of natural frequencies is fundamental to
the solution of its dynamic responses due to seismic andwind and traffic loads.
2. HIGHLIGHTS ON STATIC BEHAVIOUR
The basic difference between cable stayed
bridge and Extradosed Bridge is its tower height. As per[2] For the span to tower height ratio is generally kept at
4-5, whereas for Extradosed Bridge it is 5-8, whichmeans Extradosed bridges The stiffer the tower will
enable the use of the full range of effective depth of123

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 46

cross-section. Since the short towers act as cantilevers,
effectively prestressed by the dead load of the girder
acting through the cables, they require relatively little
reinforcement to resist bending due to live load. Neither
a flexurally stiff girder nor backstays are required inorder to provide adequate system stiffness to control
deformations due to live load. With short towers, larger
stay cables are required, but the towers are more
economical than the tall towers normally found in cablestayed bridges. The methods of providing stiffness in
cable supported structures are shown in figure 2

a live load stress range between 30 MPa and 100 MPa
and are not sensitive to wind vibrations. These
specifications resulted from a need for design
recommendations for bridges that do not fall into distinct
categories, and they propose design limits andapproximations based on rational principles. This
explains use of 0.6fu allowable stress in the Extradosed
cables, which leads to material economy.
3. FREE AND FORCED VIBRATION ANALYSIS
Research methodology:
To study dynamic behaviour of Extradosed Bridge, 3
numbers of models with variable parameters are prepared.
Basic span configuration as applicable for Extradosed
span is selected to be 125, 150 and 260m main span, theside span is about 0.5 of main span. The pylon height isvaried from 5.7 to 6.2 to account for the effect ofvarying cable inclinations. The cable inclination varies
from 17 to 30 degrees. The requirement of cable area andprestressing is as per preliminary design. Box beam
superstructure is adopted with solid rectangular pylon
designed by Limit State Design as per IRC 112:2011[4].
For details of model refer table-1.
Table 1: Details of Extradosed Bridge used in study
S.no Span(L)/
Pylon
Remarks
configuration(m)
ht
(H)
(m)
1.
62.5+125+62.5
22
On pile(Concrete deck)foundation,
21m widedeck2.
75+150+75
36
On pile(Concrete deck)foundation,
21m widedeck3.
110+260+110
45
On pile(steel deck)foundation,
21m widedeck
The dynamic response of structure for free vibrations
as well as forced vibration has been studied. Software
Midas 2018 [5] has been verified and used in the study.
Deck is modelled as Euler Bernoulli Beam and the stay
cables have been modelled as single truss elements instatic/ dynamic analysis.
4.0 Free Vibrations of Extradosed Bridge
With the rapid increase in span length, combined trend
and also trend of using high strength materials have resulted in slender structures and a concern is being raisedover dynamic behaviour of such structures, in case of cable supported structures it is more pronounced as thisfurther includes vibrations of cable elements also. An accurate analysis of natural frequencies is fundamental to
the solution of its dynamic responses due to seismic andwind and traffic loads. The modal shapes and frequencies
for above listed models are presented below;

Figure 2: Response of cable supported bridge to live
loads
SETRA [3] published recommended allowable stresslimits that cover the full range of external cables. In that
document, external prestressing tendons are defined as
being subjected to a stress range of up to 15 MPa underlive load while stays for cable-stayed bridges are
subjected to a stress range of around 100 MPa and above.
Extradosed cables are characterized as being subjected to124

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 46

Figure 6: Mode 1 for span 75+150+75, T=1.09s

Figure 3: Mode no vs. time period in sec for62.5+125+62.5 extradosed bridge
Figure 7: Mode 2 for span 75+150+75, T=0.87s

Figure 8: Mode 3 for span 75+150+75, T=0.58s
Figure 4: Mode no vs. time period in sec for
75+150+75 extradosed bridge

Figure 10: Mode 4 for span 48+120+48m, T=0.52s

Figure 5: Mode no vs. time period in sec for
110+260+110m extradosed bridge
The first 5 mode shapes are presented below for one of
the model
Figure 10: Mode 5 for span 75+150+75, T=0.43s

12517th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 46

5.0 Free Vibrations of Extradosed cables
Each stay cable is analyzed as an inclined stay cable
fixed & pinned at both ends to evaluate the natural frequencies of local vibrations. It is noted however that thereal situation is slightly different, as the end anchorages
themselves are movable. The first symmetric and antisymmetric in-plane transverse vibration frequencies arecomputed considering pinned and fixedend
conditions. The results are summarized in fig 11 and fig
12.

coupled vibration modes cannot be predicted by
Equations. For investigating the possibility of coupledmode of vibration the time periods for various modes ofvibration are superimposed for structure and cables
6.0 Forced Vibrations of Extradosed Bridge
Forced vibration is studied for selected earthquakes;
the earthquakes selected were having different
characteristics as given in table 1
Table 2: Details of Earthquakes time histories
Name
Magnitude Duration PGATime for
(sec)
Value
PGA
(g)
Value(sec)
Koyna

6.5

7.02

0.49

2.60

(1967)
Bhuj

6.9

120

0.30

39

(2001)
El-

7.2

40

1.61

2.48

CentroThe time history analysis for these was performed on(1940)
selected models and force effects at various points wererecorded
7.0 Non-Dimensionalizing of parameters
Forced vibration analysis for three earthquake time
histories having different characteristics are undertaken.
To compare the results all parameter have been non
dimensionalised using equivalent factors as mentioned
below;

Figure 11: Mode no Vs Time period (s) for structure
and cables for 62.5+125+62.5m Extradosed bridge

Where, V & M are non dimensioning factors for shear
force, bending moment.
Where, ρ= Mass Density,
g= Gravitational acceleration,
A= Cross section area of component and L= Half span
length of the component.
Span and pylon height are non-dimensionlalized byusing parametric length. The results obtained from thetime history analysis in terms of bending moment andshear forced in the structure are non-dimensionalised andsuperimposed and presented in Fig 13 to 18

Figure 12: Mode no Vs Time period (s) for structure
and cables for 110+260+110m Extradosed bridge
By looking at the mode shapes of the stay cables, it ispossible to relate these natural frequencies of the“”fixed/free end’’ cables to thoseobtainedbyanalyz- ing the whole bridge using the finite element
method. The results are shown in fig 12 & 13. Apartfrom those natural frequencies that are obviously outside
the range under consideration, all local cable vibrations
can be re- flected by finite element analysis withmultiple-element modelling of stay cables. In addition to
those pure lo- cal vibrations of stay cables, some new
frequencies are also discovered indicating strongly theexistence of cou- pled vibration modes. Obviously, theseFig 13. Variation of bending moment acrossspan for 110+260+110m span (Non-dimentionalized)126

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 46

Figure14: Variationofbending
momentacross span for 75+150+75 span (Non-dimentionalized)
Figure 18: Variation of bending moment across pylon
height for 62.5+150+62.5 span (Non-dimentionalized)

Figure 15:
acrossspandimentionalized)

8.0 Forced Vibrations of Cables
Cable excitations can be caused by rain, wind,stochastical vibration due to plying vehicles orparametric vibrations
due to vibration of the deck. Due to the infinite
number of damping values and angles of inclination thata ca- ble may take, several values can be selected torepresent typical cables. It is evident that zones of largeamplitude cable vibrations do tend to change withvarying angles of inclination, when the geometric
nonlinearity of the cable lessens, as the angle ofinclination moves towards 90. Also, the onset of theseregions of large-amplitude cable vibrations required
higher amplitudes of cable end excitation as the dampingof the cable increases.
It was considered important that the stochastic excitation or parametric excitations, which may be occur due
to various reason, but the main reason being the vehicles
plying on the bridge, which was to be imposed on thecables, be representative of a prototype stochastic timehistory that might be imposed on a stay by a full-scale
cable structure such as an extradosed bridge. Even
though an approximation, cable structures, such as
telecommunications masts and cable-stayed bridges, aresubject to random wind forces, which have time-histories
that are very similar to random normal distribution, forthe low- frequency bandwidth under examination. An
extradosed bridge or other similar structure will act as asignal filter, by filtering wind signals (or white noise
signals) through its own structural characteristics. The
resulting dynamic response input will be the actual
response of the structure to the wind load. This filteredsignal or structural response can then be used as astochastic time-history (stochastic support excitation) forthe examination of a cable’s response to that time-history.
As the wind will have varying characteristics, such as
wind speed and wind direction, the force acting on the
structure will also have varying characteristics. These
will excite the structure at different frequencies withvarying amplitudes of force.

Variation of bending momentfor 62.5+125+62.5 span (Non-Figure 16: Variation of bending moment across pylon
height for 110+260+110 span (Non-dimentionalized)

Figure 17: Variation of bending moment across pylon
height for 75+150+75 span (Non-dimentionalized)127

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Paper No. 46

9.0 DISCUSSIONSFree Vibrations: - An accurate analysis of natural frequencies and mode shapes of cable supported structures
such as Extradosed Bridge is fundamental to the solutionof its dynamic responses due to seismic, wind and trafficloads. Now days, from economic considerations, the stay
cables are often closely spaced, with the cable lengths
and tensions gradually varying from position to position.
The natural frequencies of their self-vibrations are therefore rather closely spaced. This may cause boundaryinduced vibrations of the stay cables. This complicatesthe overall dynamic behavior of cable stayed structures.
In addition to pure local vibrations of stay cables, some
new frequencies are also present indicating strongly theexistence of coupled vibration modes, these coupled vibration modes cannot be predicted by equations. The
frequencies of cables with actual boundary conditions are
expected to lie in-between those of with fixed and pinned
ends. For investigating the possibility of coupled modeof vibration the time periods for various modes ofvibration are superimposed for structure and cables. Theintersection zone (intersection of stay cable vibrations
and bridge vibrations) suggests the possibility of coupledvibrations.

[5]Midas Civil 2018 – Software for Bridge Structural
Analysis
http://en.midasuser.com/product/civil_overview.asp

Forced Vibrations: - Forced vibration studies of deck
and pylon of three types of bridges reaffirms following
facts for extradosed bridge:
1) Magnitude of bending moment / shear force isdirectly proportional to the magnitude offorcing function / PGA.
2) With increase in the distance between cables
ssuupp-- ports the shear force in deck also
increases.
3) Pylon stiffness does not have any effect on thedeck moments/shear.
4) With increase in the pylon height/slenderness
the shear force changes its sign in the upper partof pylon.
5) It is observed that only for cable stayed bridgewith harp shape cable arrangement the shear
force reduces at the junction of deck
REFERENCES[1] Katsuhiko Takami and Sumio Hamada (2005);
Behavior of extradosed bridge with composite Girder;
ASCE / Journal of Bridge Engineering.
[2] H. Otsuka, T. Wakasa, J. Ogata, W. Yabuki and D.
Takemura(2003);
Comparison
ofstructuralcharacteristics for different types of cable-supported
prestressed concrete bridges; Structural Concrete Mar2002.
[3] “External prestressing”, Recommendations,
SETRA, Bagneux, February 1990
[4]IRC-112 2011 Code of practice for design ofreinforced concrete bridges

12817th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 50

EFFECT OF ASPECT RATIO ON COLLAPSE MECHANISM OF RC STRUCTURES:
COMPARING DAMAGE PATTERN USING STATIC PUSHOVER ANALYSIS
A.VIMALA1 and R. PRADEEP KUMAR2
1
2

Professor, Head Department of Civil Engg., AGI, Hyderabad, India, vimalace@cvsr.ac.in (corresponding author)
Professor, Head, EERC, IIIT Hyderabad, India, ramancharla@iiit.ac.in

Keywords: Aspect Ratio, Pushover analysis, Expended energy, Global damage
ABSTRACTReinforced concrete frame buildings have been widelyconstructed in seismic-prone regions Worldwide. Undera given earthquake, the level of damage to a structure isgreatly influenced by nonlinear capacity of its members.
Even when the nonlinear capacities are same, the overall
damage is critically influenced by the structure’s shape,size and geometry.
Present study assesses the nonlinear performance of
the RC frames with different aspect ratios (3, 1 and 0.3).
Performance assessments indicate that the structure withan aspect ratio (height to width) 3 shows ground floor
mechanism and sudden failure observed after ultimatebase shear. The structure with an aspect ratio of 1 shows
first and second storey mechanism simultaneously andshows good ductile behavior in nonlinear state. The
structure with an aspect ratio of 0.3 significantly changes
the collapse mechanism of the frame structure, leading toa third story mechanism and also shows good ductile
behavior after ultimate base shear. The results arecompared in terms of damage, displacement and plastic
hinge pattern.
1. INTRODUCTION
To study the damage profile by applying energy based
damage methods, numerical study is carried out for threereinforced concrete structures. These structures are
considered to represent low and medium rise RC
buildings and the structures are chosen in such a way that
their aspect ratio (height to width) is about 3, 1 and 0.3.
To quantify the damage many damage models are prop
osed in literature, they are classified broadly as local dam
age indices and global damage indices; the former quanti
fy damage in individual members, at individual joints or
at a particular cross section, and the latter damage in thewhole structure [1]. A detailed review of damage indicesis available in literature [2][3].
Pushover analysis is a simplified procedure for seismic
performance evaluation of structures. The ATC-40 [4]and FEMA-356 [5] documents have developed modelingparameters, acceptance criteria and procedures of
pushover analysis. Krawinkler and Seneviratna [6]pointed out that a carefully performed pushover analysis
would provide insight into structural aspects that control
performance during earthquakes. Pushover analysis
methodologies are under continuous development. Gupta
and Kunnath [7] presented an adaptive pushover method
in which external force profile is adjusted in eachanalysis step taking into account the structure’s current
dynamic characteristics. Goel and Chopra [8] developed

a modal pushover analysis (MPA) which accounts for thecontribution of higher modes by conducting separate
pushover analyses with external force profile
proportional to the structure’s significant modes.
Mohamed Abdel-basset [9] proved that displacements
and curvatures derived from non-linear static response
can be used as good damage indicators even for a small
amount of damage. Kotanidis and Doudoumis [10]proved that the area under the classic pushover curve(base shear Vs roof displacement) could lead to incorrect
estimation of the amount of energy which the structure isable to dissipate.
2. DETAILS OF STRUCTURES
Both, 11 and 4 story buildings are 15 m by 15 m inplan (Figure 1). Their typical floor-to-floor height is 4m.
The interior frame, as shown in figure 1(a), represents 2D models of these buildings. The other 4 storey building
is 50 m by 15 m in plan (Figure 1) and its floor to floor
height is 4 m. The interior frame, as shown in figure 1(b),represents a 2-D model of the buildings.
Buildings are designed according to Indian codes ofpractice for plain and reinforced concrete, IS: 456 andearthquake resistant design IS: 1893. The buildings are
assumed to be situated in seismic zone V of IS: 1893–
2002, with an intensity of 0.36g ground acceleration.
Material properties are assumed to be 20 MPa for theconcrete compressive strength, and 415 MPa for steel
yield strength, for both, longitudinal and transverse
reinforcements.
The 11 storey-3 bay frame is 44m in elevation (Figure2). Beam, column dimension, amount and arrangementof longitudinal and transverse reinforcement are shownin figure 2. The 4 storey-3 bay frame is 16m in elevation(Figure 3). Beam, column dimension, amount andarrangement of longitudinal and transverse reinforcement
are shown in figure 3. The 4 storey-10 bay frame is 16m
in elevation (Figure 4). Beam, column dimension,amount and arrangement of longitudinal and transverse
reinforcement are shown in figure 4.

(a)

129

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 50(b)Figure 1: (a) Plan view of 11 and 4 storey buildings(b) Plan view of 4 storeys 10 bay building(c) Beam-Column reinforcement detail
Figure 2: Properties of frame-2 (4 storey-3 bay)(a) Column labeling(a) Column labelling(b) Beam labeling(b)(b) Beam labeling(c) Beam-Column reinforcement detail
Figure Ошибка! Текст указанного стиля вдокументе отсутствует.: Properties of frame-3 (4storey-10 bay)(c) Beam-Column reinforcement detail
Figure 1: Properties of frame-1 (11 storey-3 bay)(a) Column labeling

3. MODELING AND ANALYSIS
A two-dimensional model of each structure is createdin SAP2000 to carry out non-linear static analysis. Beamand column elements are modeled as non-linear frame
elements with lumped plasticity by defining plastic
hinges at both ends of beams and columns. Torsion effectin the structure is neglected.

(b) Beam labeling130

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 50
As shown in figure 5, five points, labeled A, B, C, D,
and E define the force–deformation behavior of a flexureplastic hinge. In the present study, failure of eachmember is considered in two ranges, as shown in figure 5,
the first range is load control region in which themember strength carrying capacity increases and it falls
in range B to C, the second range is the displacement
control range in which the lateral strength carrying
capacity decreases drastically, and the member isunreliable in supporting lateral load.

In the expended energy based method, the total energy
dissipated by frame in each incremental load step of the

Frame-1
Figure 3: Force–deformation relationship of a typicalplastic hinge.
Once the structure is modeled with section properties,
steel content and the loads on it, hinges are assigned tothe elements, PM hinges for columns and M3 hinges forbeams. The structure is subjected to incremental lateralforces with IS1893 load distribution along the height ofthe structure and the lateral force at any story is
calculated from the following formula:

Frame-2

Frame-3
Figure 4: C.G of external force profile for three frames.

where:
Vb = Base shear
wi = Seismic weight of floor ihi = Height of floor i measured from baseFi = Lateral force at floor i
External force profile ratio is shown in figure 4.6 forone of the pushover steps. The Pushover curve, baseshear versus displacement at the centre of gravity of
external force profile (Fiure 6) are plotted to calculate theenergy. At any deformation, the area under the curve,
represents the total energy absorbed by the structure forparticular deformation, which is equal to the work of
external loads acting on the structure.
The area under the curve base shear versus
displacement at C.G of external force profile, unlike
classic pushover curve (base shear versus roof
displacement), represents the total input energy
dissipated/absorbed by the structure. During elastic
response, all input energy is consumed by elastic
deformation of structural members.
During elastic deformation, if the structure is unloaded,
it returns to its unstressed condition without any
remaining deformation and there is no damage to thestructure. When external loads exceeds the structure’s
yield strength, input energy is being consumed throughplastic deformation of yielded structural members, andthrough elastic deformation of the rest of the structuralmembers, and damage initiate in the structure.

Displacement at C.G. of external force profile
Figure 7: Damage estimation critical points
pushover analysis (Figure 7) is calculated as the area
under the curve, base shear versus displacement of theframe at the centre of gravity of the external force system,
which gives the real meaning of external work done or
total energy dissipated by the structure. The damage stateof a structure in each incremental load step of the
pushover analysis is calculated using energy function.
Based on the capacity curve of the structure, the damage
state of the structure can be represented as five stages, as
shown in figure 7.
Point A indicates the elastic state of the structure, point
B indicates the point at which the initial tangent of thecurve deviates by 15%, point C indicates the ultimate
strength of the structure, point D represents the stage ofthe structure at which the ultimate strength drops by 15%,
point E indicates the collapse stage. The total pushover
curve is divided into two parts one is positive slope curve13117th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 50
i.e O to C and named as load control region and anotheris negative slope curve i.e. C to E and named as
displacement control region. Possible damage ranges areshown in table 1.
Table 1: Damage ranges
Range of
BehaviourStatedeformation
OA
AB
BC

Elastic
Strain hardening
Ultimate strength

No damageLight damage
Moderate damage

CD

Strength reduction

Severe damage

DE

Imminent collapse

Extreme damage
and collapse[2]
Where Ee - Represents the instant elastic energy
when the structure attains static position.

Damage method- 1
The damage index (Di) is expressed as the ratio ofexpended energy which is responsible for damage to thetotal energy capacity of the structure. Figure 4 represents
the damage parameters used in the model. The initialelastic energy (Eie) is calculated as the area under the
curve up to point ‘ie’ which is the first yield point of thestructure (Figure 8a). E is the energy absorbed by the
structure, up to any point ‘i’, where the damage is to be
calculated (Figure 8b). The total energy capacity (ET) of
the structure is calculated as the total area under the
pushover curve (Figure 8c).

Figure 9: Damage estimation parameters for Method-2
Damage method-3
In this method, damage parameters are energy
dissipated under linear response ( EL) and energy
dissipated under non linear response (ENL). At any
point i, the damage index (Di) is expressed as the ratio of
the expended energy to cause damage at point ‘i’, to thetotal energy capacity of the structure to resist damage(Figure 10)

[3]

[1]
Where

Where:

EL- Energy under linear response at a displacement
where the damage is to be estimated.
ENL - Energy under non-linear response at a isplacement
where the damage is to be estimated.
ELT - Energy under linear response at maximum
displacement of the structure.
ENLT - Energy under non-linear response at maximum
displacement of the structure.

E - Represents the energy dissipated by the structure atany displacement, where the damage is to be estimated.
Eie - Represents the energy absorbed by the structure
under linear displacement.
ET - Represents the total energy dissipation capacity ofthe structure.

(a)
(b)
(c)
Figure 8: Damage estimation parameters for Method-1
Damage method-2
In this method, the damage parameters are E, Ee, ET
and Eie, where Ee represents restored elastic energy atpoint i, all other variables are same as damage Method-1.
The damage index (Di) is expressed as the ratio ofexpended energy at any point i, to the total energy
capacity of the structure.
In this method, the instant elastic energy (Ee) at any
point i, is the area of the triangle as shown in figure 9.
When the damage is to be calculated at the displacement
i, at this point when the structure is unloaded, it isassumed that the structure comes back to static position
by moving parallel to the initial tangent.

(a)

132

(b)

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 50
second and third storey into the displacement control
region and the structure attained an unstable state,
without reaching 4% drift.
Frame 3 with an aspect ratio of 0.3, reached unstablestate at a displacement of 0.4 m i.e, at a drift of 2.6%
(Figure 15), where almost all columns of storey-3 failed
and entered the displacement control region, in which thestructure was not reliable enough to support lateral loads
any more. Hinge formation is shown in figure 16. At
point B, where the stiffness of the structure reduced by
15%, no member reached the displacement control
region. At point C, the third storey columns entered thedisplacement control region. At point D, total instability
for storey 3 was attained, which continued till point E.
finally, the damage was concentrated at storey-3.

(c)(d)
Figure 10: Damage estimation parameters for Method-3
4. RESULTS AND DISCUSSION
To carry out displacement based pushover analysis,target displacement needs to be defined. The target
displacement for 11 storey frame is defined as 4% of
drift i.e 1.76 m. The structure reached an unstable state at
a displacement of 0.92 m i.e at a drift of 2%, where allbase columns failed and entered the displacement control
region, in which the structure is not reliable enough to
support lateral loads any more. In this case, neither
structure reached 4% of the drift or 2/3 of the ultimate
strength. So the damage state of the structure wasassumed to be 100%, at structural instability. For thisstructure, D and E points (Figure 11)were located at thesame point, which depicts that the structure became
unstable even before the ultimate base shear reduced by
15%. The damage profile of method-1 is almost linear;method-3 profile resembles the deflection profile of thestructure. The profile of damage method-3 clearly depicts,
the curve becoming almost straight after point C, thismeans that the damage increases rapidly from point C to
D, which depicts the real behavior of the structure. At
point C, where the strength degradation starts, one of thebottom storey columns entered to displacement control
region, at which the member cannot be relied upon, tosupport lateral loads. When any member enters todisplacement control region, the strength caring capacityof the structure start decreases. After crossing point C,
the structure attained an unstable state by entering all
bottom storey columns into the (Figure 12)displacement
control region.
The four storey 3-bay frame attained an unstable state
at a displacement of 0.33 m i.e., at a drift of 2.1%, wheresome columns of storey-2 and storey-3 failed, andentered into the displacement control region, in which
the structure was not reliable enough to support lateralloads any more. For this structure, points D and E werelocated at the same point (Figure 13), which shows thatthe structure became unstable even before the ultimatebase shear reduced by 15%. Hinge formation is shown infigure 14. At point B, where the stiffness of the structure
reduce by 15%, some beam and column members
yielded. After crossing point C, the structure attained an
unstable state by entering a few other columns of the

Figure 11: Damage profile for frame-1

point B

point C

point D

point E

Figure 5: Hinge pattern for frame-1

Figure 6: Damage profile for frame-2

133

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
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Paper No. 50

point B

point C

point D

ratio of 0.3 failed at 2.6% drift, this shows, as aspectratio decrease drift caring capacity increases.
And another observation from the results is that the 11
storey frame became unstable immediately after point‘C’, but the later frame shown good ductility and has
greater margin for total collapse this indicates that,
increase of aspect ratio also decreases ductility capacityof the structure.
REFERENCES[1] Kappos, A.J. (1997). Seismic damage indices for RC
buildings: evaluation of concepts and procedures.
Progress in Structural Engineering and Materials, 1(1),78-87.
[2] Williams, M.S. and Sexsmith, R.G. (1995). Seismic
damage indices for concrete structures: A State-of-theArt Review. Earthquake Spectra, 11(2), 740-757.
[3] Padilla, D., and Rodriguez, M. (2009). A damage
index for the seismic analysis of reinforced concrete
members. Journal of Earthquake Engineering, 13(3),364-383.
[4] Applied Technology Council (ATC), Seismic
Evaluation and Retrofit of Concrete Buildings, ATC 401996,California.
[5] Federal Emergency Management Agency (FEMA),
Prestandard and Commentary for Seismic Rehabilitationof Buildings, FEMA 356-2000, Washington D.C., USA[6] Krawinkler H., Seneviratna G.D.P.K. (1998): Pros
and Cons of a Pushover Analysis of Seismic
Performance Evaluation, Engineering Structures, Vol.20,
452-464.
[7] Gupta B. and Kunnath S. (2000). Adaptive SpectraBased Pushover Procedure for Seismic Evaluation of
Structures, Earthquake Spectra 16(2), 367-390.
[8] Goel R. K. and Chopra A. K. (2002). Reversal inhigher mode Pushover curves and its implications on
implementation of the MPA procedure. Report
distributed to participants in project ATC-55, Applied
Technology Council, Redwood City, California.
[9] Mohamed Abdel-basset abdo (2012). Parametricstudy of using only static response in structural damage
detection. Engineering Structures, 34, 124-131.
[10] Kotanidis C. and I.N. Doudoumis (2008). Energybased approach of static pushover analysis. Proc. The
14th World Conference on Earthquake Engineering,
October 12-17, 2008, Beijing, China.
[11]Powell GH and Allahabadi R. (1988). Seismic
damage prediction by deterministic methods: concepts
and procedures. Earthquake Engineering and Structural
Dynamics,16,719-734.
12]Poljansek K., and Fajfar P. (2008). A new damage
model for the seismic damage assessment of reinforced
concrete frame structures, Proc. The 14th World
Conference on Earthquake Engineering, 12-17 October
2008, Beijng, Chinal.
[12]Roufaiel MSL and Meyer C. (1987). Analyticalmodeling of hysteretic behaviour of R/C frames. journalof Structural Engineering (ASCE),113(3),429-444.

point E

Figure 7: Hinge pattern for frame-2

Figure 15: Damage profile for frame-3

Figure 16: Hinge pattern for frame-3.
5. CONCLUSIONS
For all frames damage method-3 gave lower values
where damage metho-1 gave higher values and method-2
gave unrealistic values. Among three methods method-3
gave accurate and realistic values. At any deformation
method-3 clearly depicts, at what cost of energy damage
has taken place unlike other methods includes linear
members energy also in calculation of damage.
The 11 storey structure with an aspect ratio of 3 failed at
2% drift, and the four storey structure with an aspect134

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 63

FIELD INVESTIGATION ON A SINKHOLE DEVELOPED IN LOOSE VOLCANIC SOIL
R. KUWANO1, N. KOMINAMI2, M. OTSUBO3, and I. SATO4
1

Professor, Institute of Industrial Science, The Univ. of Tokyo, Japan, kuwano@iis.u-tokyo.ac.jp (corresponding author)
Former graduate student, Dept. of Civil Engineering, The Univ. of Tokyo, Japan, naotokominami@gmail.com
3
Research associate, Institute of Industrial Science, The Univ. of Tokyo, Japan, otsubo@iis.u-tokyo.ac.jp
4
Graduate student, Dept. of Civil Engineering, The Univ. of Tokyo, Japan, i-sato@iis.u-tokyo.ac.jp

2

Keywords: Volcanic soil, Sinkhole, Field investigation, Piping
1. INTRODUCTION
Due to the typhoon on Sept.19, 2016, a large sinkhole
occurred in a sweet-potato field of Miyakonojo,
Miyazaki, leading to a soil outflow of 1500㎥ to theroad nearby through a piping hole, as shown in Figure 1.
The size of sinkhole was 31m long, 13m wide and 7m
deep. Fortunately, there were no human casualties, but
sinkholes may lead to serious accidents depending on thetime and place of occurrence. It is important toinvestigate the cause and take measures to prevent these
accidents. The area is covered by the volcanic soil, called“Shirasu”, which generally has low density and highpermeability. Surveys including dynamic cone
penetration tests and surface wave surveys wereconducted to identify the locations of cavities, water
paths and loosened ground.

Nd

Nd

Point A
Point C
Point E

Point D

D

Nd

Point BpipingA
C

B
E

Figure2: Dynamic cone penetration test
0

stiff

B

soft

10

S wavevelocity

20
0

20
0

40

D0

C0

10
20
66

0

F0
E0
Loosenedground
B40
D66

F41

potato fieldsinkhole
0.4m

30.4m

E34

F0

0E

10

10

20
0

12.8ｍ
estimated soil
outflow 1500m3

0
10

B0

31.3m

C

41

20
0

A50

A0
D0
0A

C50

10
20
0

50

34

Figure3: surface wave surveyroad

3. FORMATION OF SINKHOLE
Very loose Shirasu layer was identified above theimpermeable clayey layer at the depth of about 12m.
Water paths seemed to form within Shirasu layer andShirasu was subjected to internal erosion. A relatively
stiff layer was also found at a depth of 4m, below which
the erosion seemed to be accelerated as schematicallyshown in Figure 3. Surface wave survey results indicatedthat water paths, the potential cause of sinkholes, were
further extended. Judging from elongated shape of thesinkhole, two or three sinkholes simultaneously or
successively occurred above the water paths.

Figure 1: Outline of Miyakonojo sinkhole (2016)
2. FIELD INVESTIGATION
Some of the results of dynamic cone penetration test
conducted around the sinkhole are shown in Figure 2. At
points A, B, C and E, near the sinkhole, the Nd values
were small, less than 10. At point B, a clear cavity(Nd=0) of about 2m was observed at 10m deep. While atpoint D, about 100m away from the sinkhole, Nd values
increase at the depth of more than 6m. Further dynamic
cone penetration tests indicated that the relatively stiff
thin layer existed in the west side of the sinkhole at 4m
deep. Surface wave survey was conducted on 6 lines as
indicated in Figure 3 and ground structure was obtained.
The results obtained from the surface wave survey
showed reasonable agreement with those from dynamic
cone penetration tests. Loosed ground was observed in
the west side of the sinkhole and the presence of water
pathway was suspected.

Stiff thin layer
Loose Shirasu
Water path

Impermeable layer

Impermeable clay
Figure4: Mechanism of sinkhole formation135

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 05

SYSTEM FOR PREVENTING FLAKING OF LINING CONCRETE
IN SUBWAY TUNNEL
Saki NEMOTO1, Shinji KONISHI2, Daisuke TANAKA3, Yuki ENOKIDANI4 and Naoki IMAIZUMI5Engineer, Infrastructure Maintenance Dept., Tokyo Metro Co., Ltd., Tokyo, Japan, s.nemoto.g3t@tokyometro.jp (corresponding author)
2
Department Manager, Infrastructure Maintenance Dept., Tokyo Metro Co., Ltd., Tokyo, Japan,s.konishi.r4r@tokyometro.jp
3
Engineer, Infrastructure Maintenance Dept., Tokyo Metro Co., Ltd., Tokyo, Japan, d.tanaka@tokyometro.jp
1

4

Engineer, Infrastructure Maintenance Dept., Tokyo Metro Co., Ltd., Tokyo, Japan, y.enokidani@tokyometro.jp

Assistant Manager, Infrastructure Maintenance Dept., Tokyo Metro Co., Ltd., Tokyo, Japan,
n.imaizumi@tokyometro.jp
5

Keywords: Subway tunnel, Flaking, Spalling, inspection, Visible Image, Infrared Thermography
1. GENERAL INSTRUCTIONSTokyo Metro Co., Ltd. (“Tokyo Metro”) currently operates nine subway lines over 195.1 km of track (532.6
km of track if through services are included) and transports roughly 7.24 million passengers per day; Tokyo
Metro is an integral part of the massive railway networkof the metropolis of Tokyo. However, by 2020, the yearof the Tokyo Olympics, 52.6% of Tokyo Metro’s tunnels
will be at least 50 years old, a fact that heightens the importance of daily maintenance toward continuing to provide services into the future while ensuring safety andsecurity for passengers. Tunnels comprise 85%, or 166.8
km, of the subway lines operated by Tokyo Metro. Nonetheless, safe and consistent operation is provided throughappropriate maintenance that complies with MaintenanceStandards for Railway Structures.1,2
When fragments of concrete peel away from the liningof railway tunnels, emergency inspections are normallyconducted of entire lines to check whether peeling isoccurring in other locations, and locations that appear to
be at risk for peeling are determined and then treated.
The work of determining locations is extremely physically demanding, and the fact that it is also urgent meansthat there is a risk of peeling being overlooked. Therefore,a highly precise, efficient method of determination isdesirable.
In light of these circumstances, Tokyo Metro usedinspection data, visible image data (digital data) (Figure2), and infrared thermography data from all tunnel sections under our ownership to research and develop a system that can automatically determine spalling and peeling on the basis of statistical analysis and image analysis
technology. This report summarizes the four methods
that were used, and describes Tokyo Metro’s system forpreventing peeling.

Figure 1. Revealed Rules Image

Figure 2. Visible Image (Database)of cracks, leakage and other forms of deterioration revealed by the data. This database is being used to develop a system for detecting the locations of spalling andpeeling. When components peel away and fall off ofstructures on railway lines, total inspections are conducted to check for similar locations. This is extremely difficult to carry out in a short period of time given the vast
number of cases of structural deterioration occurring
over long distances in the tunnels. Thus, a system is being developed that uses image recognition technology todetermine locations that closely resemble the previous
states of locations where concrete peeled and fell off.

2. SYSTEM for DETERMINING SPALLING and
PEELING LOCATIONS USING VISIBLE IMAGESTokyo Metro presently has visible image data from allnine subway lines, and a digitized database of the records

13617th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 05(2) The differences described in (1) occur when thetemperature difference between the air inside tunnels
and the concrete is at least 0. 35°C
(3) Cold winter days are ideal for taking measurements because the differences described in (2) often
occur when the outside air temperature is 5°C to 10°C
or lower

Figure3. Calculation Image Using Visible Images
Development and testing is continuing on a programfor critical deterioration patterns (the pattern in which
two instances of deterioration cross and the patternwhere they develop in parallel), and in test zones 98% of
spalling and peeling locations detected in general inspections have been successfully detected.
However, using only visible images resulted in overdetection due to the way the deteriorations were groupedand for other reasons. In addition, it is obviously impossible to detect potential spalling or peeling when locations show no surface deterioration on visible images.
Therefore, infrared thermography projections of spallingand peeling locations, as detailed below, were added toincrease the precision of the detection system.

Figure 5. Calculation Image Using Infrared Thermography

3. INFRARED THERMOGRAPHY
The surfaces of tunnel walls are warmed by heat frompassing trains during operating hours. The surfaces arequickly cooled at night once cold, outdoor air circulates
through the tunnels after last trains, but locations where
spalling exists cool more easily, resulting in temperaturesthat differ from those of healthy locations. Ways to use
infrared cameras to detect these differences are currently

Figure6. Calculation Map of Flaking
Now that measurements are taken under these conditions, it has become possible to detect roughly 95% of
spalling and peeling discovered during general inspections in shield tunnels, and roughly 80% in open-cut
tunnels.
In addition, in some sections infrared thermography
was used after general inspections to detect problems
other than those detected in the inspections, and further
hammering tests were conducted in those locations. As
a result, it is now understood that spalling and peelingactually exists in roughly 55% of locations where the useof infrared predicted spalling and peeling not detected ingeneral inspections. Essentially, spalling and peeling was
successfully detected in locations where it could not havebeen discovered visually.
In addition, hammering tests were conducted over entire surfaces in some of the areas where analysis was
conducted to investigate the extent to which problematic

Figure 4. How to Measure Using Infrared Thermography
being considered. The evidence gathered from actual
tunnels over the past three years has taught us the following:(1) Temperature differences of at least 0.03°C between
the concrete in healthy parts and in places where spalling
exists can be detected137

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
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Paper No. 05
locations that general inspections failed to reveal werebeing detected. It was found that 22% of the instances ofdeterioration newly discovered by hammering tests ofentire surfaces could be detected. The simplest way todetect spalling and peeling in locations with no visible
surface deterioration is to conduct hammering tests overentire surfaces; however, since this is physically impossible to do over entire lines, the infrared thermographymethod holds promise as an effective inspection tool.
However, while it has been shown that inspections arehighly precise near stations, ventilation openings andother locations where air circulates through undergroundspaces and where temperature changes occur easily, they
are not as precise between stations, where there are no
ventilation openings and where temperature changes areslight. It is imperative to further increase the number ofverifications to carefully examine the threshold in thesecond of the three environmental conditions described
previously (when the temperature difference between the
air inside tunnels and concrete is at least 0.35°C) in order
to expand the scope of application for this method.
In addition, as explained in Section 2, work is under
way to improve the accuracy of predictions of spallingand peeling by combining these efforts with the systemfor determining spalling and peeling locations using visible images. As part of the consideration toward implementing this technology in the field, a heat map like theone in Figure5 was used to visualize the combination of
the two methods of prediction so that a single glance is
all it takes to establish the priority of locations to hammer and eliminate locations that do not require hammering. However, the lack of landmarks in tunnels makes it
difficult to conduct hammering tests in the field using
heat maps. Therefore, ways to reproduce this method in
the field are continuously being considered.

cracks and leakage, and the conditional probabilities thatleakage also occurs where cracks have occurred, and thatcracks also occur where leakage has occurred, it is apparent that the causal relationship is stronger where theobservation probability is higher. This probabilistic model that efficiently calculates conditional probabilities
between variables is called a Bayesian network.

Figure 8. Calculation Image of Bayesian Networks
For example, while leakage may not have been observed in a particular location to date, the presence of
spalling, peeling, cracks and other forms of deterioration(as detected in inspections) should mark that location asa place where leakage could easily occur. In other words,
it is possible to estimate locations where leakage has ahigh likelihood of being overlooked. This method can beused to discover locations where it is highly likely thatspalling or peeling has been overlooked.
Figure 8 shows an actual subway line. Although it ishighly probable that some locations may have been overlooked during inspections, hammering tests can be conducted in those locations to efficiently discover spallingand peeling not seen before. This method is straightforward for everyone because the results are expressed asprobabilities. Therefore, verification of the validity of themodels is under way, and the feasibility of implementing
this method is being considered.

4. BAYESIAN NETWORKS

5. STATISTICAL ANALYSIS OF INSPECTION DATA AND STRUCTURE SPECIFICATIONS

Figure 7. Image of Bayesian Networks

Figure 9. C-Line Discriminant Impact Results

Tokyo Metro is working on the development of amethod based on statistical methodology to determine
locations that may have been overlooked during inspections.
This method uses causal relationships between deterioration types to predict the locations of these deteriorations. For example, given the two deterioration types of

In addition to inspections required by ministerial ordinance, Tokyo Metro conducts hammering tests of all
subway lines at least once every four years. These tests—
in particular, tests of upper floor slabs—require an immense amount of work to prepare the scaffolding andperform the other tasks in the limited amount of time138

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 05
between the last train on one day and the first train on thenext day. Therefore, the test frequency must be optimized
and the sections selected wisely.
Toward that end, development is proceeding with theaim of streamlining hammering test work by predicting
sections of upper floor slabs susceptible to deterioration
via the analysis of specifications, environmental data,and inspection and test data.
Two methods are used to conduct this analysis. Under
the first method, the aim is to fully understand statisticaltrends by using map visualization to confirm typical distributions of deteriorated locations in terms of geographical space, and histograms of numbers of deterioration
cases in tunnels. Under the second method, statisticalmethods are used through cluster analysis, t-tests, relativity analysis, multiple regression analysis and the like
(Figure 9).
Presently, various elements are analyzed such as construction years and completion years to determine andsort factors with the highest relativity to the occurrenceof spalling and peeling. The results of this analysis havebeen used to identify sections susceptible to deteriorationand create scatter diagrams to visualize the sections.
(Figure 10)

Figure 11. Two Performance Curves
model designed to avoid fruitless inspections by emphasizing the rate of inspections avoided (the correct answer
rate for lack of deterioration) enables us to improve thecorrect answer rate for instances of deterioration (theprobability of discovering structural deterioration via
hammering) 2.06 times over hammering tests over entire
sections, thereby reducing the work of fruitless inspections (hammering tests that result in no deterioration being found) by 90.6%; 50% of deterioration locations canbe detected with 9.4% of the workload.
Or, if a discriminant model designed to emphasize risk
reduction by emphasizing deterioration detection rates(the lack of unexpected results) is used, it is possible toreduce the workload by 27.6% while maintaining a deterioration detection rate of 94.9% (5% unexpected results).
The plan going forward is to proceed with investigations
into the selection of discriminant properties and settingof thresholds to serve as evaluation indices for different
applications of the results of analysis.

Figure 10. Example of Visualize Which Area
Susceptible to Deterioration
The results of this statistical analysis were used to
conduct interviews with actual inspectors as to whether
they are satisfied with the factors (explanatory variables)with the highest relativity to the occurrence of spallingand peeling and the sections projected as susceptible tospalling and peeling. The inspectors expressed a highlevel of satisfaction with the analysis when it identified
highly deteriorated sections that they recognized fromtheir experience in the field. However, the inspectors
were disappointed with the discriminant analysis when
the results revealed variance in the distribution of linesthat made trends difficult to interpret, or when the results
failed to assign high priority to sections that they knew
from experience to be deteriorated. In addition, because
the same explanatory variables produced extreme differences in the level of satisfaction between respondents,
new interviews are being conducted as to the discrepancies with engineering knowledge, and the results compared.
This model makes it possible to identify factors in linewith objectives through the selection of discriminant
properties while referring to two performance curves.
(Figure 11) For example, it is estimated that using a

6. PRACTICAL APPLICATIONS

Figure 12. Proposed Flow of Operations for Preventing
Concrete from Peeling Away and Falling Off
Figure 12 shows the process being considered for everything from detecting to taking action against spallingand peeling. Regular implementation of the guidelines inthe three stages explained to this point can deliver excellent results over the short term as well as the long term.
For example, the ability to establish places to hammer(and places not to hammer) in the voluntary hammering
tests that are being conducted once every four years not
only introduces variation to these tests, but also enables

13917th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 05
secure, safe and consistent operation.

Picture1. Scenes from a Maintenance Committee Meeting

Figure 14. Conceptual Diagram of Method of Determining Potential Locations of Spalling and Peeling
8. REFERENCES[1] Railway Technical Research Institute: “MaintenanceStandards for Railway Structures and Commentary(Structures): Tunnels,” Editorial Supervision by the
Railway Bureau, Ministry of Land, Infrastructure,
Transport and Tourism, Maruzen, 2007.
[2] Kubo et al.: “Consideration toward Using Infrared
Thermography to Improve Detection of Spalling andPeeling of Tunnel Concrete,” Summary of 72nd Annual
Academic Lectures, Vol. VI, 6-939, 2017.
[3] Wakuta et al.: “Prediction of Subway Tunnel Sections
Susceptible to Upper Floor Slab Concrete Peeling andFalling Off Based on Multiple Regression Analysis,”
Summary of 72nd Annual Academic Lectures, Vol. VI, 6529, 2017.
[4] Shinohara et al.: “Developing a System for Automatic
Extraction of Locations Susceptible to Concrete Peeling
Using Image Recognition Technology,” Department ofProceedings of the 26th Tunnel Engineering Committee
Meeting, 2016.
[5] Shinozaki et al: “Analysis of Causal Relationship of
Deterioration Occurrence via Bayesian Network Using
General Inspection Results,” Summary of the 70th JSCE
Annual Academic Lectures, Vol. VI, VI-343, 2015.

Figure 13. Documents for a Maintenance Committee
Meeting
the effective and efficient distribution of limited humanand financial resources when drafting short-term maintenance plans (daily inspections).
In addition, Tokyo Metro has established an internalmaintenance committee to provide a venue to discuss
maintenance policy and other issues for each line. This
committee discusses plans for short-term maintenance(daily repairs) and long-term maintenance (major repairs) that incorporate preventive maintenance in light of
the results of various inspections, investigations, the statistical analysis described previously, past repairs andmore.
In other words, analyzing the results of inspections
and daily measurements in long-term maintenance plans
makes it possible to identify sections potentially at riskof deterioration. As a result, highly explicit preventive
maintenance and other maintenance plans can be drafted
for each line, including plans to investigate root causes
and propose countermeasures, as well as policy for major
repairs and reinforcement. (Figure 13)
7. SUMMARYTokyo Metro has taken various approaches toward
working to prevent concrete tunnel lining from peelingaway and falling off. The effectiveness of the individual
methods has been proven along the way; thus, our aim is
to integrate them into overall maintenance operations,and to keep implementing these systems until they
become a natural part of operations. By doing so, Tokyo
Metro is striving to perform high-level tunnel
maintenance that will contribute to the continuation of140

USMCA 2018

SESSION 8
DISASTER MANAGEMENT II

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 60

Dolomite rock sand as fine aggregate replacement for secondary construction activities: a comparative
study
A.C Bharath KRISHNAA1*, R Vineeth 2*, S Malavika Sasi 3*, C Prakash 4*, M Ananthkumar*5
1

Student, Civil Engineering, Amrita Vishwa Vidyapeetham. Coimbatore, India, bharathkrishnaa5@gmail.com

2

Student, Civil Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India, vineethrengaraj538@gmail.com

3

Student, Civil Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India, malavikasdharan@gmail.com

4

Assistant Professor, Civil Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India,

pen2prakash@gmail.com
5

Assistant Professor, Civil Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, India,

amritananth@gmail.com
KEYWORDS: DRS- Dolomite Rock Sand, M Sand, Compressive Strength, Fine Aggregates, Sustainable, Life Cycle
Analysis, Coimbatore.
This paper attempts to study the use of Dolomite rock sand (DRS) as fine aggregate replacement to conventional
manufacture sand (M sand) considering the increasing demand from construction industry and depleting M sand availability
DRS as fine aggregate (FA) replacement might be a sustainable option. DRS was chosen for this study, since it’s locallyavailable and is present in abundance in the region of Coimbatore. Further, its transportation within the region proves to becost effective in comparison with river sand. Design mixes were prepared to achieve concrete grades of M20, M25 and M30
for FA replacement by 0, 20 and 30 % for each concrete grade. Tests were conducted to check the 28 day compressive
strength of concrete. The results of the study showed that for all concrete grades, 20-30% of FA replacement by DRS was
found to be suitable. Further, comparative analysis was performed between river sand and DRS replacement for considering
the suitability of DRS replacement concrete for various secondary construction activities. DRS showed better performancein structures which are not subjected to heavy loads and thus could be a sustainable replacement for M sand.
Table 1 : Compressive strength of concrete with variation in DRS % for grades of 20 25 and 30.

Compressive Strength ( N/ mm2 ) after 28 days

CONCRETE
GRADE

10% REPLACEMENT

20% REPLACEMENT

30% REPLACEMENT

M20

19.7

19.6

18.9

M25

24.8

24.3

23.7

M30

30.2

29.5

28.6

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Paper No. 60

Table 2 : Comparison of parameters for the two different Fine Aggregates
Parameters

M SandDolomite Rock Sand

Specific Gravity

2.59

2.704

fineness modulus

3.1

2

Water Absorption

1.8%

1.3%

Figure 1: Cubes casted with Dolomite Rock Sand
Preliminary tests were carried out on the aggregates and the design mix was calculated based on the values obtained from
Table 2. Specific gravity of cement used was 2.95.
Life cycle analysis was done on the basis of “Cradle to Grave “of processing of Dolomite Rock sand from its production to
usage. By using DRS we are able to form a closed loop system. DRS which is a waste product of cement factory in
Coimbatore proves to be cost efficient in its transportation.
Conclusion:
Based on the experimental data it was found that Dolomite Rock Sand proves to be efficient when combined with M sand inproper proportions and helps us achieve the desired strength. The result of the compressive strength test proves that it canalso be used in structural elements. This report provides a platform to achieve sustainable development and prevents
exploitation of river sand , reduces the usage M Sand. Thus, this can be implemented in places with abundant lime stone
deposits and takes us a step closer to environmental sustainability and development.
References:
1.
2.
3.

Ž. Rudžionis, E. Ivanauskas and M. Senkus, “The Analysis of Secondary Raw Materials Usage in SelfCompacting Concrete Production,” Materials Science, vol. 11, no. 3, pp. 272–277, 2005.
Viktor Vaganov, Andrey Kireev, Sergey Avdeev, Genādijs Šahmenko, Māris Šinka, "Prospects for Effective
Use of Dolomite in Concrete Compositions",Construction Science 19 (1), 27-32, 2016.
“Building Construction” By Rangwala.

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 81

RECONST RUCTIONP ROJECT S' COMPLETION SPEE D AND DAMAGE CONDITIONSDUE TOTHE GREATEAST JAPANEARTHQUAKE
0.MURA01 and M.NUMAYAMA2
1

Professor, International Research Institute ofDisaster Science, Tohoku University, Sendai, Japan,
murao@irides.tohoku.ac.jp (corresponding author)
2
Former Students, Graduate School ofEngineering, Tohoku University, Sendai, Japan
Keywords: affected municipalities, tsunami, urban recovery, land use mitigation, recovery project, recovery process
1.INTRODUCTION

2. RECOVERY
DISTRICTSPATTERNOF

B. Concentration

A. Relocation

The Great East Japan Earthquake and Tsunami
catastrophically struck the eastern part of Japan on
March 11, 2011, especially the coastal areas of the
Tohoku region. As of March 7, 2018, the number ofcasualty is 19,630, with 2,569 people still considered
missing [1]. Seven years have passed since the event,and the reconstruction projects are underway in eachdamaged area. Affected municipalities can use andcombine some reconstruction projects prepared by
Reconstruction Agency after the event. However, thearea where the reconstruction project is carried out
ranges from 500 km north to south. It is very rare tosimultaneously promote the reconstruction of a large
number of wide areas with the common reconstruction
system. There is no research focusing on the entire
tsunami-damaged area by the disaster, especially about
the relationship between the reconstruction plan andproject and the transition of space.
It is meaningful to comprehensively understand thereconstruction mechanism from the Great East Japan
Earthquake for future catastrophes. In this research, theauthors organize a dataset of the reconstruction projects
and the damage situation of the affected areas, andcategorize the patterns of the reconstruction process fromthe disaster.
The authors gathered information on recovery projectprogress situation of 61 municipalities as of March 2017
for comparative analysis of their recovery processes.
This research aims to quantitatively evaluate thereconstruction processes.

C. Compacted terraces and berms
l

ct:

�
..............�,,., ....-....

··T��r

D. Relocation and compacted terraces E. Reconstruction on the original sitelfiE].............."...

-�......

-�"'"""'""""'"'�""""Compacted terrace model in Natori

Figure 1: Recovery patterns after the Great East Japan

Earthquake

3.METHOD

The research was carried out the following procedure.
(1) Target districts
The objective of this research is 379 districts seriously
damaged by the tsunami in Iwate, Miyagi, andFukushima prefectures.
(2) Data Collection
Related dataset for the target municipalities released
by Reconstruction Agency are gathered from theprogress report site.
(3) Data Analysis
Using the dataset, recovery progress conditions arecompared in terms of adopted recovery projects, thenumber of constructed housings with construction period,and so on.
(4) Making recovery curves
Recovery curves of recovery project progress aredemonstrated for the comparison.

AFFECTED

4.COMPARISON OF RECOVERY PROCESSES

MLIT [2] classified recovery plans, the residential
districts would need, into five patterns based on thesurveys for consideration of recovery patterns for thedamagedresidential
districts
above-mentioned.
According to the damage and geographic conditions,those recovery patterns were classified into fivecategories: (A) Relocation, (B) Concentration, (C)Compacted terraces and berms, (D) Relocation andcompacted terraces and berms, and (E) Reconstruction
on the original site with facility reinforcement. The
five patterns are illustrated in Figure 1.

Finally, reconstruction processes from the 2011 Great
East Japan Earthquake are compared in terms of projecttypes and prefectures.
(1) Comparison of Recovery Processes by Project Types
Fig. 2 demonstrates recovery processes in terms ofrecovery projects constructed by the data collected from
Reconstruction Agency. X-axis indicates time period
from 2011, and Y-axis shows construction completion
ratio out of the total number of objective districts.
The speed of Type (A), collective relocation, is thehighest, followed by Type (B), enhancement of fisherysettlements' function. The lowest is of Type (C), land143

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 81

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 34

EARTHQUAKE EARLY WARNING SYSTEM FOR SHINKANSENAND ITS EFFECTIVNESS
S. UEMURA1, H. SUZUKI2, H. MIYAKOSHI3, T. NAGASAWA4, S. AOI5, W. SUZUKI6 and S. Yamamoto7
1

Chief Researcher, R＆D Center of JR East group, East Japan Railway Company, Saitama, Japan, s-uemura@jreast.co. jp (corresponding author)
2
Director, R＆D Center of JR East Group, East Japan Railway Company, Saitama, Japan, h-suzuki@jreast.co.jp
3
Researcher, R＆D Center of JR East Group, East Japan Railway Company, Saitama, Japan, hi-miyakoshi@
jreast.co.jp
4Manager, Facilities Department, East Japan Railway Company, Tokyo, Japan, t-nagasawa@jreast.co.jp
5Director-General, Network Center for Earthquake, Tsunami and Volcano, National Research Institute for Earth
Science and Disaster Resilience, Tsukuba, Japan, aoi@bosai.go.jp
6
Chief Researcher, Network Center for Earthquake, Tsunami and Volcano, National Research Institute for Earth
Science and Disaster Resilience, Tsukuba, Japan, wsuzuki@bosai.go.jp
7
Laboratory Head, Disaster Prevention Technology Division, Railway Technical Research Institute, yamamoto.
shunroku.11@rtri.or.jp
Keywords: Earthquake Early Warning Systems, ocean bottom seismometer, Shinkansen
companies in Japan. The East Japan Railway Company(JR East)
has been enforcing “hard” and “soft”
countermeasures for greater safety in seismic situations.
Anti-seismic reinforcement is representative of “hard”
countermeasures, while train operation control in timesof seismic activity and the Earthquake Early Warning(EEW) System, stopping Shinkansen trains quickly inthe event of a large earthquake, are representative of“soft” countermeasures.
In this paper, we outline the principle andeffectiveness of the EEW system. In addition, as a recent
effort, we will describe the use and effectiveness ofocean bottom seismograph data in operation control of
the Shinkansen.

1. INTRODUCTIONSJapan is one of the most earthquake-prone areas in
the world, where the Pacific Plate, Philippine Sea Plate,
North American Plate and Eurasia Plate all interact witheach other. Japan often suffers serious damage fromlarge earthquakes (Fig.1). Therefore mitigation ofearthquake damage is an important issue for railway

2. OUTLINE AND EFFECTIVENESS OF EEWSYSTEM
In the EEW system, seismometers are located at 85
points Railside, 30 points inland, and 20 points along the
Figure 1: Shinkansen derailed by earthquake

Figure 2: Overview of Earthquake Early Warning System in JR East145

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Paper No. 34

ＪＲ警報用加速度 (gal)Acceleration(gal)Control section(Costal P-wave warning)

400
150
300

Costal seismometer Iwaki

100

200
50

100
00

Earthquake
occurrence
142gal93gal
115gal100gal88gal
97gal

Epicenter(M7.4)
Iwaki

S2N13

Ocean bottom
seismometer(S2N13)
Exceed threshold
S-wave warning(About 10s later）

12s

1s

Costal seismometer
P-wave warning（About 22s later）

Figure 4: Verification of effect on the November 22, 2016 Earthquake Fukushima Prefecture Offshore
coast (Fig.2). Railside and inland seismometers detect
mainly inland earthquakes, and seismometers along thecoast detect mainly subduction-zone earthquakes. The
EEW system issues P-wave and S-wave warning[1]．A
P-wave warning is issued based on seismic magnitude
and epicenter estimated by the initial part of P-wave. An
S-wave warning is issued when acceleration exceeds thethreshold. In a P-wave warning, warning can be issued
earlier than an S-wave warning. When a warning isissued, power supply is cut, the Shinkansen emergency
brakes are automatically applied, and trains stop. In thecase of the Great East Japan Earthquake (Mw=9.0)
occurring on March 11, 2011, the coastal seismometer
closest to the epicenter issued an S-wave warning 12-22
seconds ahead of the “suspending operations” order
based on lineside devices [2].

remaining sub-networks will start in 2019.
There have been no instance of warning issued basedon S-net data as of August 2018. Therefore, we verified
the effectiveness of incorporating S-net into the EEW
system based on past data. First of all, it was roughly
estimated that by using S-net data for the Great East
Japan Earthquake (2011), an S-wave warning would be
issued about 25 seconds earlier than that of theconventional EEW system. Next, we verified
effectiveness based on S-net archive data. Below is acase study of an earthquake occurring on 22 November
2016 offshore of Fukushima Prefecture with a magnitudeof 7.4. In this earthquake, as shown in Fig. 4, a P wave
warning was issued from the Iwaki costal seismograph(▼：epicentral distance 66km) closest to the epicenter
22 seconds after occurrence. On the other hand, theacceleration at the ocean bottom seismometer closest to
the epicenter (●: epicentral distance 7 km) exceeded
threshold value 10 seconds after the earthquake occurred.
From the above, it is estimated that warning would be
issued 12 seconds earlier than conventional EEW system
if the ocean bottom seismometers of S-net are utilized.

3. UTILIZING OCEAN BOTTOM SEISMOMETERS DATA IN EEW SYSTEMThe National Research Institute for Earth Science andDisaster Resilience (NIED) equipped 150 ocean bottom
seismometers along the Japan Trench(S-net) in 2016
(Fig.3)[3]. JR East planned to incorporate data fromthese into the EEW system and began using data of a
sub-network of 22 ocean bottom seismometers installedboso offshore on November 1, 2017[4]. This system
issues an S-wave warning. Utilization data from theS5：Kushiro-Oki
and Aomori-Oki

S4：Northern
Sanriku-oki
S3：Miyagi-Oki
and Iwate-Okie
S2：Ibaraki-Oki and
Fukushima -Oki

4. CONCLUSIONSIn this paper, past and recent efforts related to the
EEW system in JR East and their effectiveness wereintroduced. Though these efforts seem to have improved
the safety in time of earthquake, we intend to continue topursue further safety through new technologies andtechnological development.

S6：Outer risealong Japan Trench

Seismometers of EEW

REFERENCES[1]H.Iwahashi.,N.Iwata., S.Saito., and K.Ashiya., (2004):”Practical Use of Earthquake Quick Alarm System”RTRIREPORT, Vol.18, No.9, pp.23-28.
[2]S.Yamamoto., and M.Tomori.,(2013): “Earthquake
early warning system for railway and its performance”,
Journal of JSCE, Vol.1, pp.322-328[3]K.Uehira., (2014) “Seafloor observation network forearthquakes tsunamis along the Japan Trench” Journalof the society of instrument and control engineers, Vol.53,
No.6, pp.477-481[4]K.Mizuno.,H.Osawa.,and F.Aizawa.,(2018): “Utilization of earthquake information at JR East” Japan
Railway Engineers Association,VOL.61,No.6,pp.23-26.

Wayside Seismometer
Costal Seismometer
Inland Sismometer

Seismometers of S-net
S1：Boso-Oki
S2：Ibaraki-Oki& Fukushima-Oki
S3：Miyagi-Oki& Iwate-Oki
S4：Northern
Sanriku-Oki
S5：Kushiro-Oki& Aomori-Oki
S6：Outer rise along
Japan Trench

S1：Boso-Oki

Figure 3: Ocean Bottom Seismometers arrangement
in S-net146

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 42

EVALUATING THE ROBUSTNESS OF NETWORKSREGARDING SPATIAL RELATIONSHIPS OF MULTIPLE ROUTES
Yudai HONMA1, and Motoki TAJIMA2
1
2

Associate Professor, ICUS IIS, The University of Tokyo, Tokyo, Japan, yudai@iis.u-tokyo.ac.jp (corresponding author)
Former Student, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan

Keywords: robustness, traffic network, spatial relationship, multiple routes
1. INTRODUCTION
In this research, we evaluate a robustness of transportation network assuming occurrence of simultaneous
multiple events from huge disasters. By focusing on thespatial relationship between the routes in the transport
network, we quantitatively analyze the influence of the
shape characteristics of the transportation network on
robustness.
Spatial movements of people and objects are achieved
mainly by transportation networks which consists of roads,
railways, waterways, airways etc. (Hereafter, we omit theword “transportation” and simply express as “networks”).
Especially in developed countries including Japan, dense
networks are formed, which contributes greatly to
improving the convenience of our lives. On the other hand,
there are many instances in which the network isinterrupted due to natural disasters abnormal weather suchas concentrated torrential rain and natural disasters suchas earthquakes, concentrated torrential rain and eruptions,
resulting in a great deal of damage. It is to say, the network
is vulnerable to disasters.
Therefore, even if a disaster happens, it is important thata network maintains functionality without significant
damage and the routes of evacuation behavior anddistribution activities are secured. There are plenty ofearlier studies on network assessment for disasters. There
researches usually regard a disaster as a stochastic
phenomenon, and evaluate a robustness/vulnerability oftransportation abilities.
For example, Berdica et al. [1] defines vulnerabilities
as susceptibility to incidents that could significantly
reduce the serviceability of road networks. From such a
point of view, some studies have focused on links thatmake up the network and evaluated its vulnerability.
Taylor et al. [2] have defined various accessibility
indicators from a socioeconomic point of view, and aresearching for critical links that are greatly affected when adeficiency occurs. In addition, Jenelius et al. [3]introduces two concepts indicating the importance ofimportance for one link and the degree of exposure for
scenarios including damage to multiple links. A
geographical information system is essential for analyzing
the damage of disaster, so there are also studies [4] thatmade large-scale computer experiments making full useof its features. They were trying to quantify damage basedon actual data, and it seems to be useful for disasterdamage estimation and disaster prevention plan
formulation. However, such kind of GIS approaches
generally have difficulty to obtain appealing conclusion

because these results tend to be complicated by assuming
too many elements.
In this way, the robustness/vulnerability of the network
against disasters have been studied from various
viewpoints, and definitions are also various. In thisresearch, we focused on the robustness of what quantified
the remaining functions even if a disaster occurred.
Meanwhile, we assume that the vulnerability is thequantified function which is lost due to a disaster. In thisassumption, the sum of the value of robustness and thevalue of vulnerability is a quantified function of normal
time, and we focus on the former robustness in the paper.
In this research, in order to quantify the robustness ofthe network, we treat events as a stochastic phenomenon
and try to evaluate the influence of the event pattern on
the network. We consider not only the network topology
which lots of earlier studies focus on, but also the spatial
relations of the network elements and the influenced areaof events. By introducing the idea of spatial relations, one
event would affect multiple links simultaneously. Since
our model is based on pure formulation, it enables us toacquire broad perspectives about network robustness.
The structure of this paper is as follows. In Section 2,
we will summarize the concept of network robustness inthis research. In the following Section 3, we propose a
new model which evaluate a robustness of the network
assuming the occurrence of simultaneous multiple events.
This model results to calculate an expected value which
considers both the probability of event pattern based on
the spatial Poisson distribution and the synthetic utility of
the C-logit model [5,6]. In Section 4, we calculate therobustness value under various conditions and discuss its
properties on an idealized network, which consists of 3
circular and 12 radial links. Finally, in Section 5, we state
the summary and future development of this paper.
The following are main findings obtained in thisresearch: (i) As for the circular-radial network, as the
network scale becomes relatively smaller, hub of the
network has a greater influence on robustness; (ii)robustness is also affected by the size relationshipbetween the damage and the city block. As describedabove, using the mathematical model of this research,
considering both the property as the network topology asin (i) and the property based on the spatial relation as in(ii), robustness It is possible to evaluate.
2. ROBUSTNESS OF NETWORKSIn this section, prior to formulation, we summarize theconcept of network robustness in this research. As

147

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
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Paper No. 42
mentioned above, in this study, it is assumed thatsimultaneous events are happened in various place.
The following conditions are listed as preferred network
characteristics against occurrence of such events.
••

damage is assumed among wooden housing densely
populated areas), and no huge bias is observed in the placeand size. In addition, these areas would be damaged at thesame time by fires, and in that case, the road passing
through the damaged area cannot be used.

Many different alternate routes are remained.
Each route must be spatially distributed so that it
will not be disconnected at the same time due toone event.

There is certain that it is better to have multiple
alternate routes from the viewpoint of robustness of the
network. On the other hand, for the second condition, we
should state actual case examples for better understanding.
In the 1995 Great Hanshin-Awaji earthquake, several
major arterial networks which were essential for domestic
East-West traffics, such as National Highway No.2, Route
43, Hanshin Expressway 3 No.3 Kobe Line and theChinese Expressway were damaged. As a result, there wasa serious trouble to domestic east and west traffic, as well
as difficulties of evacuation and rescue activities due to a
decline in traffic capacity in the disaster region. One causeof such traffic confusion is the spatial relation of theabove-mentioned networks. It has been pointed out thatmultiple arterial networks, which should originally be
replaced, are spatially close to each other and passed
through the afflicted regions, causing simultaneous
damage and causing traffic disruption. This fact suggeststhat not only focusing on multiple routes as topology but
also focusing on its spatial divergence when evaluating
the robustness of the network against disasters. Based on
the above idea, we propose a new evaluation model of
network robustness considering both the network
topology and the spatial relation of network links at thesame time.

Figure 1: Example of events which randomly happen

Figure 2: condition that a route survive
3.2. AFFECTED AREA
First, an affected area for sorting out the relationshipbetween random event occurrence and disconnected routeis described. Assuming that ℬ𝑘𝑘𝑟𝑟𝑟𝑟 is the area where thedistance from 𝐴𝐴𝑟𝑟𝑟𝑟
𝑘𝑘 is less than R, the route k cannot be
used only when the center point of the event disk is
included in the area ℬ𝑘𝑘𝑟𝑟𝑟𝑟 as shown in Fig.2. let us focus
𝑟𝑟𝑟𝑟, but 𝑘𝑘 ≠ 𝑘𝑘′. Specifically, we combine
on ℬ𝑘𝑘𝑟𝑟𝑟𝑟 and ℬ𝑘𝑘′
the common set of routes affected for all ℬ𝑘𝑘𝑟𝑟𝑟𝑟 and express
it by ℛ𝐼𝐼𝑟𝑟𝑟𝑟 (𝐼𝐼 ∈ 𝛹𝛹 𝑟𝑟𝑟𝑟 ) . The definition of ℛ𝐼𝐼𝑟𝑟𝑟𝑟 is asfollows:

3. FORMULATION
3.1. ASSUMPTION
Suppose a network as a graph G = (N, E) with vertex
the set of node N and the set of link E. G is on the twodimensional plane Z, and is a weighted graph in which theweight of each node is wn and the length of each link is le.
𝑟𝑟𝑟𝑟
th shortest paths from an origin 𝑟𝑟 ∈Also, the set of 𝑘𝑘max
𝑁𝑁 to a destination 𝑠𝑠 ∈ 𝑁𝑁, the OD pair 𝑟𝑟𝑟𝑟, is given by in𝑟𝑟𝑟𝑟}.
ascending order of distance 𝐾𝐾 𝑟𝑟𝑟𝑟 = {1,2, ⋯ , 𝑘𝑘, ⋯ , 𝑘𝑘max
𝑟𝑟𝑟𝑟
In addition, assume that 𝐴𝐴𝑘𝑘 is the link set of each routek.
Here, assuming a disaster phenomenon in which
random simultaneous multiple events occur in several
place and arbitral number, we consider the damage thatthe network receives (Fig.1). However, the event in thisstudy is expressed as a circular area (hereinafter referred
to as an “event disk”). If a link e is in the event disk, thenit is cut off. We also assume that the size of the event diskisis constant with the radius R. Also, if 𝑒𝑒 ∈ 𝐴𝐴𝑟𝑟𝑟𝑟
𝑘𝑘
disconnected, route k will be unavailable.
Descriptions of event disk assume, for example,
catastrophic damage of a fertile area due to an earthquake.
In Tokyo, there are scattered regions of about 6900
hectares in 28 areas (areas where particularly widespreadℛ𝐼𝐼𝑟𝑟𝑟𝑟 = ⋂𝑘𝑘∈𝐼𝐼 ℬ𝑘𝑘𝑟𝑟𝑟𝑟 ⋂𝑘𝑘∉𝐼𝐼 ℬ𝑘𝑘𝑟𝑟𝑟𝑟 ⋂ 𝒵𝒵
𝛹𝛹 𝑟𝑟𝑟𝑟 = Power(𝐾𝐾 𝑟𝑟𝑟𝑟 ) − {𝜙𝜙}

(1)

(2)

and its area is |ℛ𝐼𝐼𝑟𝑟𝑟𝑟 |. Here, 𝛹𝛹 𝑟𝑟𝑟𝑟 is obtained by removing
the empty set from the power set of 𝐾𝐾 𝑟𝑟𝑟𝑟 . In the example
of Fig.3, since the total number of routes is 3, there areseven possible failure areas because 23 − 1 = 7 .
However, in this case, there is no ℛ 𝑟𝑟𝑟𝑟{2,3} .
As is clear from (1), ℛ𝐼𝐼𝑟𝑟𝑟𝑟 means a region wherecombinations of routes to be disconnected are the same
when an event having a center point is included in theregion. Even if a plurality of events occur in the same
affected area, the situation does not change at all.
Therefore, it is only important whether or not an event has
happened within ℛ𝐼𝐼𝑟𝑟𝑟𝑟 . When points are randomly14817th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
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Paper No. 42
3.4. EVALUATION OF REMAINING ROUTES
We now evaluate the remaining routes 𝑟𝑟𝑟𝑟
even whenseveral events are happend. The route set 𝐾𝐾𝐽𝐽 which isremaining under a certain event pattern J is given by

distributed with a density ρ on the plane, the probability
𝑞𝑞(𝜈𝜈, 𝑆𝑆) that total v points are included in area S is givenby the spatial Poisson distribution as follows:𝑞𝑞(𝜈𝜈, 𝑆𝑆) =(𝜌𝜌𝜌𝜌)𝜈𝜈
𝜈𝜈!

exp[−𝜌𝜌𝜌𝜌]𝑟𝑟𝑟𝑟(𝜈𝜈 = 0,1,2, ⋯ ) (3)𝑟𝑟𝑟𝑟
𝐾𝐾𝐽𝐽 , we use the log sum variable

For this route set
based on the C-Logit model considering the duplication
𝑟𝑟𝑟𝑟
rate of the route and define the inclusive distance 𝐿𝐿𝐽𝐽 as
follows:

Using (3), the probability that an event will happen withinℛ𝐼𝐼𝑟𝑟𝑟𝑟 can be determined as
𝑞𝑞𝐼𝐼𝑟𝑟𝑟𝑟 = 1 − 𝑞𝑞(0, |ℛ𝐼𝐼𝑟𝑟𝑟𝑟 |)(7)

𝐾𝐾𝐽𝐽 = 𝐾𝐾 𝑟𝑟𝑟𝑟 −∪ 𝐽𝐽

(4)

𝑟𝑟𝑟𝑟

1

𝑟𝑟𝑟𝑟
𝐿𝐿𝐽𝐽 = − ln ∑𝑘𝑘∈𝐾𝐾𝑟𝑟𝑟𝑟 exp[−𝜃𝜃𝐿𝐿𝑟𝑟𝑟𝑟
𝑘𝑘 − 𝑐𝑐𝑓𝑓𝑘𝑘 ]𝜃𝜃𝐽𝐽

𝑐𝑐𝑓𝑓𝑘𝑘𝑟𝑟𝑟𝑟 = ln ∑𝑘𝑘′∈𝐾𝐾𝑟𝑟𝑟𝑟 �
𝐽𝐽

3.3. EVENT PATTERN
In this research, we assume that events happen randomly
not only in places but also in numbers. In that case, forexample, even if the route {1,2} is disconnected as a result,various patterns can be considered as the event situation.
For example, independent two events might happen in
𝑟𝑟𝑟𝑟
and ℛ 𝑟𝑟𝑟𝑟ℛ{1}{2} respectively, and route 1 and route 2 may
𝑟𝑟𝑟𝑟,
be disconnected. Meanwhile, an event happens in ℛ{1,2}and route 1 and route 2 are disconnected at the same time.
Therefore, it is necessary to enumerate all event patterns
for how to disconnect routes. When the number of routes
is 3 as shown in Fig.3, there are theoretically sevenaffected areas, and event patterns would be 27 = 128 intotal. Therefore, in order to classify whether or not an
event has happened for all ℛ𝐼𝐼𝑟𝑟𝑟𝑟 , we consider the power set
𝛺𝛺𝑟𝑟𝑟𝑟 of 𝛹𝛹 𝑟𝑟𝑟𝑟 :(5)

1

𝑉𝑉𝐽𝐽𝑟𝑟𝑟𝑟 = 𝑟𝑟𝑟𝑟

Note that 𝐼𝐼 ∈ 𝐽𝐽 because I is an element of 𝛹𝛹 𝑟𝑟𝑟𝑟 and J isan element of 𝛺𝛺𝑟𝑟𝑟𝑟 . That is, if 𝐼𝐼 ∈ 𝐽𝐽, it means that an event
happens inside the corresponding ℛ𝐼𝐼𝑟𝑟𝑟𝑟 , and conversely if
𝐼𝐼 ∉ 𝐽𝐽, it means that no event has happened within ℛ𝐼𝐼𝑟𝑟𝑟𝑟 .
Since the combination of all fault occurrence patterns isenumerated according to (5), each J shows different fault
patterns. The probability 𝑝𝑝𝐽𝐽𝑟𝑟𝑟𝑟 that a certain event pattern
J is happened can be calculate as (6):𝑝𝑝𝐽𝐽𝑟𝑟𝑟𝑟= ∏𝐼𝐼∈𝐽𝐽 𝑞𝑞𝐼𝐼𝑟𝑟𝑟𝑟 ∏𝐼𝐼′∉𝐽𝐽(1 − 𝑞𝑞𝐼𝐼′𝑟𝑟𝑟𝑟 )

𝑘𝑘

𝑘𝑘′

𝑟𝑟𝑟𝑟
�𝐿𝐿𝑟𝑟𝑟𝑟
𝑘𝑘 �𝐿𝐿𝑘𝑘′

�(9)

However, 𝐿𝐿𝑘𝑘 is the total length of route k and is𝑙𝑙 . Furthermore, 𝑐𝑐𝑓𝑓𝑘𝑘𝑟𝑟𝑟𝑟 is acalculated by 𝐿𝐿𝑘𝑘 = ∑𝑒𝑒∈𝐴𝐴𝑟𝑟𝑟𝑟
𝑘𝑘 𝑒𝑒
term (commonality factor) expressing similarity of routes,
and 𝜃𝜃 is a distance decay parameter.
Here, the mathematical properties of (8) and (9) aresummarized. The C-logit model is a type of route choicemodel based on random utility model. In the case thatroutes are no overlapped, 𝑐𝑐𝑓𝑓𝑘𝑘𝑟𝑟𝑟𝑟 = 0 in (9), and theinclusive distance of each route is equal to the inclusive
distance calculated by a simple multinomial logit model.
If there are n non-overlapping routes of length 𝑙𝑙 ∗ , theinclusive distance is given by 𝑙𝑙 ∗ − ln 𝑛𝑛 /𝜃𝜃 . Conversely,
when assuming the existence of a plurality of perfectly
matched routes, the inclusive distance obtained by the Clogit model is equal to the length of the matching routeirrespective of the number of routes. As a result, the larger
the number of routes, the shorter each route distance, andthe more these routes do not overlap, the more the𝑟𝑟𝑟𝑟
combined distance 𝐿𝐿𝐽𝐽 is calculated to be shorter. In
general, the shorter the distance between two points, thestronger the connection, so it can be considered that therobustness is high. Therefore, in this study, the evaluation
value 𝑉𝑉𝐽𝐽𝑟𝑟𝑟𝑟 of the remaining path is defined as the𝑟𝑟𝑟𝑟reciprocal of 𝐿𝐿𝐽𝐽 :Figure 3: Relation between the route k and ℛ𝐼𝐼𝑟𝑟𝑟𝑟

𝛺𝛺𝑟𝑟𝑟𝑟 = Power(𝛹𝛹 𝑟𝑟𝑟𝑟 )∑𝑒𝑒∈𝐴𝐴𝑟𝑟𝑟𝑟 ∩𝐴𝐴𝑟𝑟𝑟𝑟 𝑙𝑙𝑒𝑒𝑟𝑟𝑟𝑟

(8)

𝐿𝐿𝐽𝐽

(10)

Obviously when the inclusive distance is 0 (that is,when the origin r and destination s are the same point), theevaluation value becomes +∞ and becomes maximum.
Conversely, when the inclusive distance is +∞ , theevaluation value becomes 0, which is the minimum. That
is, 𝑉𝑉𝐽𝐽𝑟𝑟𝑟𝑟 can also be interpreted as an indicator ofproximity based on inclusive distance. Note that there is a𝑟𝑟𝑟𝑟
possibility that 𝐿𝐿𝐽𝐽 may become negative depending on
the value of θ, so we need to set the parameter so that it
𝑟𝑟𝑟𝑟
becomes 𝐿𝐿𝐽𝐽 ≥ 0.

(6)This obviously satisfies ∑𝐽𝐽∈𝛺𝛺𝑟𝑟𝑟𝑟 𝑝𝑝𝐽𝐽𝑟𝑟𝑟𝑟 = 1. For each event
pattern J, the route that is damaged at that time is the union∪ 𝐽𝐽, so the relationship between the probability of event
pattern and the route that is damaged has been sorted out.

149

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because 𝛺𝛺𝑟𝑟𝑟𝑟 increases dramatically according to the total
8
number of routes (|𝛺𝛺𝑟𝑟𝑟𝑟 | = 2�2 −1� ≃ 5.79 × 1076 ). It isnearly the limit of calculation. On the other hand, we set
the upper limit of the deviation rate of 1.5 for practicalreason of alternative routes. Finally, the distanceresistance parameter𝑟𝑟𝑟𝑟θ was set to 𝜃𝜃 = 12.0 so that theinclusive distance 𝐿𝐿𝐽𝐽 will not be negative. In order tocalculate (11), it is necessary to derive |ℛ𝐼𝐼𝑟𝑟𝑟𝑟 | in (4) but it
is difficult to calculate analytically. Therefore, we
uniformly arranging lattice points (representative points)
at intervals of 0.02 on the target area, and numericallycalculate |ℛ𝐼𝐼𝑟𝑟𝑟𝑟 | . On the other hand, all mathematicalexpression other than (4), including 𝛺𝛺𝑟𝑟𝑟𝑟 , were analyticcally calculated.

3.5. CALCULATION OF ROBUSTNESS
Based on the above preparations, this research gives therobustness 𝐺𝐺 𝑟𝑟𝑟𝑟 (𝜌𝜌, 𝑅𝑅) between certain OD pair rs on the
network as follows by using (6) and (10):= ∑𝐽𝐽∈𝛺𝛺𝑟𝑟𝑟𝑟 𝑉𝑉𝐽𝐽𝑟𝑟𝑟𝑟 ⋅ 𝑝𝑝𝐽𝐽𝑟𝑟𝑟𝑟

𝐺𝐺 𝑟𝑟𝑟𝑟 (𝜌𝜌, 𝑅𝑅)(11)

As is apparent from (11), this is the expected value of
𝑉𝑉𝐽𝐽𝑟𝑟𝑟𝑟 based on the routes that still remain even under thecondition that simultaneous multiple event has happened.
As mentioned above, in this research, we assume that thevalue of robustness is “quantified the function still
remaining even if it happens in a disaster”, and theproximity when the network is completely cut off is 0.
In addition, we can obtain the robustness 𝐺𝐺 𝑟𝑟 (𝜌𝜌, 𝑅𝑅)
for each node by fixing the origin and calculating theweighted average for every destination. Similarly,
robustness of the entire network 𝐺𝐺(𝜌𝜌, 𝑅𝑅) can be derived
by calculating the weighted average for every OD pair:
𝐺𝐺 𝑟𝑟 (𝜌𝜌, 𝑅𝑅) =𝐺𝐺(𝜌𝜌, 𝑅𝑅) =∑𝑠𝑠∈𝑁𝑁 𝑤𝑤𝑠𝑠 ⋅𝐺𝐺 𝑟𝑟𝑟𝑟 (𝜌𝜌,𝑅𝑅)∑𝑠𝑠∈𝑁𝑁 𝑤𝑤𝑠𝑠

∑𝑟𝑟∈𝑁𝑁 ∑𝑠𝑠∈𝑁𝑁 𝑤𝑤𝑟𝑟 𝑤𝑤𝑠𝑠 ⋅𝐺𝐺 𝑟𝑟𝑟𝑟 (𝜌𝜌,𝑅𝑅)∑𝑟𝑟∈𝑁𝑁 ∑𝑠𝑠∈𝑁𝑁 𝑤𝑤𝑟𝑟 𝑤𝑤𝑠𝑠

4.2. EFFECTS OF DISASTER SCALEFirst, we focus on the how the robustness G of the basic
network (Fig. 4 (a)) is affected when the event density ρand the radius of event disk R are variously changed. Fig.
5 shows the results how R affects when the event density
is set as 𝜌𝜌 = 0.25, 0.5, 1.0, 2.0. Similarly, Fig.6 shows theresult how 𝜌𝜌 affects when the radius of event disk is set
as 𝑅𝑅 = 0.1, 0.3, 0.5.
From the results, it can be confirmed that robustness
monotonically and exponentially decreases as the disasterscale such as ρ and R increases (when both ρ and R are 0,
𝐺𝐺 = 1.39). These results are natural because it is apparent
that the robustness finally converges to 0 as ρ and R
increase. On the other hand, it is confirmed from Fig.6 thatthe robustness changes can be characterized by the valueof R. Specifically, the decreasing process obviously differs
between in the case of 𝑅𝑅 = 0.1 and in the case of 𝑅𝑅 =0.3, 0.5, We consider that the size of the block surroundedby link is related. In this network, the interval of thecircular link is 1/3, so it is not so common that an event
disk cuts multiple routes and in the case of 𝑅𝑅 = 0.1. On
the other hand, in the case of 𝑅𝑅 = 0.3, 0.5 , it almost
corresponds to the size of two blocks, so it is easy to cut
multiple routes at the same time. Fig. 6 is would be a resultthat shows the influence of block size.

(12)
(13)

Based on the above discussion, the robustness of theremaining network which maintains the function without
being affected by the events is quantified under theassumption that a circular obstacle of radius R at a densityof ρ pieces per unit area happens randomly for places andnumbers. Note that comparing between networks ofdifferent scales is also possible because we calculate aweighted average rather than total. More remarkablefeature of our model is that ρ and R are given as variables.
By comparing these parameters in various ways, it ispossible to evaluate robustness taking into account thedifference in scale of disasters due to the magnitude of thedisaster.
4. NUMERICAL EXAMPLES
4.1. NETWORKS AND PARAMETERS
On the infinite plane Z, let us assume an idealized
network which has 3 circular and 12 radial links. We set
that the radius of the network is 1. In this case, the numberof nodes in the network is |𝑁𝑁| = 37, and the number oflinkes is |𝐸𝐸| = 72. In addition to this (a) Basic network,
we also prepare three types of derived networks; (b)No-core, (c) Three-quarters, and (d) No-core &Three-quarters (NC-TQ). There four networks areshown in Fig.4.
About parameters, we set the weight 𝑤𝑤𝑛𝑛 of arbitrary
nodes 𝑤𝑤𝑛𝑛 = 1 . Regarding the route set 𝐾𝐾 𝑟𝑟𝑟𝑟 , in thisnumerical example, k-shortest paths [7] were calculated
and set as follows:𝑟𝑟𝑟𝑟
𝐾𝐾 𝑟𝑟𝑟𝑟 = {𝑘𝑘|𝑘𝑘 ≤ 8, 𝐿𝐿𝑟𝑟𝑟𝑟
𝑘𝑘 ≤ 1.5 × 𝐿𝐿1 }4.3. EFFECTS OF THE HUB
Next, we calculate the robustness of the different four
patterns of networks (Figure 4). The parameters are set tofour conditions combining 𝜌𝜌 = 0.25,1 and 𝑅𝑅 = 0.1,0.3.
The results are shown in Fig.7 to Fig.10. In the figure,robustness of each node 𝐺𝐺 𝑟𝑟 corresponds the color of thenode and the total robustness 𝐺𝐺 is shown numerically.
Let us compare Fig.7 with Fig.8, and Fig.9 with Fig.10
to consider the effects of the hub in the network. It isclearly confirmed that the nodes on the innermost circularroad are more robust when the hub exists. Similarly, about
the robustness of the entire network 𝐺𝐺, the difference ofis 0.12 when comparing Fig.7 (a) with Fig.8 (a), which isabout 10% better value. Furthermore, the difference is0.26 when comparing Fig.9 (d) and Fig.10 (d), it is about
37% better. From this numerical example, we conclude
that the existence of the hub greatly contributes to enhance
the robustness of the network.

(14)

e assume that the total number of routes is 8 or less,150

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Figure 4: Examples of idealized networks
4.4. EFFECTS OF THE SHAPE
Finally, let us compare Fig.7 with Fig.9, and Fig.8 with
Fig.10 to clarify how the shape of network affects to theresults. Before observing the results, we should mention
that that the relation between the size of network and therobustness is not simple in our model. As the network
scale becomes smaller, the number of alternative routes
that can be taken between OD will of course decrease andthe inclusive distance will increase, which are factors that
reduce robustness. On the other hand, the smaller the
network scale, the smaller the total amount of disasters in
the range of influence. In addition, as OD pairs withrelatively long distances are also fewer, these would be theopposite factors that increase robustness.
Keeping this in mind, we now compare Fig.7 with Fig.9,
and Fig.8 and 10. Then It is natural even if some nodes
near center become robust in the case of three-quarters.
The nodes which acquire greater value are away from themissing 1/4 part, so it results to a decrease in long distanceOD pair. It means that the relative amount of the shortdistance pair increases, which results to the increase of therobustness. On the contrary, it is convinced that therobustness of the outer nodes, such as bottom or right end
nodes of three-quarter type, are lower in robustness,because the short distance pair would be decreased.
Moreover, when moving to the opposite region across themissing quarter part, it is necessary to bypass and the route
concentrates around the center. This also contributes toreducing the robustness. In this way, we conclude that themodel proposed in this research comprehensively
considers not only the influence of the change in region
shape on the route but also the distance distribution of OD.

inclusive utility. In addition, through numerical examples
in the idealized network, we discussed from various
viewpoints, such as the magnitude of disaster, the size ofthe block, the existence of the hub, the network shape, andthe robustness of individual OD pairs. These knowledges
about the robustness of the network must give us
suggestions for disaster prevention plan in a real society.
REFERENCES[1] Berdica, K. (2002): An introduction to roadvulnerability: what has been done, is done and should
be done, Transport Policy, Vol.9, pp. 17–127.
[2] Taylor, M.A.P., et al. (2006): Application ofaccessibility based methods for vulnerability analysisof strategic road networks, Networks and Spatial
Economics, Vol.6, pp.267–291.
[3] Jenelius, E., et al. (2006): Importance and exposure inroad network vulnerability analysis, Transportation
Research, Vol.40A, pp.537–560.
[4] Sohn, J. (2006): Evaluating the significance of
highway network links under the flood damage: anaccessibility approach, Transportation Research,
Vol.40A, pp.491–506.
[5] Cascetta, E., et al. (1996): A Modified Logit Route
Choice Model Overcoming Path Overlapping Problem.
Specification and some Calibration result1s forInterurban Networks, Transportation and Traffic
Theory, Proceedings of the 13th International
Symposium on Transportation and Traffic Theory,
Elservier Science, Oxford, pp.195–207.
[6] Cascetta, E., et al. (1998): Implicit Availability /Perception Logit Models for Route Choice inTransportation Netwroks, World Transport Research :Selected Proceedings of 8th World Conference on
Transport Research, Pergamon, Oxford, Anversa,
pp.15–24.
[7] Yen, J.Y. (1970): Finding the k Shortest Loopless Paths
in a Network, Management Science, Vol.17-11,
pp.712–716.

5. CONCLUSIONSIn this research, we focused on the spatial relationshipbetween multiple routes and proposed a mathematicalmodel to quantitatively evaluate the robustness of the
network. By considering not only the network topology
mainly pursued in the previous research but also its spatial
distributions at the same time, we could incorporate aphenomenon often observed, that is, a single eventsaffects multiple routes.We discussed the average of theevaluation values of the remaining network assuming
disaster-related events in which the number and location
happen randomly by combining several mathematical
tools such as power set, spatial Poisson distribution, and151

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Figure 5: Relations between the radius of event disk andthe robustness of networks

Figure 7: Robustness ofeach node(Basic)Figure 8: Robustness ofeach node(No-core)

Figure 6: Relation between the density of events andthe robustness of networks

Figure 9: Robustness of
Figure 10: Robustness ofeach nodeeach node(Three-quarters)(NC-TQ)152

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Paper No. 43

A MATHEMATICAL MODEL TO REPRESENT AN URBAN SYSTEM’S REGENERATIVECAPACITY FOR COPING WITH NATURAL DISASTERS
Y. SHIOZAKI1, and T. KATO2
1

Project Researcher, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, yuto@iis.u-tokyo.ac.jp(corresponding author)
2
Associate Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan, kato-t@iis.u-tokyo.ac.jp
Keywords: natural disasters, resilience, urban system, differential equation model
1. INTRODUCTION
In addition to disaster mitigation measures, the control
measure of an urban system’s ability to regenerate to adesirable situation in post-disaster phase should beconsidered. To control the capacity, the definition andmechanism of regenerative capacity needs to be clarified.
This study classifies the regenerative capacity into i)
Stability, ii) Absorptive capacity, and iii) Adaptability as aresult of review on the existing studies relating to urban
system’s regenerative capacity (e.g. [1], [2], [3]). Stability
is defined as the ability of an urban system to return to thepre-disaster situation after a disaster. Absorptive capacity
is defined as the ability of an urban system to absorb thedamage and maintain the condition in which the system
can recover. Adaptability is defined as the ability of anurban system to recover the damage and adapt the changeof socio-economic environment.
The relationship structure (mechanism) between the
Stability and its factors has been studied, and the disasterrecovery model of an urban system is established toconsider the measures to improve urban system’s Stability([1], [4]). On the other hand, regarding the Absorptive
capacity and the Adaptability, the concepts are suggested([2], [5]), but the mechanism is not sufficiently studied.
This study focuses on the Absorptive capacity and the
Adaptability. A mathematical model to describe thedynamics of an urban system’s state is established, whichis then used to analyze the mechanism of Adaptability andrepresent the concept of Adaptability.

Figure 1: The whole picture of mathematical modelof object urban system and the one of outside system. The
attractiveness 𝐴 𝑥, 𝑦 of object urban system isconsidered as the sum of three components: theattractiveness related to income per capita 𝑎 𝑥, 𝑦 , theone related to daily service 𝑎 𝑥, 𝑦 , and the one related tocongestion 𝑎 𝑥, 𝑦 . The attractiveness of outside system
is exogenously given a parameter 𝜔.
The dynamics of production capital 𝑦 𝑡 is decided by
the difference between the increment and the decrement.
The increment derives from the amount of investment toproduction capital, which the system allocates the
production 𝐹 𝑥, 𝑦 into by the constant rate 𝑟 . The
remaining of the production 𝐹 𝑥, 𝑦 is allocated into
labor population, and equally distributed among them.
The decrement corresponds to the degradation of
production capital.
In this urban system’s industry, the amount of
production 𝐹 𝑥, 𝑦 is decided by labor population andproduction capital. Scale economies operate in theindustry, but the amount of production is not supposed to.
exceed the upper limit 𝑘

2. A MATHEMATICAL MODEL
This study assumes an urban system model the state ofwhich is represented with labor population 𝑥 𝑡 andproduction capital 𝑦 𝑡 . Figure 1 shows the whole pictureof the model. In this model, there are only two cities: an
object urban system and an outside system.
The dynamics of urban system’s state is described by
the following differential equations model:𝑑𝑥⁄𝑑𝑡𝑟 𝐴 𝑥, 𝑦

𝜔 𝑥

(1)

𝑑𝑦⁄𝑑𝑡

𝑟 𝐹 𝑥, 𝑦 ⁄𝜀

𝛿𝑦

(2)

where 𝐴 𝑥, 𝑦
𝐹 𝑥, 𝑦𝑎 𝑥, 𝑦𝑘𝑎 𝑥, 𝑦𝑎 𝑥, 𝑦3. ABSORPTIVE CAPACITY
The streamlines on the 𝑥𝑦-plane, which are decided by
the vector field based on equation (1) and (2), represent
the dynamics of the urban system’s state. Given a set ofparameters to the equation (1) and (2), the streamlines andequilibria are obtained as Figure 2. Equilibrium 𝑸𝟏 and𝑸𝟑 are attractors, and equilibrium 𝑸𝟐 is a saddle point.
The pale gray- and dark gray-colored area on Figure 2 isthe basin of attractor 𝑸𝟏 and 𝑸𝟑 . The urban system’s

(3)
(4)

The dynamics of labor population 𝑥 𝑡 is described as
proportional to the difference between the attractiveness153

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Paper No. 43

Figure 2: Streamlines, equilibria, basinof attractor, and the degree of Absorptive
30000)
capacity (𝑘Figure 3: 𝑥𝑦-coordinates of equilibria and basinof attractor by the change in the value of 𝑘state, the initial value of which is located on a basin of
attractor, will converge into the attractor. Varying thevalue of parameters, the shape of streamlines and thelocation of equilibrium is changed, and the equilibrium
𝑸𝟐 and 𝑸𝟑 can be disappeared depending on the value
as shown on Figure 3.
The degree of Absorptive capacity of urban system,
whose state is located at □ on Figure 3, is represented
by the bold-black-lined area. Assuming that labor
population would be moved out of the system andproduction capital would be decreased to a certain degree
by a disaster, disaster damage would make the system’s
state move to left-lower direction on Figure 3. The
devastated system can sustain if the state is still located in
the basin of attractor 𝑸𝟑 . Hence, the system’s Absorptive
capacity is reflected by the basin of attractor 𝑸𝟑 .
Analyzing how the Absorptive capacity is influenced by
the change in parameter values relating to thecharacteristics of the urban system, the relational structure
between the characteristics and the capacity is clarified.

system’s state needs to be located in the basin of attractor
𝑸𝟑 when the attractor reemerges. Therefore, attractor 𝑸𝟑
should be restored as soon as possible.
Adaptability can be considered as a capacity of urban
system to restore an attractor where the system can besustainable in case that the attractor is not existing.
5. CONCLUSIONFirst, this study builds up a differential equation model
to describe the dynamics of an urban system state.
Secondly, the model represents the degree of Absorptive
capacity, and clarifies the mechanism of Absorptive
capacity by the change in parameter values relating to thecharacteristics of the urban system in the model. Finally,
this study explains the concept of Adaptability with themathematical model.
REFERENCES
Reference to a journal publication:[1] M. Bruneau et al., (2003), “A Framework to
Quantitatively Assess and Enhance the Seismic Resilienceof Communities,” Earthquake Spectra, Vol.19, No.4
pp.733–752[2] K. M. Bruijn, (2004), “Resilience and Flood Risk
Management,” Water Policy, Vol.6, pp.53-66[3] Y. Shiozaki et al., (2015) “The Concept of Urban
System Resilience to Natural Disasters,” J. Japan Societyof Civil Engineers, Ser. D3, Vol.71, No.3 pp.127–140 (inJapanese)[4] S. B. Miles, and S. E. Chang, (2006), “Modeling
Community Recovery from Earthquake,” Earthquake
Spectra, Vol.22, No.2, pp.439-458[5] F. H. Norris et al., (2008), “The meaning of systemrobustness for flood risk management,” Environmental
Science & Policy, Vol. 14, pp. 1121-1131

4. ADAPTABILITY
Adaptability is necessary for an urban system when adisaster causes damage on the urban system, and thesocio-economic environment of urban system is changing.
Here, this study assumes an urban system whose industry
is declining. In the above mathematical model, thedeclining industry is represented by the decreasing ofin the urban system.
production upper limit 𝑘
Attractor 𝑸𝟑 is disappeared when the value of 𝑘is lower than a certain degree. At this time, the urban
system’s state is deteriorating, and the urban system will
be eventually abandoned without disaster as shown in
Figure 3 i). Moreover, if a disaster happens then, thedeterioration will be accelerated.
In this situation, the urban system has to create a newtoindustry with enough production upper limit 𝑘
make the attractor 𝑸𝟑 reemerge. In addition, the urban

154

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 57

A SEAMLESS FRAMEWORK FOR INDOOR-OUTDOOR INTEGRATION OF BUILDING DATAFOR EMERGENCY EVACUATION
N. MAHESHWARI1, K. S. RAJAN2
Lab for Spatial Informatics, IIIT Hyderabad, Hyderabad, India
1nishith.maheshwari@research.iiit.ac.in2

rajan@iiit.ac.in

Keywords: evacuation, indoor space, modeling, framework
1. INTRODUCTION
In case of an emergency in a building like fire,effective evacuation of people inside the building to asafe place is necessary. The steps involved is doing sostarts from a room or hall (with furniture or otherobstacles) to the connecting corridors leading to the exitfrom the floor and eventually exiting the building. After
exiting the building the evacuees need to move to an
evacuation site away from the building. This flow
involves interaction of evacuees with multiple levels ofbuilding with different level of details.
A set of challenges are associated for a seamless flowof evacuees through these levels. One of the major
challenges is regarding the data available for every level.
For example a building may have only the floor planlayout available without the information about theelements comprising the space (obstacles like furniture).
Even if the data is available, it may be in an incompatible
format or with limited information to interact with anevacuation model. This brings us to the next challenge
which deals with the processing and computation
limitation of handling different types of data using aunified model. From the evacuee's perspective, initiallyonly a local view of the space is needed and providing
the whole view may lead to overload of information andcause confusion. As the scenario changes the detail of
information should also change. So a need for proper
information dissemination at different levels is needed.
Recent research works have handled evacuation
modeling in various ways. Some works have focused on
constructing a grid-based model to generate navigationroutes for evacuation using 2D floorplans [1,2] and BIM
IFC data [3] of the building. Others generate a graphnetwork using the 2D floorplans [4] or by collapsing the
3D geometry of the building to 2D polygons [5,6].
But the major challenge remains that how can thesedifferent levels of data be incorporated in a frameworkand how we can have a seamless interaction between
them.
Hence this work has focused on proposing aframework which defines the data in an hierarchicalmanner such that each level of hierarchy corresponds tothe type of information available and the kind of model
to be used for computing navigation routes. It focuses on
the 2D aspect mainly but has the flexibility toincorporate 3D data at floor and space level. The
framework suggested here is a conceptual one and is awork in progress.
2. HIERARCHICAL FRAMEWORKThe framework has been defined in the following threelevels of hierarchy Space level
The space level refers to a unit space (like room) witha dense amount of indoor information like the location ofchairs, tables, shelves and other furniture available.
The data models that can provide data for this level are
CityGML LOD4, architectural drawings with furnishing
information and detailed BIM IFC models of thebuilding.
In the context of evacuation, this level serves as thestarting point for the evacuees. The navigation is done toexit the space, while avoiding the obstacles, to connect toother indoor spaces.

Figure 1: Example of a space with furniture155

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 57

Floor level
This level of hierarchy considers a building floor leveland focuses on navigation between the spaces on a floor
and between multiple floors. The modeling is done basedon the semantic model presented in [7].
During evacuation the goal is to exit the floor to moveto a lower level (if on an upper floor) and eventually
exiting the building. Using the semantics of the spaces anavigational network is generated which would be used
for routing the evacuees.

3. CONCLUSIONS
Each level of hierarchy handles data with a different
level of detail (Space level: Spaces with the objects
inside like furniture, Floor level: Floor-plan of eachfloor, Outdoor level: Building footprint and outdoor
features). Such a framework would be able to provide thebest functionality based on the type of data available inany given scenario by using the appropriate method forthe task at hand.
REFERENCES[1] J. Sun and X. Li, (2011) “Indoor evacuation routes
planning with a grid graph-based model,” 19thInternational Conference on Geoinformatics, Shanghai,
pp.1-4.
[2] L. Tan, H. Lin, M. Hu and W. Che, (2014) “Agentbased simulation of building evacuation using a grid
graph-based model,” IOP conference series: earth andenvironmental science, Vol.18, No.1
[3] Y. H. Lin, Y. S. Liu, G. Gao, X. G. Han, C. Y. Lai and
M. Gu, (2013) “The IFC-based path planning for 3D
indoor spaces,” Advanced Engineering Informatics,
Vol.27, No.2, pp.189-205[4] S. Rai, M. Wang and X. Hu, (2015) “A graph-based
agent-oriented model
for building occupancy
simulation,” Proceedings of the Symposium on AgentDirected Simulation, Society for Computer Simulation
International, pp.76-83[5] L. Zhang, Y. Wang, H. Shi and L. Zhang, (2012)“Modeling and analyzing 3D complex building interiors
for effective evacuation simulations,” Fire Safety
Journal, Vol.53, pp.1-12[6] M. Meijers, S. Zlatanova and N. Pfeifer, (2005) “3D
geoinformation indoors: structuring for evacuation,”
Proceedings of Next generation 3D city models,
Germany Bonn, Vol.6[7] N. Maheshwari and K. S. Rajan, (2016) “A semantic
model to define indoor space in context of emergency
evacuation,
International
ArchivesofthePhotogrammetry, Remote Sensing & Spatial Information
Sciences, Vol.41

Figure 2: A floor plan with semantic labels.
Outdoor level
In this level, integration with the outdoor is explored.
From an evacuation point of view even exiting thebuilding may not be safe enough (as in the case of a fire)
and the evacuees would need to be moved to a location
away from the building. This level would also be able toincorporate managing the incoming first responders andother resources like hydrants around the building. The
modeling of this level can be done using the existing GIS
models for outdoors.

Figure 3: A set of buildings and the roads around them.

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 77

A STUDY ON THE RESIDENT’S CONSCIOUSNESS OF TSUNAMI EVACUATION BEHAVIOR
AFTER BUILDING THE TSUNAMI EVACUATION MOUND
K. MIYAUCHI1 , and K. TAKADA2
1

Doctoral student, Graduate School of Advanced Science and Technology, Tokyo Denki University, Hatoyama, Japan
Professor, Department of Architectural and Civil Engineering, Tokyo Denki University, Hatoyama, Japan,
takada67@gmail.com (corresponding author)
Keywords: Tsunami Evacuation, Evacuation Mound,2

1. BACKGROUND
In this study, evacuation method at Horikiri d istrict inTahara city, Aichi prefecture, was focused on since there
would be hit by forthcoming Nankai trough earthquakewith seis mic intensity of 7 at maximu m and also
inundated with 2m depth within 18 minutes after theearthquake. There are 1,291 residents and 410
households as of 31 December, 2016. The rat io of elderly
person with over 65 years is around 30%. This h igh rat io
makes evacuation in this district more sever.
Meanwhile, th is district is located in low flatland, as
shown in the Figure 1, so that evacuation distancebecomes longer. As shown in the Figure 2, Atsumi sport
spark, which locates on the slightly elevated hill andwhich is about 2 km away fro m residential area, isdesignated as tsunami evacuation place by themunicipality. Since it is difficult to move to theevacuation place by foot before being inundated, themunicipality set safety line as minimu m goal in order not
to give up their own evacuation and the safety line ismarked on the road where 1.5m h igher than estimatedinundation level as shown by the picture in the in the
Figure 2.
Considering such difficulty of the evacuation in this
district, the municipality decide to build a tsunami
evacuation mound on the site using the elementary
school near the residential area. The top of theevacuation mound is 15 meters above sea-level which ishigher than estimated inundation height with 11m-13m.
The space of the mound is 850 square-meter as shown in
the Figure 2, and 500 citizens can evacuate temporary.
In this study, influencing of the mound on the citizen ’s
consciousness of tsunami evacuation was investigated byconducting questionnaire survey.

Figure 1: Landscape of the Horikiri district

Tsunami evacuation moundFigure 2: Location of the evacuation place and tsunami
evacuation moundTable 1: Outline of the survey
Households
Resident
Number of surveys distributed
Number of surveys collected
Collection rate

2. QUESTIONNAIRE SURVEY
In this study, a questionnaire survey was conducted toobtain the information main ly on (i) the imp lementationof disaster prevention and preparation measures in ahousehold, (ii) the evaluation o f the tsunami evacuation
mound, (iii) the tsunami evacuation procedure(evacuation timing, evacuation place, mov ing means)and (iv) individual and household attributes. Outline of
the survey is shown on Table 1.

378
1238
756
303
40.1%

Figure 3 shows the evaluation of the tsunami
evacuation mound. There are 10 question items fro m (a)to (j). The contents of the question is mentioned above
the title o f the figure. Evaluation results of each item isshown by age group. As shown in the figure (a), older
age groups thinks that the mound will contribute to safer
evacuation of older people. On the other hand, 40% of
the older age group thinks that the mound cannot
contribute to the safer evacuation. Meanwhile, as shownin the figure (b), all age groups think that the mound

3. EVALUATION OF THE EVACUATION MOUND

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 77
100%

80%
60%

20

2

13

11

46

25
25

27

40%

80%

109

32
31

22

0%

3

3

under 50

50-59

Absolutely

11

13

30

60-69

over 70

Total

A little

Not so much

Not at all

9

5

14

20

13

80%
60%

4

0%

29
102

29

39

37

22
10

under 50
Absolutely

34

30

1
50-59

60-69

8

A little

0%

10
under 50

Absolutely

2
50-59

A little

80%
60%

19
18

118
15

over 70

80%

Not so much

40%
20%

34

0%

Total
Not at all

20%
0%

29

14

21

18

6
13

48
70

126

6

6

12

16

50-59

60-69

over 70

A little

17

13

Not so much

8

30

11
4

Absolutely

100%

32

35

22

27

40%
20%

33

0%

8
under 50

Absolutely

2

4

50-59

60-69

A little3

Not at all

0%

14
0
50-59
A little

30

10over 7080%

0%2under 50

Absolutely

24

26

29

10

(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)

1
50-59

17

Total

Not so much

24

24

30
5

28

32

10%

20%

137

30%

40%

50%

29

6

19

31

3

8

11

60-69

over 70

Not so much

60%

70%

80%

90%

designated evacuation place(shrine)

Tsunami evacuation moundother place

Total

Other

1

170

24 2

0

4

1

Evacuation moundNot at all

100%

27
0%

94

foot

121

bicycle19
20%

motorsycle

40

2 0 2 1

119Sports park

34

73

23

Shrine650-59
A little

24

6
22

4

17

9
21

20 12 0

2

40%

55
60%

automobile by myself

3
80%

100%

automobile by otherFigure 5: Evacuation place and moving means incase of daytime

27
Total
Not at all

6

25

14

74

33

38

38
41

150

20%
0%

11
under 50

Absolutely

6

6

50-59

60-69

A little

13

over 70

Not so much

84

80%
60%

15
22

14

26

14
27

40%
83

6

7

60-69

over 70

Not so much(i)3

designated evacuation place(sports park)

68

6

over 70

27

102

18

A little

40

Figure 4: Selected evacuation place

125
25

36

Total
Not at all

(h)

20

18

109

135

60%

Total

Not at all

29
18

daytime

0%

69

7

10

under 50

40%
106

25
22

Not at all

60-69

100%

60%

20%

30

6

(g)

40%

20

12

Absolutely

100%
35
120

Not so much

100%
80%

Not so much

18

40%

20%

40

36

21

39
Total

80%

Total

23

30

96

(f)

11

80%
60%

15
over 70

32

(e)
100%

12
60-69

5

27

under 50

60%

32

29

under 50
Absolutely

midnight
140

(d)

9

36

40%

29

100%

(c)
100%

80

20%

60%

32

40%
20%

2
21

27

25

(b)
10

25

1

20

26
35

(a)
100%

10

60%
40%

98

20

25

20%

100%

16
Total
Not at all

20%

0%

28

7
under 50

Absolutely

9
27

28

27

3

7

9

50-59

60-69

over 70

22

A little

Not so much

Figure 6: Evacuation place and moving means incase of midnight

52
102

Total

105

Evacuation mound26

ShrineTotal
Not at all

Sports park

(j)

0%

Evacuation of myself becomes safer.
Evacuation of support-needed person becomes safer.
Evacuation from seaside becomes safer.
Start time of evacuation can be shifted back.
Selection of the evacuation place according to the intensity ofearthquake becomes possible.
More time can be devoted to support the evacuation ofhandicapped citizen.
Tsunami evacuation by automobile can be reduced.
Citizen comes to be conscious for tsunami evacuation routinely.
I come to think that evacuation place for myself is the evacuation
mound.
Number of non-handicapped citizen who thinks that theyevacuate to the evacuation mound increases.

20%

40%

60%

0-1 min.

1-2 min.

2-3 min.

3-4 min.

5-10 min.

10-15 min.

15-20 min.

20 min.-

80%

100%

4-5 min.

Figure 7: Evacuation place and evacuation timing incase of daytime
Total
Evacuation moundShrineSports park
0%

Figure 3: Evaluation of the tsunami evacuation mound

20%

40%

60%

0-1 min.

1-2 min.

2-3 min.

3-4 min.

5-10 min.

10-15 min.

15-20 min.

20 min.-

80%

100%

4-5 min.

Figure 8: Evacuation place and evacuation timing incase of midnight

cannot contribute to safer evacuation for of supportneeded person. Moreover, as shown in the figure (h),citizens think that there is existence effect to evoke
tsunami evacuation routinely.

citizens tend to select foot as moving mode during
midnight. Figure 7 and 8 show the relation between
evacuation place and evacuation timing. It indicates thatthe evacuation timing during midn ight is delayed and thetiming of the cit izen who choose the evacuation moundis especially delayed.

4. ASSUMED EVACUATION PROCEDURE
The respondents were requested to answer theconsidered evacuation procedure. Figure 4 shows theresult of selected evacuation place during daytime andmidnight. It shows that the evacuation mound locates atresidential area is selected during midn ight rather thanduring daytime . Meanwhile, Figure 5 shows the relation
between evacuation place and moving means to theselected place during daytime and Figure 6 shows therelation during midnight. Co mparing these figures,

4. CONCLUS IONSIn this study, the citizen ’s evaluation to the tsunami
evacuation mound and the considered evacuation
procedure was examined. As the results, the influence ofthe mound on cit izen’s evacuation procedure was
identified.

158

USMCA 2018

SESSION 9
DISASTER RISK & RESPONSE I

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 38

ANALYZING WIDE AREA POST SEISMIC EFFECTS OF THE GORKHA EARTHQUAKEUSING PERSISTENT SCATTERER INTERFEROMETRY ON SENTINEL-1 IMAGES
A. TIWARI 1, A. B. NARAYAN1, M. DEVARA 2, R. DWIVEDI2, O. DIKSHIT1

1

Indian Institute of Technology, Civil Engineering - atiwari@iitk.ac.in

2

Motilal Nehru National Institute of Technology- (rgi1703, ramjid) @mnnit.ac.in

1

Indian Institute of Technology, Civil Engineering – (avadhbn, onkar)@iitk.ac.in

ABSTRACT
Deformation events including landslides, flood and earthquakes occur frequently in the inhabited Kathmandu city in
Nepal and surrounding mountains after the major Gorkha earthquake (8.1 M w) in 2015. Information about the pattern andtemporal rate of movement can be used as causative factors while developing rescue systems. In this study, a total of 21
Sentinel-1 Interferometric Wide Swath (IW) descending pass images of tracks 92 and 158, covering a time period of 27
months, are processed using the Persistent Scatterer interferometry (PSI) algorithm to estimate wide area post seismic
effects of the Gorkha earthquake in 2015 and other deformation events in Nepal. The wide swath images provide a swath
width of nearly 250 km divided in three sub-swaths. PSI algorithm was applied to two complete sub-swaths of the images
corresponding to the two tracks, resulting in extraction of 360532 and 1177124 measurement pixels for the Mid-Westernand Western Nepal regions respectively. In addition, a region containing the Kathmandu city and its surroundings wasprocessed using 11 images of track 92. From the 1 dimensional Line Of Sight (LOS) displacement maps, it is evident that
the Kathmandu city underwent subsidence at a rate of 200 mm yr-1. Also, the hilly regions near to the Gorkha earthquake
show southward downward movement (-200 to 250 mm yr-1). Apart from subsidence, some hilly slopes show uplift
ranging from 200 to 520 mm yr-1. Analyzing the measurement pixels selected in by the PSI approach, it is found thatpixels selected in the mountainous regions have larger topographic error contribution as compared to the urban area
(Kathmandu and near surroundings), which constructed a bias in the displacement computation in case of hilly areas.
From the time series displacement estimates generated from the processing of two tracks, it is observed that there are anumber of regions showing large displacement magnitudes with a regular pattern, and can become cause of deformation
events in near future. Regular time series monitoring using the Sentinel-1 IW data, along with GPS observations canprovide information about the 3 dimensional displacement signature.
Keywords: Keywords: Land subsidence, multi-temporal radar interferometry, Persistent Scatterers
1. INTRODUCTION
Analysis of deformation events requires identification of
study site, displacement measurement and interpretationof the displacement pattern. Deformation zones with aspread of less than a km or two, can generally be surveyed
temporally using ground based geodetic surveying
methods. Such field surveys involve the application ofgeodetic sensors like Global Navigation Satellite System(GNSS), Laser Scanning, Photogrammetry, Total Stationand level network surveys. However, such surveys canbecome infeasible for analysis of deformation activities ofvery large areas e.g. area greater than 100 km, sincegeodetic surveys require locating sensors at various
locations within the deformable zones and the surveys
may get labour, cost and time intensive. Over the last
decade, synthetic aperture radar interferometry (InSAR)
has been successfully employed to retrieve one dimension
line of sight (1D LOS) displacement velocities ofrelatively large areas. Each measurement pixel in a SAR
interferogram acts a measurement point on the field anddetects mm level movement of the surface. Processing a
stack of SAR interferograms corresponding to images

acquired at different times can provide time series
displacement estimates. During the last decade, multitemporal SAR interferometry (MT-InSAR) algorithms areapplied to detect displacement time series ([1], [2], [3],[4]). Information about the pattern and temporal rate of
movement are used as causative factors while developing
rescue systems.
The Himalayan region is predominantly affected bydeformation events primarily comprising landslides,
earthquakes and land subsidence. In this study, theKathmandu city lying in Nepal and the surrounding
mountains are investigated. Persistent Scatter
Interferometry (PSI) based MT-InSAR approach isapplied to investigate post seismic effects of the Gorkha
earthquake (8.1 Mw) in 2015. The earthquake drasticallyaffected the inhabited Kathmandu city in Nepal andsurrounding mountains [5]. Next section describes thedataset used in this study, followed by the Methodology
section. Results and discussions on the displacement maps
are elaborated next, followed by Conclusions.

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 38
2. STUDY AREA AND SATELLITE DATASETS
Occurrence of the Gorkha earthquake (MW 7.2) in 2015,
along with subsidence activities associated with the
Kathmandu city and areas lying in the Mid-Western Nepal
encouraged deformation investigations of three different
study areas for this research work. Subduction of the
Indian plate beneath the Eurasian plate has caused uplift
in the Himalayas, which is one of the prominent reasonsfor presence of tectonic events [5]. Gorkha lies in the Main
Himalayan Thrust, an active deformation zone. Further,
the densely populated Kathmandu city, lying in the lesser
Himalayas, lies in an active seismic zone. The city has
witnessed earthquakes nearly hundred years back, and iscurrently affected by subsidence activities [5]. Figure 2
shows the three study sites, covering Mid-Western andWestern Nepal, and the city of Kathmandu. In order to see
the effect of the earthquake, the other two areas werechosen on either sides of the earthquake. Kathmandu lies
82 km south east of the earthquake Hypocenter [7]. Other
end of the earthquake lies in the Himalayan region and isprone to wide area deformation.

Table 1: Sentinel-1 datasets used to investigate
deformation events in Nepal.
Parameters

Mid-Western
Nepal
158
10
0 to 240
0 to 180

WesternNepal
92
110 to 264
0 to 160

Track#images*Btemp$
Bperp#- No. of images*- Range of temporal baselines (days)$- Range of perpendicular baselines (meters)

Kathmandu
92
11
0 to 264
0 to 160

3. METHODOLOGY
In this study, multi-temporal SAR interferometry isapplied on Sentinel-1 TOPS images. This required a stackof co-registered interferograms, which were generated bydifferential interferometric processing of a set of images
belonging to same track and having the same groundcoverage. The Sentinel-1 images contain three sub swaths,
each sub swath covering a swath of about 80-100 km [6].
A specific sub-swath is selected based on the area ofinterest (AOI), and if the AOI lies in more than one sub
swath, then more than one sub-swaths are processed
together. This can be accomplished by processing
individual sub-swaths and merging the sub-swaths later.
Since three different study areas were chosen in this study,
three set of images were used separately. Further, in all thethree cases, the investigated site was covered in a single
sub-swath, avoiding the requirement of merging the subswaths. A master image was chosen for each image stack,based on the criteria of minimizing the perpendicular andtemporal baseline, while maximizing temporal coherence.

Two sets of 11 and 10 Sentinel-1 interferometric wideswath (IW) images corresponding to tracks 92 and 158
respectively, and covering a time period of 18 months
were acquired. Since images of track 92 covered theregion near to the Gorkha earthquake and the Kathmandu
city, a single stack was used with different subsets andsub-swaths during the MT-InSAR processing. Since
Sentinel-1 images have relatively reduced temporal andspatial baselines than the earlier missions, greater numberof measurement points was expected. Table 1 shows thedatasets used in this study and the relevant information
required for MT-InSAR processing.

Figure 1. Google earth image of the study area. White rectangles show coverage of different set of Sentinel-1 image

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 38
The processing was divided into two steps, (i) generationof differential interferogram stack and (ii) MT-InSAR
processing of the stack of differential interferograms. For
stack generation, the Sentinels Application platform(SNAP) toolbox was employed. The stack was later
exported to the Stanford method of Persistent Scatterer
Interferometry (StaMPS) environment for MT-InSAR
processing.

unwrap the phase of the selected PS pixels. Once
unwrapped, the unwrapped phase were converted to one
dimensional line of sight (1D LOS) displacement. A 1D
LOS velocity map generated from the above analysis
showed time series velocity of each PS pixel over theperiod of study. The next section presents the results
obtained by following the above mentioned methodology
on the three study areas.

Each image in the stack was split into one sub-swath, suchthat it includes the same area ground coverage for all theimages. Orbital corrections were applied to reduce theorbit related errors. The images were then co-registeredwith respect to the chosen master image, and resampled
onto the grid of the master after co-registration. Once coregistered, each image was deburst to remove demarcation
boundaries present in each sub-swath. The whole stack
can now be cropped using the subset operation for
selecting the AOI. Complex multiplication of each slave
image with the master was then carried out, resulting ininterferogram generation. A 3 arc second Digital elevation
model (DEM) from SRTM was used for topography
removal, finally producing a stack of differential
interferograms [4]. Figure 2 shows the procedure followed
for preparing a stack of differential interferograms. Using
this procedure, three stacks of differential interferograms
were generated, and exported to StaMPS environment for
MT-InSAR processing.
MT-InSAR processing of the differential interferogram
stack was performed using the Persistent Scatterer
Interferometry (PSI) algorithm in StaMPS environment.
The steps primarily involved selection of PS pixels, phaseunwrapping and displacement estimation [4]. The MTInSAR method followed in this study is shown in Figure
2. Initially, a set of candidate PS pixels were selected using
the amplitude dispersion characteristics, i.e. the ratio ofstandard deviation and mean of the pixels in a time series.
The candidate pixels were tested for phase stability using
time series phase deviation. Pixels which passed the testof both amplitude dispersion and phase stability wereselected as PS pixels.

Figure 2. Multi-temporal InSAR processing chain for
Sentinel-1 wide swath images.

4. RESULTS AND DISCUSSION
MT-InSAR processing of the Mid-Western and Western
Nepal using the PSI algorithm resulted in the extraction of
360532 and 832939 measurement points respectively.
Figure 3 shows the 1D LOS velocity plots of both theregions, with cold colours (blue) indicating movement
towards the LOS and warm colours (red) showing
movement away from the satellite LOS. In case of MidWestern Nepal, it is observed that Khalanga andDamachaur regions had encountered subsidence at a rateof ~100 mm yr-1. For the western regions lying near to
Gorkha, the higher magnitude subsidence is observed,
with the complete displacement values ranging from-249.6 to 522.9 mm yr-1. Pokhara, Besisar and Byas are
the areas affected by subsidence. Mountainous regions
near to Gorkha seem to have uplifted during the period of
observations. Figure 4 shows the 1D displacement mapof the Kathmandu city and near surroundings. It isobserved that the city encountered subsidence at a rate of
200 mm yr-1. Apart from Kathmandu city, a nearby region

The interferometric phase of these pixels containcomponents attributed to atmospheric error  a , surface
displacement  def , topography  t , and noise  n , asshown in equation (1). The term k denotes the unknown
number of phase cycles required to obtain the unwrapped
phase value.

int  def  t  a  m  n  k.2(1)

Removal of terms other than  def from theinterferometric phase could help in detection of temporal
displacement. However, since the phase value is cyclic(wrapped to modulo 2 ), the values need to be
unwrapped. Hence, phase unwrapping was done to16117th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 38
named Tokha observed subsidence at a rate of ~ 150 mm
yr-1.
Qualitative assessment of the displacement estimates was
further carried out in order to find the accuracy of thedeformation estimates. For this, error arising fromdifferent components of the interferometric phase was
evaluated. Error estimates of the master related errors,
orbit errors and phase noise had negligible magnitude.
However, topographic error estimates showed highmagnitude. The topographic error can be attributed toerrors associated with external DEM, which is used toremove topography from the interferometric stack.
Furthermore, it is also noticed that the DEM elevation
computations in case of hilly terrain is erroneous, with theerrors reaching up to 50 meters in some cases.

Figure 3. Time series velocity plots overlaid on Google earth images for the Mid-Western and Western Nepal regions.
(a) Mid-Western region and (b) Western Nepal.

Figure 4. Time series velocity plot overlaid on Google earth image of the Kathmandu city.

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Paper No. 38
Figure 5 shows the topographic errors plotted on the
Google earth images of the Mid-Western and Western
Nepal. It is revealed from the two plots (Figures 5 (a) and(b)) that the hilly areas have higher topography
contribution. The error values ranged from -0.199 to
0.175 and -0.361 to 0.105 radians m-1 for the Mid-Westernand Western Nepal respectively. The Western Nepal

region is near to the Gorkha, and is surrounded by
mountains, which can be the reason for high magnitude of
topographic errors. Moreover, for the Kathmandu city,which is situated at relatively less altitude, has lower
values of topographical error, as shown in Figure 6. The
error estimates in this case range from -0.101 to 0.102
radians m-1.

Figure 5. Plots of topographic errors for the displacement estimates of the Mid-Western and Western Nepal regions. (a)Mid-Western region and (b) Western Nepal.

Figure 6. Plot of topographic error for the displacement estimates of the Kathmandu city.

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Paper No. 38
5. CONCLUSION
Three wide areas covering the Mid-Western, Western andCentral Nepal containing the densely populated
Kathmandu city was investigated for presence of
deformation events using the MT-InSAR approach on
Sentinel-1 images. PSI based MT-InSAR approach
extracted good number of measurement points in all thethree areas, and detected large magnitude subsidence inareas lying close to Gorkha and in the city of Kathmandu.
Regular monitoring of the detected deformation zones canhelp in early rescue operations. It is further revealed thatthe displacement estimates were affected by the
topographical error estimates, which was higher in case ofhigh mountains situated near to Gorkha while showing
significant presence in the displacement estimation of all
the sites. More time series observations, along with the
improvement of topographical error estimation can
provide better insight into the ongoing wide area
deformation activity.

REFERENCES[1]. Crossetto, M., Monsserat, O., Gonzalez, M.C.,
Devanthery, N., Crippa, B., (2016). “Persistent Scatterer
Interferometry: A review”, ISPRS Journal of
Photogrammetry & Remote Sensing, 115, 78-89.
[2]. Ferretti, A., Prati, C., and Rocca F.,(2000). “Nonlinear subsidence rate estimation using
Permanent Scatterers in differential SAR”, IEEE Trans.
GARS Vol. 38, pp. 2202 – 2212, September 2000.
[3]. Ferretti, A., Guarnieri, A.M., Prati, C., Rocca, M.,(2007). InSAR Principles: Guidelines for SAR
Interferometry Processing and Interpretation, TM19, The
Netherlands.
[4]. Hooper, A., Segall, P., and Zebker, H., (2007).
“Persistent Scatterer InSAR for Crustal Deformation
Analysis, with Application to Volcan Alcedo, Galapagos”
Journal of Geophysical Research, 34.
[5]. Krishnan P.V.S., Kim, D.J., Jung, J., (2018).
“Subsidence in the Kathmandu Basin, before andafter the 2015 Mw 7.8 Gorkha Earthquake, Nepal
Revealed from Small Baseline Subset-DInSAR
Analysis” GIScience & Remote Sensing, Vol. 55 (4), 604621.
[6]. Veci, L, 2015. TOPS interferometry tutorial, ESA
Sentinel-1 toolbox, Array systems computing Inc.
[7]. Sato, H. P., and Une, H., (2016). “Detection of the2015 Gorkha earthquake-induced landslide surface
deformation in Kathmandu using InSAR images
from PALSAR-2 data” Earth, Planets and Space, 68-47.

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 76

A STUDY ON THE ASSESSMSNT OF REGIONAL EVACUATION INFORMATION USINGMETEOROLOGY INFORMATION IN JAPANKazuhiro NAGAKI1, Yuma MORISAKI2, Makoto FUJIU3, and Junichi TAKAYAMA4
Student, Kanazawa University, Department of Environmental Design, JAPAN, kazuhiro618@stu.kanazawa-u.ac.jp
Bachelor(Eng.), Kanazawa University, Department of Environmental Design, JAPAN, yki20@ stu.kanazawa-u.ac.jp
3
Ph.D., Assistant Professor, Kanazawa University, Department of Geosciences and Civil Engineering, JAPAN,
fujiu@se.kanazawa-u.ac.jp
4Dr., Eng., Professor, Kanazawa University, Department of Geoscience and Civil Engineering, JAPAN,
takayama@se.kanazawa-u.ac.jp
1

2

Keywords: evacuation timing, information announcement, personal attribute, area, personal distribution
1. INTRODUCTION
Unlike sudden disasters such as earthquakes, flood
damage caused by heavy rain can be predicted based on
various data. However, in recent disasters caused bytorrential rains frequently occurring in Japan, we havenot been able to respond appropriately, such as issuing anevacuation order on the verge of levee of theembankment. Since flood damage is different fromearthquake disaster etc. and the progress of disaster isrelatively control, human damage can be minimized if
early evacuation before the expantion of damage occur.
Therefore, we think that provision of evacuation
information at appropriate timing to local residents isimportant. In the heavy rain that occurred mainly in
Hiroshima and Okayama prefectures shown as Figure 1,
in July, 2018, (Heavy rain in July 2018), damage ranged
to 221 deaths and 390 injured people [1]. More than 70%of the dead were over 60 years old [2], it was
highlighting the fact that it was not possible to properly
deal with persons who needed consideration in the eventof a disaster. In the current information providing method,
personal attribute such as age and physical condition of aresident is not taken into consideration, and planar
information is provided. In order to reduce the damage of
persons who need consideration in times of disasters, a
new evacuation information providing method matching
the area and personal attributes is necessary.
Conventional research has many things that analyzechanges in people's sense of crisis and evacuation
awareness by changing the contents of information to beprovided. In this study, we focused on the fact that there
is a clear difference in the time required for evacuation
between healthy people and those who needconsideration, propose appropriate timings to provide
evacuation information appropriate to the age andphysical condition of the resident.

Figure 1: District that was heavily damaged by heavy
rain

Figure 2: Flow of a study
70% of the dead are over 60 years old, and many elderly
people are sacrificed due to heavy rain. Since it isindispensable to grasp detailed information of people
who need consideration during disasters such as elderly
people to reduce victims, we will examine those who areimportant in disasters using the census and the National
Health Insurance database.
In step 2, we grasp the target district. As a basic
examine of damage, understand the situation such as
time transition of rainfall of heavy rain in Hiroshima
prefecture and Okayama prefecture and time ofevacuation information provision. To examine detailed
rainfall conditions, use the data of Now cast shown as

2. FLOW OF A STUDY AND USE DATE
We aim to examine how much damage can be reducedby considering the personal attribute and area attribute of
the resident in the evacuation information and analyze
with the four steps shown as Figure 2.
In step 1, examine of persons who need considerationin the event of a disaster. In the heavy rain in 2018,165

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 76

3.

Figure 5: Disease distribution by medical big data

Figure 3: The data of Now cast

Figure 6: Depth of flood
3. UNIQUE DATA OF THIS STUDY
In this study, unique data use to analyze the distributionof disease which examine the vulnerable people during
large scale disasters. That data has disease name, age,
address, total amount of medical fee and so on. Figure 5
show that disease distribution has some characteristics.
Figure 6 shows that depth of flood in target area.
Maximum flood depth is about 5m, then two story
houses are inundated by the flood. In this situation, aged
person does not evacuate safety from their house due toinundate water by flood.

Figure 4: Multi-agent simulation
Figure 3. The data of Now cast accumulates what wasobserved and announced by the Meteorological Agency
such as current situation and future prediction once every
five minutes.
In Step 3, damage prediction of the target area is
performed. It is necessary as a comparison target when
examine the damage situation of the target district bypresent evacuation information provision and showing a
new information provision method. Assuming that thetorrential rain examined in Step 2 in the target area
occurred in the target area, perform multi-agent
simulation to predict damage, shown as Figure 4. By
using multi-agent simulation, it is possible to simulate
the settings such as walking speeds of healthy people andthose who need consideration in times of disasters.
Step 4 conducts evacuation information analysis. In
order to quantitatively evaluate the damage of new
evacuation information provision method, we conductmulti agent simulation. Considering the information on
persons who took care of during disasters examined in
Step 1, we provide information separated by area rather
than planar information and Compare with the current
damage prediction in step 3.

4. CONCLUSION AND FUTURE TASKSIn this research, we review current evacuation
information provision method and propose new
evacuation information providing method focusing on
the timing and areas, attributes.
Future tasks include National Health Insurance
Database, collection of census, and organization of Now
cast data. In addition, we conduct a questionnaire survey
to examine the present evacuation information provisionlaw, conduct interview surveys to local governments andweather stations.
REFERENCES[1] Fire and Disaster Management Agency, Japan
http://www.fdma.go.jp/bn/318b43ad8ead2c717087f45ff6
4a427e5cfc343d.pdf[2] Asahi Shimbun Digital (2018)https://www.asahi.com/articles/ASL7D7FSZL7DPTIL01
N.html166

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 75

EVALUATION OF REGIONAL HEALTH LEVELDURING SUPER-AGING SOCIETY
Shizuka SANO1, Junichi TAKAYAMA2, Makoto FUJIU3, Kiyoko YANAGIHARA4
Tatsuya NISHINO5, Masahiko SAGAE6 and Kohei HIRAKO7
1

Bachelor (Eng.), Kanazawa university, Dept. of Environmental Design, osizu219@stu.kanazawa-u.ac.jp
Dr., Eng., Professor, Kanazawa university, Geosciences and civil Engineering, takayama@staff.kanazawa-u.ac.jp
3
Ph.D., Assistant Professor, Kanazawa university, Geosciences and civil Engineering, fujiu@se.kanazawa-u.ac.jp(corresponding author)
4
Ph.D., Associate Professor, Kanazawa university, Pharmaceutical and Health Sciences, kyana@mhs.mp.kanazawau.ac.jp
5Ph.D., Associate Professor, Kanazawa university, Geosciences and civil Engineering, tan378@se.kanazawa-u.ac.jp
6Ph.D., Professor, Kanazawa university, Human and Social Sciences, sagae.masahiko@gmail.com
7
Bachelor(Economics.), Project Assistant Professor, Kanazawa university, Organization of Frontier Science andInnovation, hirako@staff.kanazawa-u.ac.jp
2

Keywords: KDB, requiring long-term care, Komatsu city, regional characteristics
1. BACKGROUND AND PURPOSE
The average life span of Japan continues to grow year
by year, the aging rate has reached 27.3%, and Japan has
already entered into a super-aging society [1]. As a result,the number of care-need certificated persons has
increased rapidly, and medical and nursing care problems
will become more serious. In response to this problem,
we will establish of a "Community-based integrated caresystems" that enables elderly people to continue living intheir home towns even if they come to need long-termcare [2].
In Japan, which is a super-aging society, it is an urgent
issue to build a community where elderly people cancontinue living at home, not nursing facilities, even if
nursing care is needed. Therefore, in this study, 25
regions are classified into 6 groups with similar
characteristics by cluster analysis using the National
Health Insurance Data which is medical big data, and thequestionnaire result. Then, clarify the living environment
in the area where level of care dependency increases andwhere level of care dependency is maintained.
There have been few studies on factors that cause
regional differences of changes in the level of caredependency. In addition, there is not much suggestion on
how to utilize data on care-need certificated persons
among the National Health Insurance Data. For thisreason, the novelty of this study is to grasp therelationship between change in the level of caredependency and living environment using the National
Health Insurance Data not fully utilized.

Figure 1: Level of care dependency

4.0 6.4

0%

9.4

10%

12.2

18.9

20%

30%

40%

20's

30's

40's

34.1

50%

50's

60's

60%

70's

70%

80%

80's

90's

13.8

1.3

90%

100%

Figure 2: Percentage of respondents by age
city. This data includes personal attributes of late-stageelderly who certificated care-need, level of caredependency, content of nursing care service used, cost ofcare, etc. Depending on the physical and psychologicalstate of the elderly, it is divided into seven level of caredependency. (Figure 1)
3. ANALYTICAL METHOD
For 25 elementary school districts in Komatsu city, weclassify into six groups by agglomerative hierarchicalclustering with the proportion of people who rose levelof care dependency and the 17 variables representing theliving environment.
For the proportion of people who rose level of caredependency, calculate for each elementary school district
using the National Health Insurance Data. In this study,
we refer to the proportion of people who rose level ofcare dependency as “State deterioration rate”. State
deterioration rate is the proportion of the people who

2. OVERVIEW OF ANALYSIS
Komatsu city, Ishikawa Prefecture, to be analyzed has apopulation of 108,582 people. There are 228 town, and it
is divided into 25 elementary school districts. The aging
rate of Komatsu city is 27.6%, which is higher than thenational average of 26.6% [3].
We use data on care-need certificated persons in the
National Health Insurance Data provided by Komatsu

167

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 75
worsened to the level 3 to 7 (in 2015) to the people who
certified the level 1 or level 2 (in 2012).
For the 17 variables representing the living environment,
use the questionnaire for Komatsu resident. The
questionnaire survey period was August 2017, and it waspossible to collect 1523 samples. Figure 2 shows that
more than half of respondents are elderly people;
therefore, from the questionnaire result, we can grasp theliving situation of elderly in Komatsu city. From thequestionnaire, the response rate to the four kinds ofquestion items are set as variables. The question items
are divided into “Enhancement of living environment”,“Usual outing situation”, “Regional connection”, “Healthawareness”.

connections are intimate and high health awareness.
Cluster 6 with second largest State deterioration rate isarea where it is very inconvenient for usual outing andfew people get medical exams every year. Cluster 4 withthe smallest State deterioration rate is area where usual
outings are very convenient and go out frequently. The
characteristics of cluster 5 with second smallest State
deterioration rate are satisfactory living environment andpoor regional connections.
5. CONCLUSIONSWe divided 25 elementary school districts of Komatsu
city into 6 clusters according to regional characteristics.
As a result, it was revealed that common characteristics
in areas where level of care dependency increases andwhere level of care dependency is maintained areconvenience to usual outing. Level of care dependency iseasier to rise in areas where usual outings areinconvenient, and conversely useful outing areas are lesslikely to rise in level of care dependency. Furthermore, inareas where level of care dependency increases, regional
connections are intimate. In areas where level of caredependency is maintained, regional connections are poor.
In the future, we will clarify how each variable
representing the living environment affects the
proportion of people who rose level of care dependency
and care-need certification rate.

4. RESULT OF ANALYSIS
Table 1 shows the average, unbiased variance, standard
deviation of each of the 18 variables used for cluster
analysis. It can be seen that the variable of “No smoking
experience”, “Provision of commercial facilities”, “To goout 5 days a week or more” with large standard deviation
greatly affects the classification result.
Table 2 shows the average value of 18 variables foreach of the six clusters. The characteristics of cluster 3
with the largest State deterioration rate are unsatisfactoryliving environment, inconvenience go out, regional
Table 1: The average, unbiased variance, standard
deviation of each of the 18 variables used for cluster
analysis
Variable

Average

Unbiasedvariance

REFERENCES[1] Cabinet Office, Government of Japan. (2018). Annual
Report on the Aging Society, Retrieved Aug. 17, 2018,from http://www8.cao.go.jp/kourei/whitepaper/w2017/zenbun/29pdf_index.html[2] Ministry of Health, Labor and Welfare. (2012).
References on Promotion of Healthy Japan 21 (second
order), Retrieved Aug. 17, 2018, fromhttp://www.mhlw.go.jp/bunya/kenkou/dl/kenkounippon2
1_02.pdf[3] Japan Medical Association. (n.d.). Japan Medical
Analysis Platform, Retrieved Aug. 17, 2018, fromhttp://jmap.jp/cities/detail/city/17203

Standard
deviation

State deterioration rate

42.65

97.07

9.85

Provision of commercial facilities

26.45

164.4912.83

Provision of medical welfare facilities

26.97

91.15

9.55

Provision of public facilities

17.02

53.33

7.30

Provision of public transport

14.22

55.71

7.46

Enhancement of employment location

10.78

43.19

6.57

Sufficient greening maintenance

24.28

61.83

7.86

Safe sidewalk maintenance

32.86

119.9910.95

To go out 5 days a week or more

64.10

158.78

12.60

Inconvenience is shopping

20.16

116.19

10.78

Inconvenience is attending a hospital

20.48

108.92

10.44

Intimate neighborhood relationship

11.05

64.38

8.02

Active participation in the neighborhood association

20.96

138.73

11.78

To exercise five days a week or more

18.66

52.92

7.27

Keep in mind a well-balanced meal

40.33

128.26

11.33

Keep in mind a regular life

48.13

125.72

11.21

No smoking experience

63.69

226.7915.06

To get medical exams every year

84.35

50.07

7.08

Table 2: The average value of 18 variables for each of the six clusters
ActiveTo
Keep in
Provision
Enhancement
To go outState
Provision ofProvision Provision
Sufficient
Safe
Inconvenience
Intimate
participation exercise
mind aof medicalof
5 days a Inconvenience
No deterioration commercialof public of publicgreening
sidewalk
is attending a neighborhoodin thefive days awellwelfare
employment
week oris shoppingrate
facilities
facilities transport
maintenance maintenancehospitalrelationship neighborhood week or balanced
facilities
location
more
association
more
meal

Keep inNo
mind asmoking
regularexperiencelife

To getmedical
exams
every
year

1

43.73

41.21

40.52

29.00

22.61

17.18

33.99

42.36

67.55

14.01

15.24

7.70

16.63

17.22

38.44

46.53

51.10

81.17

2

45.32

22.55

23.31

14.56

12.89

8.62

17.98

27.79

68.78

17.81

21.15

7.66

20.11

14.82

42.03

49.32

63.30

87.39

3

46.96

11.13

18.64

9.85

6.21

4.64

29.27

48.02

48.30

26.36

25.93

25.80

40.95

29.26

52.12

56.74

89.72

83.71

4

32.18

31.49

29.93

16.50

14.39

12.69

25.32

24.55

76.32

13.10

11.53

8.52

15.91

17.53

38.47

50.82

53.05

81.60

5

43.08

45.14

35.42

17.36

25.00

21.53

27.78

21.53

55.93

21.00

21.38

2.08

8.33

11.00

20.00

22.00

55.00

92.86

6

46.88

11.86

15.26

18.18

7.54

3.33

13.95

35.98

47.72

46.20

38.81

17.07

18.29

26.21

38.75

48.81

73.61

78.24

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 79

LANDSLIDE DISASTER RISK FOR THE FUTURE POPULATION DECREASE IN JAPANTAKANORI KATO1 , MUNEYOSHI NUMADA2 and KIMIRO MEGURO3
1

Master student, Department of Civil Engineering, UTokyo, Japan, taka-kat@iis.u-tokyo.ac.jp (corresponding author)
Associate Professor, IIS, UTokyo, Japan, numa@iis.u-tokyo.ac.jp
3
Professor, IIS, UTokyo, Japan, meguro@iis.u-tokyo.ac.jp
2

Keywords: landslide disaster, relocation, population decrease, ArcGIS
1. INTRODUCTION
Every year in Japan, multiple natural disasters cause
fatalities. To reduce the victims by the disasters, it isnecessary to investigate the causes of deaths in eachdisaster [1]. By investigation of the kind of behavior indetails, previous researches have analyzed how victims
are lead to the death just before the disasters. The
previous study of the authors identified the factors to
reduce the deaths in each disaster [2]. Table 1 shows thatlandslide disasters and typhoons caused the mostsignificant number of deaths by natural disasters in Japanin addition to the major earthquakes such as the 2011
Great East Japan Earthquake disaster. Especially, themajor cause of death is that they did not evacuate andwere staying at home even after an early warning (175out of 437 people) as well as failed to evacuate (88 out of
437 people).

if landslide disasters occurr in the future and calculated t
he amount of financial support, which is desirable and fe
asible.
2. METHODOLOGYThe number of households living in the landslide
waning area in the futute and the amount of money ofsubsidies per household are calculated by the following
procedure. First, the mesh data of the landslide disasterwarning area provided by Kanagawa Prefecture wasoverlaid with the 500m × 500m mesh data of the
population presumption until 2050, and the change of the
population within the area is analyzed.
Next, the cost-effectiveness of each municipality byrelocating households in the landslide disaster warning
area is analyzed. At this time, we considered a scenario
in 2050 that distributes subsidies to households who arestill living within the landslide disaster warning area toevaluate the resident households to zero. In this case, it
can be thought that the reduction of landslide disaster
restoration cost and reduction of infrastructure
maintenance and management cost are benefits ofrelocation. According to previous research [3], theinfrastructures that can reduce the maintenance cost canbe a municipal road, water supply system, sewage
system, merger treatment septic tank. Based on thisassumption, it is difficult to rerelease real estates to themarket, so it is necessary for the administrative side topurchase it. Considering these differences as subsidies tohouseholds, we calculated subsidies per household.

Table 1: Classification of causes by behavior before

the death of disaster victims in Japan (2009-2017)
The pre-deathbehavior ofdisaster victims
Activelyapproaching
danger
Evacuation
failureAccident
Disaster-Related
Death
Secondarydisaster

Earth
quake

TyphoonFloodpeople

Snow
storm

0

17

0

50

437

122

0

17

244

194

7

0

5

8

1

3. RESULT
Kanagawa prefecture is set as the research target(Figure 1), because the number of landslide disasters in
Kanagawa Prefecture happened in the past 10 years islargest in Japan.
Figure 2 and 3 show the mesh of the landslide disasterwarning area and the mesh of predicted population. The
sum of the landslide disaster warning area is larger in thesouthern area, but the population is concentrated in thenorthern area. As a result, it is shown that the resident
population in the landslide disaster warning area ofKanagawa prefecture accounts for the majority in themunicipality in the northern area including YokohamaCity.
Figure 4 shows the amount of subsidies for eachmunicipality. 2 municipalities among 32 municipalities
in Kanagawa prefecture can pay 10 million yen for one
household. 10 municipalities (5.3% of the total
population of Kanagawa Prefecture) can subsidize.

Many people have no choice but to live in a vulnerable
area while giving warning areas that are expected tosuffer a landslide disaster in the future. The purpose ofthis research is to evaluate the number of people living inlandslide disaster potential areas and high potential risk
areas. The result showed the number of people in thelandslide potential area would change due to thedecreasing population, on the other hand, there are someareas where the risk of landslides will not change orincrease even in the situation of decreasing population in
Japan.
In addition, since the current municipal financial resou
rces cannot provide people living in the landslide potenti
al area with enough amount of relocation assistance, thisresearch estimates how much economic loss would incur169

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12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 79

Tokyo
Ayase-City
0 – 656 people
657 – 1,668 people
1,668 – 2,798 people
2,799 – 4,326 people
4,327 – 9,320 people

Oiso-Town
Kanagawa

Figure 1: Location of Kanagawa prefecture

Figure 3: Mesh data (500m × 500m) of the population
presumption in 2050
Ayase-City
Oiso-Town
Hiratsuka-City
Aikawa-Town
Isehara-City
Kiyokawa-Village
Nakai-Town
Odawara-City
Sagamihara-City
Manaduru-Town
Miura-City(million Yen)
0.0

Figure 2: Mesh data of the landslide disaster warningarea
The common point of two municipalities is that few
households locate in the landslide disaster warning area,
the cost of restoring damages at landslide disasters in thepast is larger than other municipalities.
Other municipalities will become a deficit just bypurchasing the land from the relocated households.
Moreover, households that gain less than one million yenof the subsidies at the time of changing the residence will
not relocate due to the lack of relocation. This researchfound that an enough relocation support cannot beprovided merely by waiting for the anticipatedpopulation decrease.

5.0

10.0 15.0 20.0 25.0 30.0

Figure 4: Subsidies per household in municipalities

Third, to reduce the risk of damage due to landslidedisasters, it is necessary to induce people living in thelandslide disaster warning area to move outside of thearea before subsidizing financial support. It is importantto minimize the financial burden of each municipality. It
is very difficult for all the residents to provide financial
relief assistance, reducing the residence within thewarning area by methods other than relocation must be
considered. For example, it is an unnatural system tosecure these resources from residents living in areas withlow disaster risk, so raising property tax of residents
living in regions with high disaster risk need to beconsidered. In the future, it is intended to hypothesize
these options and evaluate each option. In addition, it isnecessary to consider all potential disasters withlandslide disaster risk.

4. CONCLUSIONFirst, the population in landslide disaster warning
areas decreases due to the population decrease in Japan.
However, the proportion of the total population in eachmunicipality does not change drastically. Therefore, even
if the policies such as relocation are delayed, thefinancial burden does not change so much. Municipal
governments will need long-term policies by introducing
guidelines for the residents to relocate to the outside of
the warning area at the timing of changing residences.
Second, the cost-effectiveness analysis by therelocation turned out that there are considerably few
local governments that can generate subsidies. Assuming
that, if all the population relocate, even if supposing to
induce such as a compact city and abandon maintenanceof infrastructure, the number of municipalities that can
subsidize will be about one third, 5.3% of the entire
population of Kanagawa prefecture.

REFERENCES[1] M. Ushiyama, Y. Takayanagi, (2010) “Characteristi
cs of death or missing caused by heavy rainfall disaster events from 2004 to 2009” J.JSNDS, No.29,
Vol.3, pp. 355-363.
[2] T. Kato, M. Numada, K. Meguro, (2018) “BEHAVIOR ANALYSIS BEFORE THE DEATH OF
THE VICTIM AT DISASTERS”, JSCE Annual meeti
ng, Ⅳ-159.
[3] R. Kaijimoto, N. Kachi, K. Tsukahara, Y. Akiyama (2015) “FINANCIAL FEASIBILITY STUDY ON RELOCATION AT VILLAGE LEVEL FROM DISASTE
R DANGEROUS AREA”, JSCE, Vol.71, No.5, pp.
367-373.

170

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 36

UNDERSTANDING FATALITIES IN URBAN ROAD ACCIDENTS: A CASE STUDY
K. KALKAL1, S. MISRA2, and V. VASUDEVAN3
1

Graduate Student, Department of Civil Engineering, IIT Kanpur, Kanpur, India, krutika@iitk.ac.in (corresponding)Professor, Department of Civil Engineering, IIT Kanpur, Kanpur, India, sud@iitk.ac.in
3
Associate Professor, Department of Civil Engineering, IIT Kanpur, Kanpur, India, vinodv@iitk.ac.in
2

Keywords: safety, fatalities, road accidents, safety performance, public transport, India
1. INTRODUCTION
Injuries and fatalities in road accidents are the 9thmajor killer in India, with around 1.4 lakh deaths in 2017.
Improving the efficiency and safety record of public
transportation systems is critical to increase their modal
share and can contribute significantly to decongestingroads, especially in urban areas.
The effort in this paper is directed towards presenting
the results of the analysis of data involving fatalities forthe last four years from the public transport company of
one of the metro cities of India. The aim of this work is
to identify factors and physical conditions that contributethe most towards fatal accidents.

3.3 Distribution of Fatal Accidents during the day
Data for all fatal accidents for the four-year period of
2014-18 was viewed in terms of hour-wise frequency of
accidents. The results are plotted in Figure 2. Two peaks
are observed – one from 11 am to 2 pm and another from
7 pm to 10 pm. There is a linear trend of increase in thenumber of fatal accidents as the traffic thins (and thecorresponding vehicular speeds increase) both in themorning hours (7 am to 2 pm) and in the evening hours(4 pm to 11 pm).

2. ANALYSIS AND RESULTS
Accidents are classified using accidents/bus, numberof accidents occurring during monsoon season, and the
distribution of accidents during the day. The results are
discussed in the following paragraphs.
3.1 Fatal Accidents per Bus
A total of 24, 29, 21, and 21 fatal accidents occurred in
2014-15, 15-16, 16-17, and 17-18 respectively. When
divided by the number of buses in operation in the
different years, the ratio obtained is almost a constant, asvisible in Figure 1.

Figure 2: Distribution of Number of Total Accidents
from 2014-15 to 2017-18

100 Buses

4. CONCLUDING REMARKSThe results from the preliminary analysis in terms offatal accidents per bus and the effect of rains on fatal
accidents are inconclusive. However, there is apparently
a clear relation between the traffic density, speed andfatal accidents. This calls for further studies, including
the collection of relevant data, to understand the effectsof parameters such as driver training, road and bus
condition.
REFERENCES[1] Ministry of Road Transport and Highways, Physical
Performance of SRTUs, National Data Sharing andAccessibility Policy (NDSAP), Open Government Data
(OGD) Platform India[2] W.A. Evans and A.J. Courtney, (1985) “An Analysis
of Accident Data for Franchised Public Buses in HongKong”, Accident Analysis and Prevention, Vol. 17, pp
335–336[3] Somit Sen, (2018, May 2) 900 BEST Buses taken off
roads in five years, The Times of India, Retrieved fromhttps://timesofindia.indiatimes.com/[4] Sanchita Sharma, (2017, September 30) The top 10
causes of death in India, Hindustan Times, Retrieved
from https://hindustantimes.com/

Figure 1: Number of Fatal Accidents per 100 Buses
3.2 Fatal Accidents during the Monsoon Season
To get an insight into the effect of rains on the numberof fatalities, the data for the period of June-September,the known ‘rainy season’, was looked at separately.
It was found that the number of accidents in this 3month period as a percentage of the total accidents ineach year was 29%, 17%, 38% and 19%, which is not
significantly different from 25% (i.e. for 3 out of 12months, or 25% of a year).

171

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 56

Is a change in land surface temperature treated as an early warning sign to predict earthquakes?
N. KAVYALAKSHMI 1, KAUSHAL KRISHNA TOTLA1, M. VANI2, and P. RAMA CHANDRA PRASAD2
1

Department of Civil Engineering, Mahindra Ecole Centrale, Hyderabad-500043, India,
nkavyalakshmi98@gmail.com, kaushal15238@mechyd.ac.in
2,

Lab for Spatial Informatics, International Institute of Information Technology, Hyderabad-500032, India,
m.vani@research.iiit.ac.in, rcprasad@iiit.ac.in (corresponding author)
Keywords: surface temperature, earthquake, satellite imagery
1. INTRODUCTION
Recent advancements in space science reveals various
processes
associatedwithearthquakes
liketransformation of the earth surface, increasing surface
temperature, variations in the atmospheric gases, aerosol
expiration, and electromagnetic disturbances in theatmospheric column especially in the ionosphere.
Analysis of these earths’s processes carry priorinformation related to earthquake that serves as anindicator towards predicting the event of an earthquake.
Land surface temperature (LST) is one such potential
indicator linked with earthquakes. Information on the
LST is derived from the thermal infra-red (TIR) band of
the electromagnetic spectrum employed in sensors onboard satellites.
Scientific research has led to an observation of rise in
the LST before the occurrence of an earthquake. A rise of
3-10oC has been observed before the event (Swapnamita
Choudhury 2006, Adnan Barkat et al. 2018). Thisanomaly can be employed in forecasting earthquake. The
rise in temperature can be explained by the tectonic
stress built up around the epicenter of the earthquake.

magnitude; Strong earthquake: 6.0 – 6.9; Moderate
earthquake: 5.0 – 5.9; Minor earthquake: 3.0 – 3.9 withpotential to cause minor damage) based on themagnitude. All the mentioned locations (except Koyna
Warna, Maharashtra) lie close to the Alpide belt, which isvery prone to earthquakes.
Analysis involve retrieval of the surface temperaturefrom the thermal band of the Landsat series 5, 7 and 8 ofsatellite imageries using Mono-window algorithm
developed after Qin et al. (2001). The bands
corresponding to the NIR, red and TIR data wereprimarily used to retrieve LST of the locations. The LST
is derived based on the parameters viz., groundemissivity, atmospheric transmittance and effective mean
atmospheric temperature. The variations in the LST wereanalyzed by creating buffers at distances of 3 km, 6 km,
9 km, 12 km and 15 km from the epicenter. The analysis
was done in two phase viz., variations in the intensity of
LST: with the increasing distance from the epicenter andwith time. The observed variations in the LST patternwere further linked to the Land Use/Land Cover (LULC)
prevailing at the immediate vicinity of the epicenter.

2. STUDY AREA AND METHODOLOGYThis study attempts to analyze the thermal anomaly ofeight events (Table 1) in and around India. The idea wasto analyze the LST variations from 15 days prior andpost the event of an earthquake; and existence ofcorrelating patterns of earthquake magnitude and theircorresponding variations in LST across locations.

3. RESULTS AND DISCUSSION
Three distinct patterns of surface temperature
anomalies were observed as: (1) increasing surface
temperature towards the event of an earthquake andreduction post the event; (2) higher temperature both preand post an earthquake and lesser temperature at theevent of earthquake; and (3) steadily increasing
temperature prior to the earthquake that continues evenpost the earthquake event. A model plot of variations in
the LST with increasing distance from the epicenter andtime is shown in figures 1 and 2 respectively.

Table 1: Study areas associated with earthquake event
Location
Magnitude
Date
Kashmir
7.6
08-10-2005
Hindu Kush, Afghanistan
7.5
26-10-2015
Imphal, Manipur
6.7
04-01-2016
Tripura5.7
03-01-2017
Gujarat5.5
06-04-2006
Jaisalmer
5.2
09-04-2009
Koyna Warna,
5.1
14-03-2005
Maharashtra
Punjab3.1
05-11-2015
The locations were chosen based on the availability ofdata and different earthquake classes (Major earthquakewith potential to cause serious damage: 7.0 - 7.9

Figure 1: Distance of buffer vs LST

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 56
5. REFERENCES[1] Adnan Barkat, Aamir Ali, Khaista Rehman,
Muhammad Awais, Muhammad Shahid Riaz, and Talat
Iqbal (2018) “Thermal IR satellite data application forearthquake research in Pakistan”, J of Geody., 116, 13-22[2] Swapnamita Choudhury, Sudipta Dasgupta, Arun K.
Saraf and Santosh Panda (2006) “Remote sensing
observations of pre-earthquake thermal anomalies inIran”, Int. J of Rem. Sens., TRES-PAP-2005-0503.R2

Figure 2: Date vs LSTWhile Hindu Kush and Koyna Warna witnessed anincrease in the LST as we approach the event ofearthquake and subsidence post the event; Gujarat,
Kashmir and Punjab reported a gradual reduction in the
LST towards the date of earthquake and an increase post
the event. The LST in Imphal and Tripura have been
observed to increase throughout the period of the study,i.e. before and after the earthquake event. Jaisalmer
showcased a different pattern: a steady LST towards theevent of earthquake and reduction later on. The
complicated patterns observed at these locations
intrigued to find out the possible reason behind theanomalies. Therefore LU/LC of the site at the epicenter
was further investigated to find out if they could be thepossible reason behind these varying patterns (Table 2).

[3] Qin Z., A. Karnieli, and P. Berliner (2001) “A monowindow algorithm for retrieving land surface
temperature from Landsat TM data and its application to
the Israel-Egypt border region”, Int. J of Rem. Sens.,
22:18, 3719-3746

Table 2: Observed LU/LC classes at the epicenters
Locations
LU/LC
ImphalForestGujarat
Open area
Kashmir
Open village area
TripuraRiver Bank
Koyna Warna
Mountainous
Jaisalmer
Barren land
Hindu Kush
Mountainous
PunjabLess density vegetation
The investigation on LU/LC identifies that the LST
variations in the mountainous regions of Hindukush andKoyna Warna were similar following pattern (1); while
low density settlements and vegetation as observed in
Gujarat, Kashmir and Punjab reports a similar pattern (2)of LST variations. The potential cool areas forest andriver bank observed at Imphal and Tripura respectively
followed pattern (3) of the LST variations. It wasinferred that a uniform pattern of surface temperature
variations prevailed over similar LU/LC classes.
4. CONCLUSIONSThe changes in LST patterns vary according to the land
use type and topography. This study is restricted only tothe analysis of surface temperature and the land surface
features and their efficiency in predicting an earthquake
event. Further investigation needs to be done
incorporating the soil parameters and sub-surface
features of the earth that will enhance the results of thisstudy to be more reliable to predict an earthquake event.

173

USMCA 2018

SESSION 10
DISASTER RISK & RESPONSE II

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 29

DEVELOPMENT OF CAVE-IN POTENTIAL MAP OF FUJISAWA CITY
R.SERA 1, R. KUWANO 2, R. HIRATA 3, M. HARIGAYA4, Y. YAMAMOTO5 and S. YONEMOTO6
1

Manager, Operational Headquarter, GEOSEARCH Co.,LTD., Tokyo, JAPAN, r-sera@geosearch.co.jp (corresponding
author)2
Professor, Institute of Industrial Science, The University of Tokyo, Tokyo, JAPAN, kuwano@ iis.u-tokyo.ac.jp
3Manager, Road and River Department, Fujisawa City, Fijisawa, JAPAN, fj0-kasensuuiro@city.fujisawa.lg.jp
4Manager, Sewage Department, Fujisawa City, Fijisawa, JAPAN, fj2-gesui-ka@city.fujisawa.lg.jp
5Senior chief, Road and River Department, Fujisawa City, Fijisawa, JAPAN, fj1-dorokasen-s@city.fujisawa.lg.jp
6
Chief, Tokyo Regional Office, GEOSEARCH Co.,LTD., Tokyo, JAPAN, s-yonemoto@geosearch.co.jp
Keywords: subsurface cavity, road cave-in, regional characteristics, factor analysis, evaluation of potential
1. BACKGROUND
Preventing road cave-in is key to keeping road traffic
functions. A collaboration among Fujisawa city and IIS
Univ. of Tokyo and GEO SEARCH started to develop
effective solutions for prevention of road cave-in
accidents in Fujisawa city in 2017. Fujisawa city is
located in the central part of Kanagawa Prefectureadjoining western Tokyo. The south area faces the
Pacific Ocean and the alluvial lowlands of the Shonan
dunes lies. The intensive developments of infrastructuresuch as roads and sewers were during 1950’s to 1970’s.
In recent years, deteriorate of infrastructures by the aging
was obviously, and the handlings for them become aserious issue [1].
The development of “Cave-in Potential Map ofFujisawa City” is one approach to this collaborative
study and this is the first attempt to evaluate the regional
area based on cavity information. The purpose ofdevelopment of the map is to understand the regional
condition. For keeping road function against cave-ins, itis necessary to consider the road network around thecavities. The regional assessment of the potential of thecave-in and the map showing it give some benefits. It
takes appropriate measures not only for regular situation
but also for emergency situation such as large-scale
natural disasters. In addition, these approaches will
support discussion at other local governments thatstarting new measures for cave-in as experienced cases.

In addition, another main factors are consolidation
settlement of soil particles in the subgrade, loosen soil
around underground structure, and fluctuation ofgroundwater level. In many cases, some contributing
factors influence each other forming cavities.
3. FINDINGS OF REGIONAL FACTORS OF
CAVE-IN IN FUJISAWA CITY
The data of more than 430 cave-ins which covering
Fujisawa city, the data of more than 230 cavities bypassed investigation and the data of trial monitoring
surveys on 10 roads in this study were analyzed forcave-in potential evaluation. And valuable data managed
by Fujisawa city that sewage, groundwater, geologicalborings and so on were also used regional overlying andanalyzing. In this collaborative study, detail condition
around the cavities were surveyed to find out theirfactors [2] (Fig.1). In addition, the model tests were also
conducted to clarify the process of expansion of cavity.
The sand of the test was simulated as actual condition
around a cavity where surveyed in detail [3] (Fig.2).
Based on previous knowledges and regional findings
from the study, four environmental factors: the oldness ofsewage, the number of utilities, the level of groundwater,
and the permeability of soils were selected as theregional potential factors.

2. CAUSES OF CAVITIESRoad cave-in occurs suddenly with collapse andbroken pavement. However the beginning is a small
ground phenomenon. One of the factors forming cavities
can be considered as washout of soil particles through a
broken or joint failure of sewer pipe. Fig. 1 shows photos
as actual examples of factor of cavities in Fujisawa city.

Figure 2: Model test of cavity occurrence in actual sandcondition of Fujisawa city

Figure 1: Photos of under cavities; left/ground water andjoint failure of sewer, right/ broken sewer joint by aging

4. A STUDY FOR POTENTIAL EVALUATION
Through the discussions about the effects and theevolutional techniques, the cave-in potential of Fujisawa
city were set by using four factors belonging to eachdivided grids. Fig. 3 shows the four maps of regional
factors of cave-in in Fujisawa City, and an occurrence
frequency of cave-in and cavity by sewer pipeclassification into type and aged years as example.
174

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 29

Sewer pipe / type and age
Legend [4]Occurrence frequency of cave-in and cavity by sewer pipeclassification into drainage method and oldness

Figure 4: Prototype of cave-in potential map of Fujisawa
City[4]

Number of sewer attachingpipe

LegendThen the regional occurrence tendency of cave-ins wasanalyzed by overlaying the each four factor maps withthe cave-in and cavity location map. Fig 3 shows

Ground water level( reference value)

6. CONCLUSION
This is the first attempts to evaluate the area by thecavity information. And it was able to get the realistic
result with the output named cave-in Potential Map. This
was achieved by various data and regional findings form
passed cavity survey data, actual cave-in information,
precious managed sewer information, and several
challenges in this collaborative study such as monitoring
surveys and detailed investigations of cavity. Preventing
road cave-in is key to keeping road traffic functions. And
it is also a disaster-resistant system. These collaborative
studies are most leading, advancing, and practical casesin the world. In the future, we would like to make effort
to develop evaluation even more effective.

LegendREFERENCES[1] R. Hatakeyama., E. Nakamura., M. Harigaya., R.
Kuwano., and H. Miki., (2018). Development of Effective
Technique for Prevention of Road Cave-in in FUJISAWA
city, 53rd Japan National Conference on GeotechnicalEngineering, Takamatsu, pp. 1617-1618.
[2] M. Okamura., M. Abe, K. Fujii., K. Kitamura., and R.
Kuwano., (2018). Development of Effective Techniquefor Prevention of Road Cave-in in FUJISAWA city, 53rd
Japan National Conference on Geotechnical Engineering,Takamatsu, pp. 1619-1620.
[3] Y. Ohara., R. Kuwano., R. Sera., R. Hatakeyama., and
H. Kageyama., (2018). Development of Effective
Technique for Prevention of Road Cave-in in FUJISAWA
city, 53rd Japan National Conference on GeotechnicalEngineering, Takamatsu, pp. 1621-1622.
[4] R. Sera., R. Kuwano., and M. Hotta., (2019).
Development of subsurface cavity potential map for
prevention of road cave-in (in press), The 16th AsianRegional Conference on Soil Mechanics andGeotechnical Engineering (16ARC), Taipei.
[5] http://nrb-www.mlit.go.jp/kokjo/inspect/landclassi
fication/download/index.html

Surface geology
1/50,000 Land Classification Basic Survey Fujisawa by MILT, National Land Information Division[5]LegendFigure 3: Four factor maps of cave-in in Fujisawa City
5. PROTOTYPE CAVE-IN POTENTIAL MAP OF
FUJISAWA CITY
After making sure for appropriateness by sensitivity
analysis of four potential factors in each, a knowledge
that cavities often occur under overlapped multiple
factors was reflected on this evaluation as a new attempt.
Fig. 4 shows the prototype of cave-in potential map ofFujisawa city that evaluated based on the degree ofoverlap of multiple factors.
175

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 39

DEVELOPMENT OF SITE AND SCENARIO SPECIFIC DESIGN GROUND ACCELEROGRAMSUSING RECORDED GROUND MOTIONS
C.K. GADAGAMMA1 , S.R. MENON2 , Y. ARAI3 , S. SATO3 , T. KATAGIRI4 and M. NUMADA5
1 Project Assistant Professor, Institute of Industrial Science, Tokyo, Japan,
2 Engineer, Kozo Keikaku Engineering, Tokyo, Japan,
3 Tokyo Metro Corporation, Tokyo, Japan,
4 Technical Director, Institute of Industrial Science, Tokyo, Japan
5 Lecturer, Institute of Industrial Science, Tokyo, Japan
Correspond to C.K. GADAGAMMA(chaitugk@iis.u-tokyo.ac.jp)
Keywords: Strong Motion, GMPEs, Attenuation, Strong Motion Prediction
ground parameters, PGA, PGV and PGD are further
extracted.In order to incorporate the local site effects, thedesign accelerogram is convoluted using equivalent linear
analysis of ground tool, DYNEQ [3]. These peak groundparameters are then used to un-normalize the response
spectrum to obtain a single target response spectrum.
Applying Ohsaki method, the response spectrum istranslated into an earthquake ground motion.

2.2

In this method, a set of well tested GMPEs for Japanare considered and are validated using the ground motion
database at different locations. Further, analysing thevariations during the validation, applied corrections to
obtain site-specific GMPEs. Utilizing recommended
scenarios prescribed by J-SHIS [4], the deterministic
demand in the form of peak ground parameters are
estimated at the bed rock. An averaged normalized
response spectrum is generated using the recorded groundmotions at the bedrock. This is then un-normalizedusing the estimated demand parameters, to get the target
spectrum. Using the local site conditions, a convoluted
accelerogram is obtained at the tunnel site.

Figure 1: Background and development of the database

1

INTRODUCTION

In this research different methods have been establishedto generate a spectrum consistent earthquake design
input motion, incorporating local site conditions using a
database of strong ground motions, recorded by sensors
buried at different depths at various locations in Tokyo
since 40 years by Tokyo Metro Co., Ltd. as shown in 1,
along with the source to site information and local site
borehole data [1]. The distortions and shift in the axis
and short and long period noises in the recorded groundmotion records are initially processed with band-passfiltering of cut off frequencies of 0.02Hz and 20Hz,
and baseline correction is done as shown in Figure 2.
The source characteristics of each of the earthquake are
obtained from the JMA repository. The borehole data
for each of the station is further converted to engineering
quantities using empirical relationships.

2

2.3

Method 3

In this method, the average normalized response spectrumat the surface is obtained from the recorded groundmotions. The target response spectrum is obtained byusing the probabilistic hazard prescribed at J-SHIS. This
response spectrum is then deconvoluted to the tunnel
location by using the local site conditions and DYNEQ.

METHODOLOGY

3

The different strategies to obtain the target response
spectrum are explained below as:

2.1

Method 2

RESULTS AND DISCUSSION

All three methods have been evaluated using the recorded
data at Shinkiba station in Tokyo. The complete datasetof Shinkiba station measured at three different depths
have been processed as mentioned earlier, an average
normalized response spectrum, for method 1 is obtained
as shown in Figure 4. The target response spectrum
using RTRI design accelerogram peak ground parameters
is shown in Figure 5 Further, a design accelerogram is

Method 1

Using the average normalised response spectrum atthe surface depth [2]. The design response spectrum
as prescribed by RTRI as L1 and L2 at engineering
bedrock is taken for consideration. The values of peak176

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 39
Shear wave velocity (m/s)

Gmax (MPa)

Baseline Correction

0

100

200

0

300

0

20

20

30

40

Shear Wave Modulus andVelocity30

Depth (m)Borehole Data

Depth (m)Processed GM
Data

40

50

50

60

60

Empirical70Equations

70

80

80

Bandpass Filtering

400

10

10

+

200

0

Figure 2: Data processing of ground motion records and conversion of borehole data to engineering parameters

Ground Motion Data

Source-Site Data

Surface Normalized
Response Spectrum

Site Speciﬁc GMPEs

Soil Borehole Data

Engineering Parameters

Non-Linear Site
Response Analysis(DYNEQ)

Bedrock Normalized
Response Spectrum
Method 1

L1/L2 Earthquake atthe bed rock

Method 2

Deterministic Hazard
Scenarios

Method 3

Probabilistic Hazard
Scenarios

Figure 5: The target response spectrum in Method 1
Bedrock Target
Design Spectrum

SurfaceTarget Design
Spectrum

Simulated Earthquake Wave L2
1000

Design Accelerogramat Substructure

Ohsaki Method

Acceleration (gals)

Ohsaki Method

500

Figure 3:
Flowchart of different methods in design
accelerogram

0

-500

-1000
-1500
0

2

4

6

8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
Time (sec)

Simulated Earthquake Wave L1

Acceleration (gals)

200
100
0

-100
-200
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
Time (sec)Figure 6: The simulated accelerograms in Method 1
Figure 4: The normalized response spectrum in Method 1

REFERENCES[1] C. K. GADAGAMMA, S. M. RAJASEKHARAN,
Y. ARAI, S. SATO, T. KATAGIRI, M. NUMADA,
Observations of strong ground motion in tokyo metro
stations at different depths, Seisan kenkyu 70 (4) (2018)299–308. doi:10.11188/seisankenkyu.70.299.
[2] P. K. Malhotra, Normalized Response Spectrum of Ground
Motion, in: Annual Meeting of the Seismological Societyof America, 2015.
[3] N. Yoshida, I. Suetomi, DYNEQ: a computer program for
dynamic analysis of level ground based on equivalent linear
method, Reports of Engineering Research Institute, Sato
Kogyo Co., Ltd (1996) 61–70.
[4] J-SHIS (Japan Seismic Hazard Information Station).
URL http://www.j-shis.bosai.go.jp/en/

developed using Ohsaki method as shown in Figure 6.
Further analysis is conducted on the accelerograms toevaluate the energy content and the frequency content.

4

CONCLUSIONS

A big data of ground motion, soil data and earthquake
source information is compiled at different locations anddepths to obtain design accelerograms. Multifaceted
methods established and tested in the necessity ofincorporating local site effects and accumulated data. The
validation, sensitivities and aspects of applicability ofthese methods are a subject of future scope.
177

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 54

COMMUTER AND ROAD SAFETY ON HYDERABAD CITY ROADS: TECHNOLOGY TRENDSSVS KASTURI
Asst. Manager, IIIT Hyderabad, India. e-mail: vijay@iiit.ac.in (Corresponding author)
ABSTRACT(CCC) to monitor real-time traffic incident management

Human migration to urban cities is increasing day by day,rd

and, other civic issues on the roads. The CCC is a nodal

world-wide. A prediction was that 2/3 of world populace

office connected with electronic and network enabled

will settle down only in the cities by the year 2050

devices such as Personal Digital Assistants, Tabs, Smartbecause of the better facilities that are available in

Phones and cameras. It enabled with on-line traffic

education, health and employment etc. Contemplating themanagement system to identify the chain-snatchers,

fact, the Government of India was focusing to set up

traffic violators, signal jumping, vehicle parked at adecent urban infrastructure from the past three decades.

wrong place etc. The camera recorded footage is helping

Recently, an initiative - building 100 Smart Cities wasto control anti-social elements and sensational crimes.

started with an investment of Rs.96,000 crores to execute

2. OBJECTIVES OF THE STUDY

within five years (2015-2019). The aim of these cities is(i) To study the causes of road accidents in Hyderabad

to meet the urban-centric citizen needs by adapting

city. (ii) To understand the causes for road conditions andInformation and Communication Technologies (ICTs).

traffic congestions on the city roads. (iii) To analyze theYet, one question can remain is – are these cities are safer

various technologies deployed on the city roads to preventfor the residents?

the road accidents and deaths.

Safety of residents can be understood in two

3. METHODOLOGY

ways: (i) safety from natural disasters and (ii) safety from

The investigator interviewed about 30 senior police

physical threats viz., thefts, robbery, road accident deaths

officers and, secondary data was collected from reliable

etc. To protect from the physical threats, governments are

web sources, reports and newspaper articles.

making time bound solutions because safety of residents

4. BACKGROUND

is a critical concern for them. According to the recent

The city roads are covering with bicycles, scooters, autos,

statistics, with the deployment of Close Circuit Televisioncars, trucks, buses, mini-vans and pedestrians etc. The(CCTV) cameras, the number of threats and roadrecent traffic incidents data says two wheelers and four

accidents has come down in the city of Hyderabad whichwheelers are causing more accidents on the city roads asis the focus of this study.

shown in the below picture [2]. The cameras deployed are

Keywords: Commuter Safety, Road Conditions, City

somewhat helping both the commuters and regulatory but

Transportation, Smart Cities Mission, Technologies

a few more advancements are recently introduced for

1. INTRODUCTION

preventing the road accidents.
th

The Hyderabad City is the 6 largest city in India with apopulation of about 7.75 million located in hilly andterrains. The city has approx. 40 lakh registered vehicles[3/4th are two wheelers] and the accident deaths are about
400 on average in a year, during 2013 to 2016. The
number of road accident deaths is increasing due to thesubstantial growth of urbanization and loud boom ofvehicles. However, after deployment of CCTVs, thenumber has come down to 288 in 2017 [1]. Thesecameras are integrated to a Command Control Centre[Source: Hyderabad Traffic Police]178

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 54(i) Technologies that are helping ‘Regulatory Authority’Firstly, Computer based tests are deployed to takemWallet, a free downloadable app act as a wallet to store

stringent steps while issuing driving licence [5]. It can belicence related documents in the smart phones viz.,either learner licence or permanent licence. Recently,

driving licence, registration and insurance certificates that

Insurance Regulatory and Development Authority oflessened both transport and police verification process.

India (IRDA) had made mandatory that third party

Earlier, Collar mikes, body worn cameras are in place for

insurance to be enhanced to 3 years for cars and 5 years

recording the interactions of an offender when he wasfor two wheelers from 1st September 2018. Earlier it wascaught by officers. Online e-challan is CCTV footage

only one year for both types of vehicle. Then, a Twelve-

based penalty process, when traffic violation occurs it

point mobile based penalty system was introduced togenerates a challan and delivered to a violator postal

impose penalty for careless, lecense-less, speed andaddress [3]. HydCop is another mobile app where thedrunken driving etc. The majority commuter mobile

entire city police is connected and communicates withnumbers are linked and made mandatory when theyeach other. With such exchange of information, incidents

purchase or register a new vehicle and while applying forsuch as managing crowd, mob attacks are under control

the driving licences that eased the penalty system.

[4]. Other than the technologies, Stone-pelting protection

Hyderabad Traffic Live is a mobile app that provides

plates and blue colts are safeguarding the police from theinformation on traffic conditions and details viz., nearby

gangsters, decoit attacks and other civic agitations etc.

traffic police station address, concerned officer contacts(ii) Technologies that are helping ‘commuters’

and road safety tips etc. During any havoc or hazardous

MyGHMC is a mobile app where commuters can raisesituations, commuters can approach the concerned

their grievances by capturing the photographs of any

officers for booking complaints. Frequency modulation

issues such as road conditions, hazards, street lightening,(FM) radio and social media (twitter) alerts are alsosanitation problems etc., HawkEye This GPS enabled

helping the commuters to manage the traffic congestions

mobile app that has SOS button is very useful for aon the city roads. To control the vehicles speed - laser

women when she commutes in a private cab or on the city

guns, speed guns and breathalyzer tests for drunken

roads. SHE Teams is a special drive which is protecting

driving are in place. Recently, the police have also

the working women safety from the eve-teasers at bus

deployed video analytics, face recognition devices tostops i.e., safeguarding the women safety on the roads.

identify the rowdy sheeters and perpetrator activities inIntegrated Voice Responsive System (IVRS) toll freepublic places viz., VIP bandobasth, political party

numbers 100, 101, 108 (24/7 Call Centres) from where

meetings and railway stations etc., for better monitoring.

commuters can directly make complaints or report

A study led by the Rutgers University in New Jersey

grievances to the authorities.

indicated that ordinary wi-fi could be used to detect

5. RESULTS

weapons and explosives in public places in very near

Other than these advancements, the study results havefuture [6]. These need to be explored and replicated on

found some more distinguished features deployed for

rapid basis for safety of commuters on the city roads.

commuter safety and to create awareness towards trafficb. Road Safety [Accident brings tears – Safety brings

rules and the law. These are classified into three sections -Cheers] A city road condition is another determining

Commuter Safety, Road Safety and Self Governance.

factor which avoid accidents but Indian road engineeringa. Commuter Safety [Drive Safe and Stay Safe]

varies among National highways, State highways, city,

The commuters, by taking an extra care while driving cancolony roads, footpath lanes, sub-ways, under-groundsafely reach their destination on the roads for which somepassages, flyovers, pedestrian and roads for cyclists etc.

technology advancements are introduced in the city.

An extra care has taken while laying these different set of179

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 54
roads by adopting the highest engineering standards.

record that safety of others is also important hence

Especially, when a road has bumpy and potholes - thewearing helmets and seat belts are to be practiced inauthority is overseeing the works in a time bound manner.

rigour. It is estimated that 30% accidental deaths andRecently, a white topping technology was implemented

hazards are taking place only because of not having seaton a pilot basis where cement concrete was overlaid on

belts in the cars. It was also revealed that majority air-the damaged roads, which has 15 to 20 years ofconditioned (AC) cars are meeting with the roadsustenance life [7]. The same technique was escalated toaccidents. Thus, the road accidents are manyfold

another 65 city roads that are accident prone junctions

especially, when it leading to a death, it can affect on the[ibid]. These junctions have black whole points (Novictim’s family. The young generation aged between 18-

Return Roads) and are safeguarding the traffic signals by

35 years are causing more bike accidents due to theconverting them into a legal U-turns. The recently laid

licence less driving [9]. The police are giving counselling

158 kilometres Nehru Outer Ring Road with eight laneto the parents who are giving costly and speed bikes toroads are avoiding heavy load vehicles on the city roads.

their children through Community Policing (NenuLight Detection and Ranging (LIDAR) Gun is another

Saitham – meaning ‘Me too’) campaign to prevent childdevice that estimates tailgating and speed of a vehicle on

riding [10]. Use of mobile phones and watching LCD

the cross roads but commuters are not much aware of thistelevision (distracted driving) are another reasons for thedevice. It is needed to create awareness on such devices toroad accidents. Riding with more than one pillion,

reduce the traffic violations on the city roads. Wayback inoverloading cargo, outdated vehicles are some more

the year 2005, Safety always for all roads (SAFAR) wascauses [11]. It is impossible to cover all sorts of risks

introduced to sensitize the commuters, drivers, school

hence it is the discretion of commuters to govern

children and general public. The objectives of thethemselves on the roads.

program was somewhat met and need to reintroduce to

6. CONCLUSION

meet the current trends of traffic violations. An Advanced

The Police department of Hyderabad city do not have

Driver Assistance System (ADAS) which was in the pilot

sufficient budgets yet, they are managing the safety ofstages in European and Western countries that has ancommuters and roads mostly with the help of CCTV

electronic stability control, autonomous emergency

cameras, currently. But most of the time they are using

breaking system, anti-lock brake, lane departure warning,

outdated technologies (not updated) and not adequate toadaptive cruise control and blind spot features are yet tosolve the real-time problems. The department has tointroduced on the Indian roads [8]. The existing number

sanction substantial budgets to purchase new (GPS, GIS

plate recognition devices, GPS enabled cabs and longenabled) vehicles and electronic gadgets so that those canfusion cameras are yet to sensitize the safety segment on

be connected to command control centers for efficient

the city roads. But with the currently available

patrolling. Though, Hyderabad is not chosen as a Smarttechnologies and the effort of integrating several

city but the technologies adopted are commendable anddatabases of commuters, road safety is reasonably incan be replicated to any other cities. The road expansions,place. Notwithstanding the above means, it is also

widening, dividers and speed controllers for the vehicles

commuter responsibility to take extra care while

are to be enforced in regular intervals by the regulatorycommuting on the roads.

bodies. Road Safety Audit which regulates periodicc. Self Governance [Speed Thrills but Kills]

maintenance of roads and standards is to ensure better and

Nearly, 75% of the road accidents occur due to the humansafe roads was difficult for the authorities to organize on

error on the city roads viz., fatigue, drunken driving, overthe existing city roads. This limitation can be overcome

speeding and incompetent driving etc. It has to put on

while planning and designing of city roads in the future180

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 54
green field cities. Due to the enormous growth in the[4] http://www.thehansindia.com/posts/index/Hyderabad-

number of vehicles, the number of risks and accidents are

Tab/2017-10-26/For-better-road-safety-use-Call-also equally increasing in the cities. Apart from that bus

Ambulance-technology/335472

stops are also located near to cross road junctions which is[5] Road Safety Strategy in the State, Transportcausing more traffic jams and accidents i.e., close to the

Department, Government of Andhra Pradesh. Pg2

bus-bays. Many a times, these bus bays are occupied with

[6] https://www.bbc.co.uk/news/technology-45196164

the contract carriage vehicles which can be captured with

[7] https://india.smartcitiescouncil.com/article/hyderabad-the help of CCTV cameras to impose penalties. To

adopts-white-topping-technology-gets-maintenance-free-

identify the wrong path riders and to maintain the laneroads

discipline on the roads, penalty through these cameras[ibid]

also another area that can be introduced. The currently

https://www.thehindu.com/news/cities/Hyderabad/technol

available technologies are surely adequate to handle theogy-to-determine-quality-of-roads/article19862998.ece

current traffic conditions however there is a need to[8] https://en.wikipedia.org/wiki/Advanced_driver-

introduce more futuristic technologies to solve the futureassistance_systems accessed on 30th September 2018

problems. The transport department has been imposing[9] M. Bhagyaiah and B Shrinagesh. Traffic analysis andchallans and penalties in substantial amounts compared toRoad Accidents: A Case study of Hyderabad using GIS.

the old rates such additional income can be invested on

IOP Conference Publishing. Pg.6. oi:10.1088/1755-

building new infrastructure viz., multi-level complexes

1315/20/1/012026.

for car parking and double-decker fly-overs to control the[10] Harnam Singh and A D Aggarwal. Fatal Road

traffic congestions. Integrating with the air quality sensors

Traffic Accidents among young Children. J Indian Acad

which are meant for predicting the pollution of a specific

Forensic Med, 32(4). ISSN 0971-0973. Pg.287.

area on city roads is another feather that can be looked[Ibid]

into. There were several incidents where the offenders

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893966/

escaped even from the CCTV images especially in the[11] Sanjay Kumar Singh. Road Traffic Accidents innights hence all the technologies can not guarantee fool-

India: Issues and Challenges. World Conference on

proof solutions but one has to have the will and passion toTransport Research. Science Direct. Pg.4717.

execute. Thus, the political and executive will is[Ibid]https://timesofindia.indiatimes.com/city/hyderabad/necessary in implementing the technologies in the

more-road-accidents-in-upscale-tech-corridor-than-administration process where Hyderabad police are far far

highways-reveals-data/articleshow/63252115.cms

ahead. Finally, new technologies will come and go but
choosing and deploying the right one to the contemporary

BIBLIOGRAPHY

needs was the key to success.

1. Guidelines for Road Safety Audit, A report by Govt. of

7. REFERENCES

Karnataka[1] Donita Jose

2. Research Framework for Road Safety in the South-East

https://timesofindia.indiatimes.com/city/hyderabad/fatal-

Asia Region. A report by World Health Organization

accidents-on-hyderabad-roads-drop-by-(WHO), 2015.

50/articleshow/62107205.cms accessed on 12th Sep 2018

3. Road Safety – Impact of New Technologies: A report[2] http://hyderabadpolice.gov.in/Traffic.html accessed onby Organization for Economic Cooperation and

8th Sep 2018

Development (OECD).
th[3] http://www.htp.gov.in/ accessed on 9 Sep 2018

4. https://sites.ndtv.com/roadsafety/5-technologysolutions-can-make-indias-roads-safer-2647/

181

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 72

DEVELOPMENT OF QUICK INSPECTION SYSTEMFOR DAMAGED HOUSES AFTER THE EARTHQUAKE USING INFRARED CAMERA
Yuki MATSUOKA1, Makoto FUJIU2,
Jyunichi TAKAYAMA3, Shinya SUDA4
1

Bachelor, School of Environmental Design, Kanazawa University, Kanazawa, Japan,
Assistant Professor, Ph.D., School of Environmental Design, Kanazawa University, Kanazawa, Japan
3
Professor, Dr., Eng., School of Environmental Design, Kanazawa University, Kanazawa, Japan
4
President, SkyLink Japan, Kyoto, Japan
2

Keywords: earthquake, unmanned aerial vehicle, infrared camera, visible light camera, Microsoft Azure, AI
1. INTRODUCTION
The Kumamoto earthquake occurred at 1:25, April 16,
2016[1]. There are many dangerous places in the affected
area, restrictions are placed on the activities of the
respondents of the victims in the affected area, theevacuation life of the victims in the affected area and theinvestigators of emergency risk determination performed
after the earthquake disaster. In order for victims andinvestigators to work safely in disaster areas, it isimportant to grasp the hazards in advance. Therefore, inthis research, we have machine-learned image data
photographed in the disaster area using an infrared camera
mounted on a small unmanned aerial vehicle (UAV), andidentified and grasp the roof damage of the affectedbuilding by computer.

Visible light camera

Infrared camera

Figure 1: The building of experimental subject takenwith a visible light camera and infrared camera
building can be recognized. Therefore, it is suitable fordamage judgment.
4. BASIC ANALYSISFirst, it was confirmed visually the difference between
how to appear the building damage in the visible lightcamera and the infrared camera. For example, from Figure
1 when the temperature of tile is high, the infrared camera
indicate white color. And when the temperature of no tile
is lower than the temperature of tile, the infrared camera
indicate red color.
This color difference is determined using AI.

2. DATAWe selected the Miyazono area of Musashiro-machi,
Kumamoto Prefecture, which was affected by the
Kumamoto earthquake area. Masuki-cho is the area thatobserved the maximum seismic intensity 7 on the
Kumamoto earthquake, the area most damaged in
Kumamoto prefecture, where the building damage isnoticeable. Therefore, we decided to obtain building
damage data from the building in Miyagi-machi
Miyazono area.
The building damage data was collected in Mashiki city
on April 30, 2016. We flew a UAV equipped with an
infrared camera up to about 50 m which does not interferewith obstacles such as electric poles and electric wires andthe height does not become rough, and photographed theafflicted building in the Miyazono district from directly
above. After that, we changed the camera to a visible lightcamera and shot at the same condition / place. The
building damaged easily to compare the video taken witha visible light camera and infrared camera and to
determine the roof damage, which is used as the subject ofexperiments in this study (Figure 1).
In this research, we use the image of the infrared camera
to judge the damage of the roof of the building. The reason
why the image of the infrared camera is used instead of
the image of the visible light camera is that the amount ofcolor information in the image of the visible light camera
is too large, so it takes time to judge the damage. However,in the image of the infrared camera, since the informationon the roof damage area is converted into the temperature
information, the information amount is retained and the

5. Outline of the AI system used in this research
In this research, in order to quickly judge the roof
damage of a disaster-affected building in the affected area,
we aim at automatic judgment by a computer, not visualjudgment by a person. Therefore, I decided to use AI forthat judgment.
We use Microsoft Azure's Cognitive Services For thisanalysis. This study used Custom Vision which isclassified as vision in Cognitive Services,

Figure 2: Microsoft Azure's Cognitive Services

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 72
6. Determination of damaged buildings from theinfrared image using AI system
The Cognitive service is made to model by learning by
AI. Therefore, the data for learning is necessary. In thisanalysis, we have learned infrared images of buildings
with roof damage and infrared images of buildings
without roof damage, in order to create a model to judge
whether infrared images of buildings in affected areas
have roof damage or not. In the infrared image of thebuilding with the roof damage, tags of "building" and"roof damage" were tagged, and the infrared image of thebuilding without roof damage was tagged with "building"and "no damage" and learned by AI. The accuracy of all
tags was 100%, and when I recalled, the tags of "building"and "roof damaged" were 100% and the tag of "nodamage" was 83.3% and the average was 94.4%.
We determined the building with roof damage and thebuilding without damage using this created image
recognition model. The results are shown in Figure 3 and4. According to Fig. 3, the probability of "building" is100%, the probability of "roof damage" is 99.9%, and theprobability of "no damage" is 0% in the created image
recognition model for buildings with roof damage.
According to figure 4, the probability of "building" is
98.8%, the probability of "no damage" is 95%, and theprobability of "roof damage" is 0% in the created image
recognition model for buildings without roof damage.
Infrared images of two damaged buildings and two nodamage buildings were judged, and good results wereobtained respectively.
From the above, it was suggested that the image
recognition model created this time can judge the infrared
image of the damaged building as "roof damaged" and "nodamage".

Performance Per Tag

Tag

Probability

building
roof damage
no damage
Figure 3: Determination result of building
with roof damage

7. CONCLUSIONS
2016 Kumamoto earthquake occurred at 1:25, April 16,
2016. It was taken of the building affected by theearthquake by the infrared camera mounted on UAV in
Mashiki city on April 30, 2016. We visually confirmedthat roof damage can be grasped from infrared image. In
addition, Cognitive Services of Microsoft Azure was used
to create a model to judge, whether or not the infrared
image of the damaged building has roof damage.
As a result, it was possible to distinguish the damaged
part from the non-damaged part, indicating the possibilityof quickly judging the damage of a large number ofbuildings, and suggesting that it is possible to grasp thedangerous part in the afflicted region.
As a future prospect, we aim to learn and judge thebuilding where the roof damage is caused and the blue
sheet is put on the roof. Furthermore, we aim not only tojudge the existence / nonexistence of the current damage,but also to create a model that classifies the damagedbuildings according to the extent of the roof damage andallows them to learn and to judge the extent of the damage.

Performance Per Tag

Tag

Probability

building
roof damage
no damage
Figure 4: Determination result of building
without roof damage[1] Japan Meteorological Agency HP:
http://www.jma.go.jp/jp/quake/quake_local_index.html
Reference to an overview academic conference[2]Yuki MATSUOKA, Makoto FUJIU, Jyunichi
TAKAYAMA, Syoichiro NAKAYAMA, Shinya SUDA
andHirokiSAKAGUTI,(2016)“赤外線カメラを用いた地震発生直後の建物被害自動検出に関する基礎的研究”，第36回地震工学研究
発表会論文概要集REFERENCES
Reference to a home page:

Notice : Part of the content of this paper is patent pending.

183

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 62

INFLUENCE OF CONTAINMENT REINFORCEMENT ON THE
SEISMIC RESPONSE OF URM BUILDINGS CONSIDERING THE EFFECT OF FLEXIBILITY OF
SOIL MEDIUM

S. R. VAIDEHI1, P. NEETHU2, and S.V. JISHA3
1

PG Research Scholar, Structural Engineering, Mar Baselios College of Engineering and Technology,
Thiruvananthapuram, Kerala, India, vaidehisr781@gmail.com
2

PG Research Scholar, Structural Engineering, Mar Baselios College of Engineering and Technology,
Thiruvananthapuram, Kerala, India, neethusprakash94@gmail.com
3

Assistant Professor, Department of Civil Engineering, Mar Baselios College of Engineering and Technology,
Thiruvananthapuram, Kerala, India, jpn.nitk@gmail.com
Abstract: Un-Reinforced Masonry (URM) buildings represent one of the most seismically vulnerable building types,
which are weak in resisting lateral loads. In most of the studies the seismic response of conventional URM buildings
are evaluated without considering the effect of soil strata. The main objective of this study is to investigate theeffectiveness of vertical containment in mitigating seismic vulnerability of URM buildings incorporating the effect of
flexibility of underlying soil strata. Four URM buildings with dimension 6×3×3m are considered namely, (i)buildings
without roof slab and lintel band (ii) building without roof slab and with lintel band (iii) buildings with roof slab andlintel band and (iv) buildings with roof slab, lintel band and containment reinforcement. Vertical containment
reinforcement of 12mm diameter steel bars of Fe250 grade is provided on the surface of the walls on both faces with aspacing of 1m. Time history analysis is carried out by considering Bhuj (2001) ground motion. The effect of SoilStructure Interaction (SSI) is evaluated by considering three different types of soil strata such as soft clayey sand strata,
medium clayey sand strata and rock. Three-dimensional building-foundation-soil system is analysed using finite
element method on the basis of direct method of SSI. Non-linear material behavior of underlying soil medium and linear
behaviour of buildings is considered. The responses such as storey deflection and base shear of URM buildings withand without considering the effect of SSI are evaluated. It is found that responses such as storey deflection and baseshear of the buildings increased by two times and nine times respectively for buildings with containment reinforcement
than building without it due to the effect of SSI. Also, with lintel band, roof slab and containment reinforcement the
deflection decreased by four times compared to building without it in mitigating seismic vulnerability in terms ofdeflection.
Keywords: Un-Reinforced Masonry buildings, Containment reinforcement, Time history analysis, Soil-StructureInteraction
1. INTRODUCTION

floor and walls, anchor failure when joists are anchoredto walls were studied. A combined in-plane and out ofplane effects showed that in-plane failure may not lead tocollapse since the load carrying capacity of a wall is notcompletely lost by diagonal cracking, whereas, out-ofplane failure leads to unstable and explosive collapse [6].
The structural performance of URM buildings are
improved by using containment reinforcement. This
containment reinforcement is provided around masonrywalls at an appropriate spacing. The reinforcements on
the two faces are tied together through links or ties
provided at a definite vertical spacing as shown in Fig.1.
As the masonry wall bends, one face of masonry would
be subjected to tension and the reinforcement on that side
would bend to its profile. The reinforcement on thecompression side would tend to become slack. The
reverse happens as the wall bends the other way [7,8].
Here the reinforcement is intended to prevent the growthof flexural tensile cracks that lead to failure. The

Un-Reinforced Masonry (URM) construction is the mostcommon type of construction in rural as well as urban
areas due to its lower cost, ease of construction and goodaesthetics. The damages observed in these structures
depend on quality of materials and construction,
structural layout and connections between structuralelements.
Numerous experimental investigations were carried out
on URM walls which shows the seismic behaviour ofbrick masonry walls [1-3]. Considering the influence offlanges on the in-plane behaviour of URM walls it isobserved that for a diagonal tension-controlled wall,
once a stair stepped crack is opened up, sliding can be
expected to occur along the bed joints and deformation
can be expected [4]. The seismic performance of URM
with different types of failures such as in-plane failure[5], out-of- plane failure, lack of anchorage between

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17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 62
containment reinforcement will prevent brittle failure
due to tension cracks and permit larger deflections andhence a much higher absorption of energy without asubstantial increase in strength.

2. METHODOLOGY
Idealisation of the building and foundation
In this study, single storeyed masonry buildings having
masonry walls made of laterite blocks of 1:6 cement
mortar is considered. For improving the seismic
performance of URM buildings lintel bands, roof slabs
and containment reinforcement are used. Four types ofmasonry buildings such as (i) building without roof slab
and with lintel band (ii) building without roof slab andwith lintel band (iii) building with roof slab and lintel
band (iv) building with roof slab, lintel band andcontainment reinforcement are used. The designation
used for the above four types of buildings are given in
Table 1. Fig.2 shows the various building configurations
used for the analysis. URM buildings with plan
dimensions of 6m x 3m x 3m have been considered forthe analysis. Provisions of openings in the buildings havebeen considered with one door of size 1 m x 2 m on front
longer wall. The considered plan has one window in thefront longer wall and two windows in the longer wall ofbackside. Each of the short walls is assumed to beprovided with one central opening of dimension 1m ×1m
for window. Fig.3 illustrates the plan dimension of the
URM building with vertical containment reinforcement.
Vertical containment reinforcement made of 12mm
diameter steel bars of Fe250 grade is provided on thesurface of the walls on both the faces at a spacing of 1 m.
Roof slab of thickness 0.12m and lintel band of thickness
0.2m and width 0.2m with M25 grade concrete andFe250 grade steel reinforcement is used.

Fig. 1. Masonry with containment reinforcement andlinks [9]From the studies it is understood that response ofbuildings depends on the response of the underlying soil
medium and vice versa especially when considering the
dynamic loads. The soil-structure interaction model canbe used for a complete probabilistic study of the responseof a corner section of a single storey masonry veneer
house founded on an expansive soil [10]. The model has
the potential for widespread applications for similar suchstudies [11-12]. The responses of various buildings on
soft clay and hard rock have been performed byintroducing the theory of SSI [13]. There are twodifferent approaches for interaction effects namely, direct
approach and indirect approach. In the direct approach,structure is modelled explicitly with soil strata and acomplete solution is obtained in a single analysis. In thesubstructure method, the soil-structure system isanalysed separately as two substructures; a structure
which may include a portion of non-linear soil strata andthe unbounded soil. If the structural foundations were
perfectly rigid, the solution arrived by substructure
approach and direct-method will be identical. The
influence of SSI on elastic and inelastic range responses
of low-rise building frames resting on shallow
foundations shows that the base shear increases due tothe effect of SSI. The seismic response of medium tohigh rise buildings generally decreases due to the
influence of SSI [14,15].
Many of the previous researches focus on the numerical,
analytical and experimental study on masonry building.
Very few studies emphasis in the seismic behaviour ofmasonry buildings subjected to earthquake groundmotion considering the effect of underlying soil medium.
This study enumerates the effects of SSI on URM
buildings using an integrated three-dimensional soilstructure system considering nonlinear behaviour of soil
stratum.

Table 1. Types of single storeyed masonry structures
Designation
U
UL
ULR
ULRC

Building description
URM building without roof slab andlintel band
URM building without roof slab andwith lintel band
URM building with roof slab and lintel
band
URM building with roof slab, lintel
band and containment reinforcement

Fig.2. Configurations of URM buildings (a) U (b) UL(c)ULR (d) ULRC type [8]18517th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 62

Property

Modulusof
Elasticity(kN/m2)
Poisson’s
Ratio(assume)Mass
Density(kg/m3)

Table 2. Material properties

Idealisation of soil strata

MasonryRC(used inlintelband, RoofSlab)VerticalContainment
reinforcement

1.20×106

2.50×107

2×108

0.15

0.15

0.30

2100

2500

7850

Three different soil strata considered in this analysis areSoft clayey sand strata (S), Medium clayey sand strata(M) and Rock (R) in which the flexibility decreases fromrock to soft strata. Bedrock was assumed at a depth of
30m below the soil stratum. The lateral dimension of thesoil stratum was taken as four times the lateral dimensionof foundation [16]. The properties of soil strata aredefined by its mass density, modulus of elasticity,poisson’s ratio and angle of internal friction [17] asshown in Table 3. There are various types of soil models
used to represent soil media. Here, Drucker-Prager (DP)model is used to define the non-linear soil stratum. DP
model represents non-linear plastic failure of the soil andis simple as well as easy for numerical analysis. The DP
yield criterion is a pressure-dependent model for
determining whether a material has failed or undergone
plastic yielding. The criterion was introduced to deal
with the plastic deformation of soils and have been
applied to rock, concrete, polymers, foams, and otherpressure-dependent materials.

Strip footing of random rubble masonry having width of
0.6 m and depth of 0.6m is provided. Table 2. provides
the properties of masonry, RCC and vertical containment
reinforcement bars. Fig.4 gives the sectional elevation of
URM building giving the details of foundation.

Table 3. Properties of soil strata [17]
Soil
type

Poisson’s
ratio

Density(kg/m3)

Elastic
modulus(kN/m2 )Angleoffriction(ø)

Cohesion(kN/m2 )

S

0.20

16

50000

30

50

M

0.25

18

100000

34

100

R

0.30

20

25000038

200

Fig.3. Plan of ULRC building [8]3. FINITE ELEMENT ANALYSIS
Finite element analyses of 3D integrated soil-structure
system were carried out by using the finite element
software. Different building components of a URM
building under consideration are masonry, roof band,
lintel band and vertical containment reinforcement. The
URM building, foundation and underlying soil strata
were modeled using eight noded brick element having
three translation degrees of freedom at each node. Roofslab is modeled by using four noded elastic shellelement. The element has six degrees of freedom at eachnode and has both bending and membrane capabilities.
The vertical reinforcements were modeled using truss
elements which is a uniaxial tension-compression
element, also with three translational degrees of freedom
at each node. All the masonry walls, lintel band, roof

Fig.4. Sectional elevation of U building18617th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 62
slab, vertical containment reinforcement and foundation
were discretized with mesh size 0.2m. The soil strata
were discretized with mesh size of 1m upto a depth of
20m and with mesh size 2m for the remaining depth
along the vertical direction. Along the lateral direction
soil stratum is discretized with mesh size 1m. The finite
element structure of building with and without soil
medium is depicted in Fig.6 and Fig.7 respectively. The
total discretized system, consisting of the structure andthe soil was then analyzed. This system was analyzed
based on direct method of SSI by assuming the linear
behaviour of building and foundation and nonlinear
behaviour of underlying soil strata.

46.94s for Bhuj ground motion. The earthquake reacheda magnitude of 7.7 Mw on the moment magnitude scale.
The Fourier amplitude spectrum of Bhuj earthquake isrevealed in Fig.9. Free vibration analysis is carried out tofind the frequency and mode shapes of the U, UL, ULR
and ULRC buildings with and without considering SSI.
The responses such as storey deflection and base shear isalso found out from the time history analysis considering
their base fixity and base flexibility.

Fig.8. Acceleration time history of Bhuj earthquake [18]Fig.6. Finite element URM building

Fig.9. Fourier-amplitude spectrum Bhuj earthquake [18]5. RESULTS AND DISCUSSIONSAll the four types of URM buildings were analysed tofind their responses under Bhuj ground excitation.
Frequencies were calculated. The absolute maximum
responses such as deflection and base shear
corresponding to fixed base buildings were evaluated.
Variation of Natural frequency
The natural frequency determined for URM building
with and without the soil stratum is tabulated in Table 4.
Fundamental natural frequency obtained from buildings
with fixed base is higher than that obtained from SSI
analysis. Increase in frequency of the buildings is due tothe increase in stiffness of the building. Variation of
fundamental frequency of building with flexible basefrom that of building with fixed base is more for U typebuilding resting on soil type S and the maximum
variation is about 47%.

Fig.7. Finite element Soil-Structure system
4. GROUND MOTIONTime history analysis was conducted for URM buildingsfor Bhuj ground motion (2001). A part of the Bhuj
ground motion acceleration recorded at Ahmedabad
during earthquake which lasted over 135s is revealed in
Fig.8 [18]. The peak ground acceleration is 0.11g at time187

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 62
Table 4. Comparison of natural frequency of building

Table 6. Variation in base shear of buildings

Fundamental Natural Frequency (Hz)
U

UL

ULR

Designation

ULRC

S

2.859

4.394

4.575

4.583

M

2.860

4.408

5.002

5.182

Base

Variation of base shear ofShearbuildings (%)(without
SSI)

S

M

R

(kN)
H

2.862

4.411

5.071

5.339

Fixed

4.950

6.904

11.05812.397

U

179.98

87.78

92.17

93.49

UL

194.10

88.95

92.19

94.27

ULR

236.31

89.11

92.20

94.35

Variation of deflection

ULRC

243.06

89.75

93.57

94.85

The percentage variation of displacement of buildings
with flexible base compared to fixed base is given in
Table 5. The percentage variation of deflection for UL,
ULR and ULRC buildings decreased by 43%, 95% and
96% respectively with respect to U building without
considering the flexibility of soil strata. The percentage
variation of deflection is 60% for U building supported
on soft soil strata when compared with the same type ofbuilding with base fixed. The variation reduced to 40%
and 20% for the same building supported on medium
strata and rock respectively. The same is observed in UL,ULR and ULRC buildings. It is found that the deflectionof the UL, ULR and ULRC building increases withdecrease in stiffness of soil compared to U type building.

6. CONCLUSIONS
The analysis of URM buildings considering the SSI
effect is compared with buildings with fixed base. The
major findings are shown below:(i) With lintel band, roof slab and containment
reinforcement the deflection decreased by four times
compared to building without it in mitigating seismic
vulnerability in terms of deflection.
(ii) The effect of SSI is significant while considering
vertical containment reinforcement. The shear isincreased by nine times and deflections increased by twotimes for buildings with vertical containment
reinforcement than building without it when soft clayey
sand stratum is account for.

Table 5. Percentage variation in displacement

REFERENCES
Designation

Displacement% variation of(Without

displacement (with SSI)

SSI) (mm)S

M[1] Anthonie, A., Magonette, G. and Magenes, G., (1995)“Shear compression testing and analysis of brickmasonry walls”, Proceedings of 10th European
Conference on Earthquake Engineering, (Taylor andFrancis), 657-1662[2] Dolatshahi, K. M. and Aref, A. J., (2016) “Multidirectional response of unreinforced masonry walls:
experimental and computational investigations”,
Earthquake Engineering and Structural Dynamics,(Wiley Online Library), 45, 1427–1449[3] Khanmohammadi, M., Behnamb, H. and Marefata,
M. S., (2015) “Seismic behaviour prediction of flanged
unreinforced masonry (FURM) walls”, Journal of
Earthquake Engineering, 18(5), 759-78[4] Kalali, A. and Kabir, M. Z., (2012) “Cyclic behaviourof perforated masonry walls strengthened with glass fibre
reinforced polymers.” Scientia Iranica, (Elsevier), 19(2),151–65[5] Singh, Y., Lang, D. H., Prasad, J. S. R. and Deoliya,R., (2013) “An analytical study on the seismic
vulnerability of masonry buildings in India”, Journal of
Earthquake Engineering, 17, 399–422

R

U

3.717

60.10

40.70

20.42

UL

2.109

78.97

73.37

40.25

ULR

0.160

96.47

93.31

87.40

ULRC

0.150

96.45

92.80

87.20

Variation of Base shear
Variation in base shear of low-rise buildings withflexible base is higher than buildings with fixed base.
Table 6. displays percentage variation in the base shearof buildings. In the table given, there is an increase of
35% of base shear in ULRC type building than U typebuilding. Therefore, base shear of a building with lintel
band, roof slab and containment reinforcement are muchhigher than that of building without these. The building
with more seismic weight has high base shear. Also, baseshear got increased approximately about 94% for URM
buildings due to the effect of SSI compared to masonrybuildings without SSI.

188

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 62[6] Bruneau, M., (1994) “State-of-the-art report on
seismic performance of unreinforced masonrybuildings”, Journal of Structural Engineering, (ASCE),
120(1), 231-251[7] Unnikrishnan, S., Mattur, N. C., and Venkataramana,K., (2013) “Effect of containment reinforcement on theseismic response of box type laterite masonry structures– an analytical evaluation,” Earthquakes and Structures,
5(1), 067-081[8] Jagadish, K. S., Raghunath, S. and Rao, N. K. S.,(2002) “Shock table studies on masonry building modelwith containment reinforcement”, Journal of StructuralEngineering, 29(1), 09-17[9]
http://civil-online2010.
blogspot.in/2010/02/
earthquake resistant features in html downloaded on
24/03/2018[10] Masia, M. J., Kleeman, P. W. and Melchers, R. E.,(2004), “Modeling Soil of Structure Interaction for
Masonry Structures.” Journal of Structural Engineering,
ASCE, 130, 641-649[11] Masia, M. J., Totoev, Y. Z., and Kleeman, P. W.,(1999), ‘‘Modelling reactive soil movements for the
study of cracking in masonry structures.’’ Proceedings of
16th Australian Conference on the Mechanics ofStructures and Materials, Sydney, Australia, 685– 690[12] Saliba, J. E., Al-Akkad, R. S. and Sawaya, G. E.,(1996), ‘‘Use of finite elements in masonry structures.’’
Masonry Society Journal[13] Suyehiro, K., (1932) Engineering seismology noteson American lectures, Proc. ASCE,58,4,1-110 (1932).
[14] Dutta, S.C. and Roy, R. (2002). "A critical review
on idealization and modelling for interaction among soil–
foundation–structure
system."Computerand.
Structures., 80, 1579-1594[15] Luigi, C., Sebastiano, R. and Giulia, M. B. V.
(2013), “Soil–structure interaction for the seismic designof the Messina Strait Bridge”, Soil Dynamics andEarthquake Engineering, (Elsevier), 52, 103-115[16] Jisha, S. V., Jayalakshmi, B. R. and Shivashankar,R., (2015) “Response in piled raft foundation of tallchimneys under along-wind load incorporating flexibilityof soil”, Frontiers of Structural and Civil Engineering,(Springer., 9(3), 307-322[17] Bowles, J. E., (1997) Foundation analysis anddesign., McGraw-Hill International Editions, Singapore.
[18]http://www.strongmotioncenter.org/vdc/scripts/event.
plx?evt=785[19] IS: 1893 (Part 1) :2016, Criteria for Earthquake
Resistant Design of Structures, Bureau ofIndianStandards, New Delhi, India[20] IS: 1080:1985, Code of Practice for Design andConstruction of Shallow Foundation in Soils (other thanraft, ring and shell), Bureau of Indian Standards, New
Delhi, India

189

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 18

REJUVENATION OF AMANISHAH NALLAH – A CASE STUDY
N.K. HARANATH PINNAMARAJU1, SHAIK MAHAMMAD JABEED2, MOHAMMED.ARBAAZ PARVEZ3,
K. HARIHARANATH4
1
Senior Manager, TATA Projects Limited Hyderabad, haranathpnk@tataprojects.com
2
Manager, TATA Projects Limited Hyderabad, shaikjabeed@tataprojects.com
3
Deputy Manager, TATA Projects Limited Hyderabad,arbaazm@tataprojects.com
4
Deputy General Manager, TATA Projects Limited Hyderabad,hariharanath@tataprojects.com
Keywords: Amanishah Nallah, Rejuvenation, Urban Safety.
1. INTRODUCTION
Dravyavati River which is now called as
Amanishah Nallah is the major drainage system in thewestern outskirt of Jaipur City. It flows in a length of
47.5Km originating in the Amer Forest Nature Reserveand flow through the central part of Jaipur city anddrains into Dhund River. It has the catchment area of 240
Sq.Km and maximum flood discharge of 1700 cumecs
and the width of the river varies from minimum 50m to
300m. Due to adverse effect of urban Sprawl this river
had been converted into Nallah which mainly undertakes
drainages of rains from the catchment areas that includes
banks and other branches, wastewater drainage andagricultural irrigation along the river. The Nallah being
dry in most of the seasons, heavy encroachments havecreated a danger floods during Monsoons. The pollutantsin the Amanishah Nallah are also rising causing healthhazards and destroying the ecological system. This paper
deals with, how we had transfigured Amanishah Nallah
into a magnificent and attractive place to attract people
and make Jaipur city clean and crowd pleaser.

necessary to construct flood prevention system inaccordance with design standards by undertaking river
rehabilitation.
(2) Water pollution:
Presently, the areas adjoining Amanishah Nallah lack asound wastewater management network. This wastewater
is generated by the human habitation alongside the river,includinghotels/commercial
establishments.
Industrialization process in the city and the surroundings
impact and deteriorate the water seriously. Amanishah
Nallah carries dirty stinking water, which fosters thegrowth of mosquitoes which is severe health and sanitaryrisks for the locals. In addition, the direct polluted waterused for irrigation or infiltration of polluted water into
the ground increases water pollution risks, leading to apotential health risk to agricultural products.
(3) Water resource:
Jaipur is facing serious water resource shortage. Being insemi-arid climate zone, Jaipur experiences an averageannual rainfall of 650 mm, with 90% rainfalls duringJun.-Sep. The rains fail to supplement the ground water
sufficiently. At the same time, water deterioration,shortage of water management infrastructure and rapid
increase in population, aggravate this phenomenon.
Therefore, we have to consider effective rainwater
preservation/conservation measures to address the
problem of water shortage. Further, the polluted water of
the Nallah is being used for agriculture and thereby
leading to health hazards with the production of toxicinfected food grains/vegetables.
(4) Ecology
Limited green spaces, disorderly constructions,
encroachments and unauthorized industrialization along
the Nallah have damaged the ecology. The water and soil
erosion in the upstream is serious. Drainage of polluted
water with domestic and industrial garbage is being
dumped in Nallah. All of this has adversely affected theecology along Amanishah Nallah which is does notcomplement the development plans of Jaipur.
(5) Value Creation and Economic Boost
Water is lifeline of any city’s economic growth anddevelopment. Development of Amanishah Nallah will forsure add a significant factor to accelerate the businessactivities around some of the most valuable pockets of
the Jaipur. While in current state Amanishah Nallah andits surrounding land have diminishing value due toadverse conditions. It is expected that this project will

2. KEY ISSUES
To rejuvenate back it into the cleaner, clearer,odorless flowing water which will be suitable forsurvival of aqua life and in creation of river front with
better aesthetic surrounding, the following key issues
should be resolved.
(1) Flood Problem: Amanishah Nallah is the main drainage channel in thecity of Jaipur, which suffers from Serious water and soil erosion on the hills in
Upstream area
 lllegal construction of building alongside theriver occupying the river bed swathes.
 Growing of vegetables and commercial crop on
the riverbed with polluted water.
 Unchecked use of the Banks and the Bed of thewater channel as garbage dumps.
The above issues severely restrict the drainage capacityof river channel, making the area susceptible to floods,
and thus threatening the safety of life and assets. Further,
rapid urbanization increases hardened ground andreduces agricultural land which damages naturaldrainage mode. Moreover, in the rapid process ofurbanization, the construction of drainage system inJaipur now adding to the risks of floods. It has become

19017th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 18
give a significant fillip to the business activities around
Nallah, starting with sky rocketing of the price of landholdings around Nallah. It is expected that this valueenhancement will be multiple time of the proposed costof the Nallah development work.
3. REJUVENATE OF NALLAH
To rejuvenate back it into its earlier form,
construction of sewage treatment plant have been takenplace at 5 different strategic Locations with advancetreatment techniques like Sequential batch reactors,
vortex grit chambers, turbo blowers etc. The present
sewage that is being generated and joining the river iscollected through underground pipes on the both banks.
The collected sewage is taken to the sewage treatment
plants totalling to 170MLD and the treated water isdischarged into the river for the continual flow. After aproper examination of the flow and the length of the flow,
Amanishah Nallah is dissect into 13 reaches
Figure 2: Present Photos
4. CONCLUSIONThe river rejuvenation has been designed todeliver value to the Pink city, Jaipur in multiple
forms by Creating clean river front, recharging
ground water, increasing green cover, creating
community spaces, providing clean air to breath,adding beauty to the urban landscape.
Increasing the economy by attracting tourists.
As this project is one of its kind in India, Projectexperience center was built to understand the
project profoundly

5. REFERENCES[1] CPHEEO Manual[2] Waste water engineering reference manual Latest
Manual by Metcalfe and Eddy by McGraw hill
[3] Water and waste water handbook of Degremont[4] Manual on Sewage and Sewage treatment, MoUD,CHPEEO and Jica – November 2013
[5] Central Pollution Control Board (CPCB) Manual[6] CWC Manual on flood

Figure 1: Maps Showing Amanishah Nallah Path
(Source: Google Maps)

Table 1: Showing Reach locations.

191

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 71

A STUDY ON THE ASSESSMENT OF DAMAGE LEVELDURING LARGE SCALE EARTHQUAKE DISASTER USING KDB DATABASE
Yuma MORISAKI1, Makoto FUJIU2, Junichi TAKAYAMA3, Kiyoko YANAGIHARA4, Tatsuya NISHINO5,
Masahiko SAGAE6, and Kohei HIRAKO7
1

Bachelor(Eng.), Kanazawa University, Department of Environmental Design, Japan, yki20@stu.kanazawa-u.ac.jp
Ph.D., Assistant Professor, Kanazawa University, Department of Geosciences and Civil Engineering, Japan,
fujiu@se.kanazawa-u.ac.jp (corresponding author)
3Dr., Eng., Professor, Kanazawa University, Department of Geosciences and Civil Engineering, Japan,
takayama@se.kanazawa-u.ac.jp
4
Ph.D., Associate Professor, Kanazawa University, Department of Pharmaceutical and Health Sciences, Japan,
kyana@mhs.mp.kanazawa-u.ac.jp
5Ph.D., Associate Professor, Kanazawa University, Department of Geosciences and Civil Engineering, Japan,
tan378@se.kanazawa-u.ac.jp
6Ph.D., Professor, Kanazawa University, Department of Huma and Social Science, Japan, sagae.masahiko@gmail.com
7
Bachelor., Project Assistant Professor , Kanazawa University, Organization of Frontier Science and Innovation, Japan,
hirako@staff.kanazawa-u.ac.jp
2

Keywords: large scale earthquake disaster, damage assessment, KDB database vulnerability, vulnerable people
1. INTRODUCTION
In recent years, large-scale earthquake disaster such as
The 2011 off the Pacific coast of Tohoku Earthquake and
The 2016 Kumamoto Earthquake frequently occur inJapan. An earthquake with magnitude 6.7 and maximum
seismic intensity (JMA) 7 occurred in middle easternpart of the iburi district of Hokkaido on September 6th,
2018, at 03:07(JST) [1]. This earthquake was named
Hokkaido earthquake, 2018. As of 13:30 on September
13th, 2018, the number of dead and serious injury were
41 and 9[1]. The issue during large scale earthquake is
respond to vulnerable people. They need care after
earthquake disaster, such as rescue and evacuation.
Specifically, aged person, injured person, pregnant
person, infants and foreigner are considered vulnerable
people. In Japan, establishing a support system forvulnerable people for large scale disaster is an urgent
problem.
In order to achieve the establishment of support
system for vulnerable people, it is important to examine
the degree of weakness (Vulnerability) to the disaster. A
lot of studies are being conducted about examination ofvulnerability [2], [3], [4], [5]. Fujiu et al [6] examined acomprehensive index on the vulnerability of the area
integrating vulnerability of people and structures. In
addition, Evaluation of disaster was conducted using thefollowing equation (1) which is generally known as
being able to examine quantitatively the disaster situation.

:::

Hakui City

0

62.5

125

250 kmFigure.1 Location of Hakui-City, Ishikawa Prefecture【ANALYSIS PROCEDURE】

Step.1

By managed data,setting of analysis
target person andcalculate by timeseries.

•Setting of analysis
target person

Step.2

Examination of
hazardStep.3Futureprediction ofvulnerability(1)

Step.4
Examination
damage levelconsidering
time series

It is generally impossible to control the external force(Hazard) of disaster, and it is necessary to examine andcontrol vulnerability in order to minimize disaster.

•

Examination how muchhazard is assumed forset disaster•

Evaluation ofvulnerability by timeseries using
Autoregressive Model•【DATA】•

National census（Examine infants,
foreigner, aged
person）•

National healthinsurance data
(Examine injured
person by attribute)••

J-SHIS Japan
seismic Hazard
Information station

Statistical analysis
free software 「R」

From the formula of D = H · V, examine thedamage level considering time series

Figure.2 Analysis procedure of this study192

17th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia
12-14 December 2018, IIIT Hyderabad__________________________________________________________________________________________
Paper No. 71

Table.1 Example of KDB data
氏名

性別

年齢

生年月日 住所

直近月レセプトの決定点数 糖尿病
164,273
95,0772,670
50,380 ●39,082
96,060 ●Decision165,185 ●
36,449 ●points of the
43,096 ●reception42,956 ●

高血圧症 高尿酸血症虚血性心疾患
インスリン療法
糖尿病性神経障害
糖尿病性網膜症
動脈閉塞性疾患
脳血管疾患個人番号
●
7747
●
7747
●
7747
●
●
●
●
●
853
●
●
7764
●
●
1434
●
●
●
●
●
1435
●
1435
●
●
●
1738
●
●
2126

Human vulnerability and physical vulnerability aremainly considered as vulnerability. As mentioned above,
recent disasters, vulnerable people suffered huge damage.
Therefore, the purpose of this study is to examine thehuman vulnerability and to estimate the future of humanvulnerability considering large-scale earthquake disaster.
By estimating human vulnerability, it is possible tosimultaneously estimate the disaster situation, and it isalso possible to examine detailed disaster situationconsidering time series data.

study, after evaluating future human vulnerability, wequantify the resilience having the opposite meaning to
the human "vulnerability". After that, we would like toevaluate the region from two points of vulnerability andresilience. Moreover, Questionnaire survey is conductedto collect qualitative data for evaluation of resilience andfuture vulnerability.

Personal
attributes

住所

Chronic illness, none

Personal
number

REFERENCES[1] Ministry of Land, Infrastructure and Transport, JMA,
“https://www.jma.go.jp/jma/menu/20180906_iburi_jishin_menu.html”[2] Kunihiro AMAKUNI, Takahisa ENOMOTO, andToshio MOCHIZUKI, (1999) “Research on Evaluation
Methods for Vulnerability and Defense against
Earthquake Disaster ―A Case Study of Aomori
Prefecture―” Journal of social safety science, Vol.1,
pp.179–188[3] Zi YANG, Keiko INAGAKI, Satoshi YOSHIDA, andSatoru SADOHARA, (2015) “Regional Characteristics
Analysis from the View of Community- Based Disaster
Risk Management for People with Functional Needs inTimes of Disaster” Journal of social safety science,
Vol.27, pp.145–154[4] Makoto KOSUGI, Kenshi BABA, and Mitsuru
TANAKA, (2017) “Resilience Index of Regional
Communities to the Risks of Disasters―Comparison ofEight Regions through Questionnaire Survey Data―”
Environmental science, Vol.30, No. 3, pp.225–237[5] Miwa ABE, Arinori YOSANO, (2013) “Social
Vulnerability Analysis of Households in Kita ward,
Osaka: Elucidating the Relationship between Residence
Height and Elderly Demographics”
http://hdl.handle.e.net/10112/7748[6] Makoto FUJIU, Yuma MORISAKI, Junichi
TAKAYAMA, Kiyoko YANAGIHARA, Tatsuya
NISHINO, Masahiko SAGAE, Kohei HIRAKO, (2018)“Evaluation of Regional Vulnerability to Disasters byPeople of Ishikawa, Japan: A cross Sectional Study
Using National Health Insurance Data” Int. J. Environ.
Res. Public Health, Vol.15, No. 3, 507

2. ANALYSIS PROCEDURE OF THIS STUDYFirst, Hakui-City, Ishikawa Prefecture was set analysis
field in this study. Hakui-City is a small city facing the
Sea of Japan. Fig.1 shows location of Hakui-City,
Ishikawa Prefecture. The analysis procedure of this study
is as shown in Fig.2. Vulnerable people area examine
using data on “population”. As mentioned above, aged
person, injured person, pregnant, infants, and foreigner
are considered vulnerable people. In this study, aged
person, injured person, infants and foreigner is examinedusing national census. This census is large-scale survey
focused according to attribution. In addition, this census
is conducted every 5years. Injured person is examinedusing national health insurance data (KDB data). As
shown in Table.1, KDB data can be comprehensively
examined injured person. Those who have chronic renal
failure, brain disease and cardiac disease are included asvulnerable people. By using national census, it is
impossible to examine detailed injured person. However,by using national health insurance data, injured person
can be examined. Both data have huge amount of
information. National census is conducted every 5years
from 1920, and national health insurance data has
information since 2013 every 1 month. Therefore, using
both data, vulnerable people can be examinedconsidering time series data. Then, regarding degree of
earthquake disaster (Hazard) by analysis target field, JSHIS (Japan Seismic Hazard Information Station) is used.
After that, future human vulnerability is estimated using
Autoregressive Model. By evaluating future humanvulnerability considering aged person, infants, injured
person and foreigner using Autoregressive model, it issimultaneously possible to estimate future degree ofdisaster.
3. CONCLUSIONS AND FUTURE WORKS
This study is to estimated future human vulnerability oflarge-scale disasters by using census and national healthinsurance data in time series. As a future work of this193