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International Journal of Advanced Technology and Engineering Exploration, Vol 9(86)
ISSN (Print): 2394-5443 ISSN (Online): 2394-7454
Seismic vulnerability assessment of buildings of Patna by rapid visual
Siddharth1* and Ajay Kumar Sinha2
PhD. Research Scholar, Department of Civil Engineering, National Institute of Technology, Patna, India1
Professor, Department of Civil Engineering, National Institute of Technology, Patna, India2
Received: 07-September-2021; Revised: 23-January-2022; Accepted: 25-January-2022
©2022 Siddharth and Ajay Kumar Sinha. This is an open access article distributed under the Creative Commons Attribution (CC
BY) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is
properly cited.
The seismic vulnerability of any structure is its
inability to withstand future earthquakes [1, 2].
Severe damages to the structure have occurred due to
past earthquakes, resulting in loss of life and money.
Buildings constructed in India before implementing
seismic codes are most vulnerable and have resulted
in a significant loss. India is a country that is very
seismically active due to its location and
demography. Around 80% population of India lives
in earthquake-prone seismic zones [3]. Bhuj
earthquake occurred in 2001, which resulted in the
collapse of reinforced concrete buildings in Bhuj and
Gandhidham [4, 5]. The earthquake in Kashmir in
2005 resulted in damage to stone masonry buildings
[6]. The occurrence of the Sikkim earthquake in the
year 2011 resulted in the deterioration of non-
engineered reinforced concrete buildings [7]. So,
because of these failures, a seismic vulnerability
assessment needs to be done. Seismic vulnerability
assessment is the process of evaluation to find out the
deficiencies of the structure.
*Author for correspondence
Much research has been done on seismic
vulnerability assessment methods by various
scientists around the world [8]. The casualty and
magnitude during occurred earthquakes are shown in
Figure 1 and Figure 2 respectively. The Seismic
vulnerability assessment is a three-step process in
different codes namely, (1) Rapid visual screening
(RVS) (2) Preliminary assessment method or
simplified assessment (3) Detailed assessment
Rapid visual screening (RVS)
This is a fast method of assessment. The screening is
usually done within 10-15 methods. In this, various
parameter is taken into account as per the RVS
forms. Trained surveyors carry out the RVS process.
The main aim of this procedure is to rank buildings
and also to filter out which buildings need further
evaluation. In this method grading is usually done.
Preliminary assessment method or simplified
In this method models of buildings are drawn along
with layout of columns and beams. This method
includes various type of strength checks and in-depth
evaluations of buildings are done.
Research Article
Many damaging earthquakes have occurred in various regions of India in past few decades. It has affected large scale
loss to life and property. The city of Patna is located in seismic Zone IV, according to IS1893 making it substantially
vulnerable to earthquake. Such areas need proper study to decide preventive measures for avoiding any probable disaster.
Seismic vulnerability is one of the most crucial parameters for structural safety assessment. According to most of the
guidelines used worldwide, a three-stage process of evaluation is generally adopted. The first level of evaluation is rapid
visual screening (RVS). This paper summarizes the RVS carried out in 201 buildings of Patna. The buildings have been
ranked according to the number of storeys, grade of damage, and year built. The study shows poor maintenance history of
buildings. Also, the buildings were found to be constructed not as per codal provisions. The result shows the need for
retrofitting of buildings after further study.
Seismic vulnerability, Rapid visual screening, Damageability, Non-engineered buildings.
Siddharth and Ajay Kumar Sinha
Figure 1 Death reported in India due to significant earthquakes
(Source: Indian Meteorological Department)
Figure 2 Magnitude of earthquakes in India
(Source: Indian Meteorological Department)
Detailed Evaluation
This is the third phase of evaluation. It requires linear
or nonlinear analyses of the building based on as-
built dimensions. This phase involves calculation of
moments and flexural capacity of buildings. Also,
storey drift calculation is done. The flowchart for the
three-step assessment procedure is shown in Figure
3. The main objective of current work is to find out
the current vulnerability status of buildings of this
area and identify which building needs further
evaluation. The motivation behind the correct work is
the number of damages due to recurring earthquakes
in this city in past 100 odd years and how to reduce
it. The limitation of the current study is RVS of
selected buildings of Patna.
2000 414 0 1500 0 0
10653 1530 1004 768
0 8790
No. of deaths reported
Casualities reported during occured earthquakes
8 7.7 7.4 8.1 7.6 7.1 8.2 8.7
6.6 6.4
7.7 7.6 6.8 7.8
Intensity of earthquakes,Mw
Magnitude of major earthquakes
International Journal of Advanced Technology and Engineering Exploration, Vol 9(86)
Figure 3 Flow chart of vulnerability assessment process
2.Literature review
Mulas et al. [9] studied vulnerability of torsionally
deformable reinforced concrete buildings of Italy. In
this study it was found that buildings were not built
as per seismic provision. The advantages of different
retrofitting methods were concluded.
Haryanto et al. [10] conducted RVS of buildings in
Indonesia. The conclusion from the study is that a
safety policy of educational buildings needs to be
made and the vulnerable buildings can be retrofitted.
Ruggieri et al. [11] did study on priority of most
vulnerable school buildings and proposed a
methodology for assessment of buildings. The result
showed that the proposed methodology can be used
for vulnerability assessment efficiently.
Reddy et al. [12] did study the risk vulnerability of
Chennai. A total number of 100 buildings from
Chennai were surveyed. Pushover analysis was done
on selected buildings. After the analysis, it was
concluded that detailed study for the city needs to be
Parmar et al. [13] did vulnerability assessment of
buildings of Surat. In the study RVS of 690 buildings
were done It was concluded that almost 80 %
buildings were in good condition.
Calvi et al. [14] did review of various methodology
proposed in past 30 years. In the study it was
emphasized that for assessment of vulnerability in a
loss model, the main parameter is sound algorithm.
Ramly et al. [15] conducted a RVS of 1166 number
of buildings in Pahang, Malaysia. Out of which 308
number of buildings required detailed investigation.
Sarraz et al. [16] conducted RVS of 310 number of
buildings in Chandgaon, Bangladesh. In this study
the vulnerability was compared with the performance
score of the buildings. It was concluded that the
vulnerable buildings need to be repaired and restored.
Modi and Mohan [17] conducted RVS of 100 number
of reinforced concrete buildings in Rambaug,
Ahmedabad, after the Bhuj earthquake. In this study,
it was concluded that 88 % of the building had a soft
storey, 55 % of the building had heavy overhangs,
and 48% had vertical irregularity.
Siddharth and Ajay Kumar Sinha
Sadat et al. [18] studied 2007 number of buildings in
the Dhanmondi, Lalmatia, and Mohammadpur areas
of Dhaka. Out of which 1082 buildings were RCC,
and 975 numbers of the building were unreinforced
masonry buildings. Total 476 buildings out of 1082
buildings had a soft storey. It was concluded that the
majority of buildings did not follow codal provisions
and had no proper emergency exit.
Joshi and Kumar [19] conducted RVS of 3339
number of buildings in Mussoorie, Uttarakhand. Out
of which, around 20% of buildings (623 buildings)
were having grade 5 damage (G5) and grade 4 (G4)
damage. Also, about 19% of buildings (587
buildings) were having grade 4 (G4) damage and
grade 3 (G3) damage.
Dutta et al. [20] did a damage assessment of
buildings after the 2015 Gorkha earthquake. In this
study, it was decided to judge the earthquake
preparedness of buildings in the city of Patna. It was
concluded that many buildings need retrofitting
measures, especially for non-engineered buildings.
Sarmah and Das [21] conducted RVS of 100 number
of buildings of Guwahati. The buildings were
categorized according to nine different parameters.
The study provided details according to which
retrofitting and replacement may be decided further
by municipal authorities of Guwahati.
Rautela et al. [22] conducted a RVS of 6206 numbers
of buildings in Mussoorie and Nainital town of
Uttarakhand. In this study, it was concluded 14% of
buildings of Nainital and 18 % of buildings of
Mussoorie are of Grade 5(G5) damage category.
These buildings are hospital and lifeline buildings
that might be vulnerable in case of significant
Shakya et al. [23] did damage assessment of
buildings of Bhaktapur city of Nepal after the 2015
Gorkha earthquake. In this study, the main causes of
building damage during the earthquake were
described. Also the remedial measures after
earthquake destruction were recommended.
Aldemir et al. [24] studied about the seismic risk
assessment of buildings. In this study, a method was
developed for the risk assessment of unreinforced
Halder et al. [25] studied about damage of existing
buildings in North East. The result with the help of
fragility curve shows the unreinforced masonry
(URM) building present are most vulnerable ones and
detailed study is required for more accurate results
[26]. From the literature review it is clear that older
buildings are deficient and hence require further
detailed evaluation. After the evaluation of buildings,
retrofitting needs to be done.
3.1RVS procedure
The RVS procedure followed in this research work
includes the following is shown in Figure 4. Firstly,
the data collection form is selected from existing
RVS methods. Then the area to be screened is chosen
and the secondary data such as soil data, plan etc. are
collected. A team of surveyors is formed. They are
trained and sent to field for data collection. The
primary data of the survey includes the sketch of the
building, no of storeys, plan irregularity, vertical
irregularity and photographs of the buildings etc.
Thereafter the collected data are stored in computer
and analysed.
Figure 4 Flowchart for the RVS procedure
International Journal of Advanced Technology and Engineering Exploration, Vol 9(86)
3.2Overview of the study area
The study was conducted in the city of Patna. Few
localities of Patna such as Bailey Road, Circular
Road, Deshratna Marg, Mangles Road, Polo Road,
Shastri Nagar, Strand Road, and Taylor Road were
selected for the survey work. The city of Patna lies in
seismic zone IV according to the classification of IS
1893: 2016. Patna is the capital city of Bihar, which
lies on the Indo-Nepal border. Bihar is located in
high seismic zones due to its location on a tectonic
plate in the Himalayas. Bihar has total no of 38
districts, out of which 8 district lies in Zone V and 24
district lies in zone IV. The state of Bihar has
witnessed major earthquakes in the year 1833, 1934
and 1988 with loss of life and money [27, 28]. The
typology of surveyed buildings are unreinforced
masonry buildings. Figure 5 is the location of study
area taken from the google map of Patna and roads
surveyed are highlighted in yellow.
3.3Data collection
Primary data was collected through RVS by field
visit and secondary data was collected from junior
engineers of building construction department,
Goverment of Bihar, Patna. RVS survey sheet as
developed in IS13935:2009[29] was used (Appendix
II). The RVS Survey sheet is an empirical method of
assessment. The details of locality of buildings are
tabulated in Table 1. Figure 6, Figure 7, Figure 8,
Figure 9 and Figure 10 are different photographs of
building no.-1, Deshratna Marg. This building used
to be the residence of Late Karpoori Thakur, former
chief minister of Bihar and currently used as
Figure 6 is the front view of the building. Figure 7
shows spalling in ceiling inside the buildings. These
are most common problems in URM buildings.
Figure 8 shows the dampness on the walls of the
buildings. This may have deteriorating effects on the
strength of the buildings. Figure 9 represents walls
with plaster damage. Figure 10 shows corrosion of
reinforcement of roofs.
Figure 5 Location of study area (Highlighted in yellow)
Siddharth and Ajay Kumar Sinha
Table 1 List of surveyed buildings
Name of the locality
Quaters of Bailey Road
Quarters of Circular Road
Quarters of Deshratna Marg
Quarters of Mangles Road
Quarters of Polo Road
Quarters of Shastri Nagar
Quarters of Strand Road
Quarters of Taylor Road
Figure 6 Front view of main buildings of 1, Desh Ratna Marg (Residence of Late CM Karpoori Thakur)
Figure 7 Spalling in ceiling
Figure 8 Dampness on walls
International Journal of Advanced Technology and Engineering Exploration, Vol 9(86)
Figure 9 Deterioration of walls
Figure 10 Corrosion reinforcement of the ceiling
3.4Factors affecting the damageability of
Irregularity in plan as well as elevation could leads
to higher grade of damageability.
Fire exits provided in the buildings were checked.
Spalling and dampness were checked which had
influence on damage grades.
Corrosion of reinforcement
In this research study damages in buildings were hair
line cracks, major cracks and spalling of plasters for
different grades of damage. There was dampness in
building as well as cracks at roof and lintel level. The
buildings were checked for irregularities. The results
of the current study are classified based upon
damageability, height of the building and age of the
Damageability grades
A total number of 201 buildings were surveyed and
the damageability grades for each of buildings were
found out using the RVS forms. Survey form as per
IS 13935:2019 were used for the classification of
grades. All the surveyed buildings were masonry type
buildings. The Table 2 below shows the grades of
different buildings
Table 2 Buildings in different damage grade
Grade of damageability
Grade 1
Grade 2
Grade 3
Grade 4
Grade 5
The Figure 11 shows the pie chart for comparison
between damageability grade and percentage no of
buildings. The percentage of grade 3 buildings were
more than grade 4 damage buildings. Also, there
were no grade 1damage buildings. The Table 3
shows the classification of surveyed buildings based
upon the height of the buildings. The height of the
building also affects the vulnerability of building.
The Figure 12 shows the pie chart for comparison
between storey height and percentage no of
buildings. The percentage of surveyed buildings
having height >1 was more than single story building.
Also, there were few buildings of single storey.
Table 3 Storey height of the surveyed buildings
Height of the buildings
The Figure 12 shows the pie chart for comparison
between storey height and percentage no of
buildings. The percentage of surveyed buildings
having height >1 was more than single story building.
Also, there were few buildings of single storey. The
Table 4 shows the classification of surveyed
buildings based upon the age of the buildings. The
age of the building also affects the vulnerability of
building. The topology of surveyed building which
were built in between 1927 and 1950 were made of
lime mortar and roof were flat roof. Also, some roofs
were made of timber which had impact on the
condition of building. The Figure 13 shows the pie
chart for comparison between age of building and
percentage no. of buildings.
Siddharth and Ajay Kumar Sinha
The percentage of surveyed buildings built between
1927 and 2000.The building where not complaint to
current Indian standard code and hence are more
vulnerable to seismic hazards.
A complete list of abbreviations is shown in
Appendix I.
Figure 11 Pie chart of classification based upon damageability grade
Figure 12 Pie chart of classification based upon Height of building
Grade 1, 0% Grade 2, 0.50%
Grade 3, 75.60%
Grade 4, 22.90%
Damageability grade vs. % no. of buildings
G, 11%
G+1, 23.00%
G+2, 66.00%
Height of buildings vs. % no. of buildings
International Journal of Advanced Technology and Engineering Exploration, Vol 9(86)
Table 4 Buildings in different damage grade
Year built
Figure 13 Classification of building based on Age of
The vulnerability of existing buildings depends upon
the maintenance history, provision of fire exits and
implementation of codal provisions. The existing
URM buildings in the current research work are
vulnerable due to above factors. The scope of the
current research is limited to RVS of 201 number of
buildings located in Bailey Road, Circular Road,
Deshratna Marg, Mangles Road, Polo Road, Shastri
Nagar, Strand Road, and Taylor Road of Patna. The
surveyed buildings had no fire exits which may prove
to be fatal during fire hazards. Also, higher damage
grade 4 and grade 5 are due to age of buildings and
poor maintenance conditions. There were buildings
having timber roof which may be vulnerable due to
decay in course of time. There was corrosion in
reinforcement in roofs of few buildings which may
be disastrous for occupants in case of failure. The
result of current work will pave way for decision to
be taken for further study and action to be taken
6.Conclusion and future work
During RVS survey it was observed that 11.4% of
buildings have a ground floor, 22.9% of buildings are
G+1, and 65.7% of buildings are G+2. The majority
of buildings surveyed are built between 1927 and
2000. Most of buildings had spalling and dampness
in walls. Vegetation growth in and around the
structure was seen which may have impact on
vulnerability. Also, there were many visible vertical
and diagonal cracks in the buildings. These factors
had impact of damage grades. From the study it has
been found that 1% of buildings are Grade 5, 23% of
buildings are Grade 4, 75.6% of buildings are Grade
3 and 0.04% of buildings are Grade 2. In future,
further detailed study of Grade 4 and Grade 5
buildings needs to be done after which retrofitting
measures can be decided.
Conflicts of interest
The authors have no conflicts of interest to declare.
Authors contribution statement
Siddharth: Conceptualization, data collection, analysis,
writing- review and editing. Ajay Kumar Sinha: Writing-
original draft, analysis and interpretation of results.
[1] Cockburn G, Tesfamariam S. Earthquake disaster risk
index for Canadian cities using bayesian belief
networks. Georisk: Assessment and Management of
Risk for Engineered Systems and Geohazards. 2012;
[2] Hill M, Rossetto T. Comparison of building damage
scales and damage descriptions for use in earthquake
loss modelling in Europe. Bulletin of Earthquake
Engineering. 2008; 6(2):335-65.
[3] Kumar RP, Murty CV. Earthquake safety of houses in
India: understanding the bottlenecks in
implementation. Indian Concrete Journal. 2014.
[4] Accessed 05
September 2021.
[5] CVR RMM, Goel RK, Goyal A, Jain SK, Sinha R,
Durgesh CR, et al. Reinforced concrete structures.
Earthquake Spectra. 2002; 18(S1):14986.
[6] Naeem A, Ali Q, Javed M, Hussain Z, Naseer A, Ali
SM, et al. First report on the Kashmir earthquake of
October 8, 2005. EERI Special Earthquake Report.
[7] Murty CV, Raghukanth ST, Menon A, Goswami R,
Vijayanarayanan AR, Gandhi SR, et al. The Mw 6.9
sikkim-nepal border earthquake of September 18,
2011. EERI Newsletter, EERI Special Earthquake
Report. 2012:1-4.
Siddharth and Ajay Kumar Sinha
[8] Rai DC. Review of documents on seismic evaluation
of existing buildings. Department of Civil
Engineering, Indian Institute of Technology Kanpur
India. 2005.
[9] Mulas MG, Stroffolini L, Martinelli P. Vulnerability
and retrofitting of torsionally deformable RC
buildings: a case study. In structures 2021 (pp. 861-
75). Elsevier.
[10] Haryanto Y, Hu HT, Han AL, Hidayat BA,
Widyaningrum A, Yulianita PE. Seismic vulnerability
assessment using rapid visual screening: case study of
educational facility buildings of jenderal soedirman
University, Indonesia. Civil Engineering Dimension.
2020; 22(1):13-21.
[11] Ruggieri S, Perrone D, Leone M, Uva G, Aiello MA.
A prioritization RVS methodology for the seismic risk
assessment of RC school buildings. International
Journal of Disaster Risk Reduction. 2020; 51:101807.
[12] Reddy MD, Jeyashree TM, Reddy CD. A case study
on vulnerability risk assessment of buildings in
chennai using rapid visual screening. Annals of the
Romanian Society for Cell Biology. 2021:2183-92.
[13] Parmar A, Patel VM, Singh AP. Seismic vulnerability
assessment of buildings in surat City of western India.
International Journal of Innovative Technology and
Exploring Engineering (IJITEE). 2019; 8(10):719-23.
[14] Calvi GM, Pinho R, Magenes G, Bommer JJ,
Restrepo-vélez LF, Crowley H. Development of
seismic vulnerability assessment methodologies over
the past 30 years. ISET Journal of Earthquake
Technology. 2006; 43(3):75-104.
[15] Ramly N, Ghafar M, Alel M, Adnan A. Rapid visual
screening method for seismic vulnerability assessment
of existing buildings in Bukit Tinggi, Pahang,
Malaysia. In international conference on advances in
Civil, structural and mechanical engineering,
birmingham 2014.
[16] Sarraz A, Ali MK, Das DC. Seismic vulnerability
assessment of existing building stocks at Chandgaon
in Chittagong city, Bangladesh. American Journal of
Civil Engineering. 2015; 3(1):1-8.
[17] Modi R, Mohan K. Rapid visual screening of RC
frame buildings in 2001 Bhuj earthquake affected
Rambaug area of Ahmedabad, Gujarat. Editorial
Office. 2019; 23(2):143-51.
[18] Sadat MR, Huq MS, Ansary MA. Seismic
vulnerability assessment of buildings of Dhaka city.
Journal of Civil Engineering. 2010; 38(2):159-72.
[19] Joshi GC, Kumar R. Preliminary seismic vulnerability
assessment of Mussoorie town, Uttarakhand (India).
Journal of Building Appraisal. 2010; 5(4):357-68.
[20] Dutta SC, Nayak S, Acharjee G, Panda SK, Das PK.
Gorkha (Nepal) earthquake of April 25, 2015: actual
damage, retrofitting measures and prediction by RVS
for a few typical structures. Soil Dynamics and
Earthquake Engineering. 2016; 89:171-84.
[21] Sarmah T, Das S. Earthquake vulnerability assessment
for RCC buildings of Guwahati City using rapid visual
screening. Procedia Engineering. 2018; 212:214-21.
[22] Rautela P, Joshi GC, Bhaisora B, Dhyani C, Ghildiyal
S, Rawat A. Seismic vulnerability of nainital and
mussoorie, two major lesser himalayan tourist
destinations of India. International Journal of Disaster
Risk Reduction. 2015; 13:400-8.
[23] Shakya M, Kawan CK, Gaire AK, Duwal S. Post-
earthquake damage assessment of traditional masonry
buildings: a case study of Bhaktapur municipality
following 2015 Gorkha (Nepal) earthquake.
Engineering Failure Analysis. 2021; 123:105277.
[24] Aldemir A, Guvenir E, Sahmaran M. Rapid screening
method for the determination of regional risk
distribution of masonry structures. Structural Safety.
2020; 85:101959.
[25] Halder L, Dutta SC, Sharma RP. Damage study and
seismic vulnerability assessment of existing masonry
buildings in Northeast India. Journal of Building
Engineering. 2020; 29:101190.
[26] Sobaih ME, Nazif MA. A proposed methodology for
seismic risk evaluation of existing reinforced school
buildings. HBRC Journal. 2012; 8(3):204-11.
[27] Dasgupta S, Mukhopadhyay B. Historiography and
commentary from archives on the Kathmandu
(Nepal)India earthquake of 26 August 1833. Indian
Journal of History of Science. 2015; 50:491-513.
[28] Accessed
05 September 2021.
[29] Accessed
05 September 2021.
Siddharth has done his B.E in Civil
Engineering from RV College of
Engineering,Bengaluru.He completed
his M.E with specialization in
structural Engineering from BIT
Mesra.Presently he is pursuing his Ph.D
from NIT Patna He is a member of
earthquake safety clinic and centre at
NIT Patna. His research area includes Vulnerability
Assessment and Retrofitting of Buildings.
Ajay Kumar Sinha is presently
Professor, Civil Engineering
Department, National Institute of
Technology Patna. He has 35 years of
teaching and research experience. He
obtained his B.Tech degree from IIT
BHU in 1986, M.E. in Earthquake
Engineering from IIT Roorkee in 1989.
He completed his PhD from Delhi College of Engineering,
University of Delhi. His research interests include Seismic
resistant structures, Vulnerability Assessment and
Retrofitting of structures, Structural Health Monitoring,
Reliability Engineering. He is centre Director cum Nodal
Officer of Earthquake safety clinic and centre at NIT Patna.
He is a member of the Earthquake Committee of BSDMA,
GoB, Patna. He has published over 150 research Paper
International Journal of Advanced Technology and Engineering Exploration, Vol 9(86)
International journals and conferences. He has supervised 5
PhD and 55 ME students with 10 PhDs undergoing.
Appendix I
S. No.
Average Recurrent Interval
Unreinforced Masonry
Appendix II
The data collection form utilized for field survey (IS 13935:2009)
... However, it is still common to perform data-acquisition campaigns based on paper datasheets that are later transferred and managed on informatics platforms. Some examples of this approach are given in the Rapid Seismic Vulnerability Assessment developed by Nanda et al. [7], the survey form for masonry buildings of Guiliani [8], the model of the Bihar State Disaster Management Authority (India) [9] or the CARTIS datasheet for the typological characterisation towards seismic risk [10]. There are territorial-scale applications that have used similar approaches for assessing other types of vulnerabilities, such as the implementation performed by Salvati et al. [11] for assessing geo-hydrological hazards. ...
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The characterisation of the seismic vulnerability of historical constructions represents a complex problem in which the typological variability, the difficulty of performing reliable large-scale assessments and dealing with a large database all play a role. Nevertheless, reducing the uncertainty regarding the structural vulnerability of the existing building stock (mostly for small and/or isolated human settlements) is key for risk assessment and management. The present work proposes a novel approach based on the integration of a series of open-source tools for assembling a vulnerability-oriented database that is linked to a series of external services for increasing its capabilities. The database was implemented in a Geographical Information System (GIS) environment and contains the survey of a seismic vulnerability index for masonry constructions based on an adapted version of the GNDT-II approach. A customised Python-based software for reading, managing and editing the database is herein presented. This program allows the execution of the most typical operations with no assistance from the GIS environment, facilitating user interaction. Furthermore, the calculations regarding the vulnerability index and levels of damage have been implemented in this program. Alternatives for distributing the database are implemented and discussed, such as cloud-based distribution and the use of the Transactional Web Feature Service (WFS-T) protocol for its virtual publishing. The entire framework herein presented is a replicable and feasible workflow that can be set even with reduced infrastructure, allowing a progressive enlargement.
... For Japan, the form is based on seismic index (strength, ductility, and regularity) of structures and for Canada both structural parameters (stiffness and regularity) and nonstructural parameters (occupancy and falling hazard) of the structures are considered (Sarmah and Das, 2018). Many researches (Yakut et al., 2006;Gueguen et al., 2007;Martinelli et al., 2008;Jalayer et al., 2010;Kanti et al., 2013;Işık, 2016;Sarmah and Das, 2018 and Pradhan, 2020; Sinha, 2022) have developed rapid evaluation methods for risk assessment of structures. Sucuoglu et al. (2007) developed a simple screening method for three-to six-story insufficient reinforced concrete structures in Turkey. ...
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Turkey has experienced many casualties and property losses due to severe earthquakes in recent years. In these severe earthquakes, many RC structures collapsed due to insufficient materials, faults of engineering and workmanship. As a result of investigation of the structure stock, insufficient structures should be quickly determined. If necessary, the structures should be strengthened or demolished. Considering the size of the existing structure stock, this investigation takes a long time and is impossible economically. Therefore, rapid evaluation methods should be used and determined collapse risks of structures. Rapid evaluation methods such as Canadian Seismic Screening Method (NRC/ IRC 1992), P25 Method, FEMA 154, Japanese Seismic Index Method etc. are frequently used to determine the risk situations of RC structures. There are various forms to evaluate RC structures with these methods. For Japan, the form is based on seismic index (strength, ductility, and regularity) of structures and for Canada both structural parameters (stiffness and regularity) and nonstructural parameters (occupancy and falling hazard) of the structures are considered (Sarmah and Das, 2018). Many researches (Yakut et al., 2006; Gueguen et al., 2007; Martinelli et al., 2008; Jalayer et al., 2010; Kanti et al., 2013; Işık, 2016; Sarmah and Das, 2018; Jena and Pradhan, 2020; Sinha, 2022) have developed rapid evaluation methods for risk assessment of structures. Sucuoglu et al. (2007) developed a simple screening method for three- to six-story insufficient reinforced concrete structures in Turkey. The method was calibrated with field data collected after the 1999 Duzce Earthquake. The method assigns a cutoff score depending on the number of stories and the seismic, presence of soft stories, apparent quality and heavy overhangs. Risk situations of structures are classified in 4 group as none, light, moderate, collapse. Jain et al. (2010) developed a rapid visual screening method to determine risk situations of RC structures. The method is based on nine major parameters; soil condition; open storey; vertical irregularity; plan irregularity; torsion irregularity; heavy overhangs; apparent quality; insufficient gap with adjacent buildings and falling hazards. Alam et al. (2012) determined risk situations of existing RC structures by using rapid evaluation methods such as FEMA 154, Euro Code 8 (CEN 2004), New Zealand Guidelines (NZSEE 2000, 2003), Modified Turkish method and NRC/IRC (1992). A new Hybrid method was developed by combining the parameters of FEMA 310 (1998) and IITK-GSDMA (2007) methods and comparing with the existing methods. The authors concluded that the proposed method provided a more robust basis than other methods for the interpretation of vulnerability. Ningthoujam and Nanda (2018) carried out risk analyses of 396 structures damaged during the 4th January Manipur earthquake of 2016. As a results of analyses, it was concluded that the type of soil, apparent construction quality, maintenance condition, age of the buildings, substantial overhang and number of storey of the existing structures were considerably significant parameters in determining the vulnerability of the structure during an earthquake. Sonmezer et. al. (2018) developed a new method to evaluate structural performance of RC structure stock with rapid visual site screening. Authors stated that most crucial structural parameters were number of stories, soft storey, short column, heavy overhangs, pounding effect, topographic effect, visional quality and local soil condition. It was concluded that risk situations of RC structures could be safely determined with developed method. The purpose of this study is to develop a new rapid evaluation method to determine the risk situations of existing RC structures. Risk situations of 30 RC structures located in Manisa province of Turkey are determined by using NRC/IRC (1992), P25 Method, Principles for the Identification of Risky Structures (2013) (PIRS (2013)) and Turkish Seismic Code (TSC) methods. Significant parameters affected risk situations of the structures are investigated during these analyses. Then, a story plan, which reflects general properties of existing RC structure stock in Manisa and Turkey are selected. 22 RC structures having this story plan and different parameters such as concrete strength, steel strength, number of storey etc. are modeled. The risk analyses of these structures are executed with above 4 methods and the effectivenesses levels of these parameters are clearly revealed. In total, 52 RC structures are used in order to determine effectiveness levels of these parameters. Finally, a new, rapid and reliable method based on observation and analytical scoring is developed. Then, risk analyses of 53 existing RC structures are carried out by developed method, the results are compared with TSC.
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The seismic vulnerability assessment of critical facilities, such as hospital and school buildings, is of paramount importance to avoid the collapse in ordinary conditions and to guarantee their immediate functionality in the post-earthquake emergency. Due to the high number of school buildings, and to the need to perform the assessment in a short time, a simple methodology for ranking the more vulnerable buildings through a seismic risk index is highly desirable. In this study, a Rapid Visual Screening (RVS) methodology is proposed. The method aims to prioritize the buildings prone to higher seismic risk and to assist decision-makers in the implementation of seismic risk reduction strategies. The methodology allows to assess the seismic risk of reinforced concrete (RC) school buildings through the compilation of a factsheet. The main sources of structural and non-structural vulnerability are considered in the survey form. The influence of the hazard and exposure are also accounted for in the calculation of the safety index through simplified parameters. The proposed RVS method can be quickly applied to a large number of buildings to identify those that require more accurate analyses. The proposed methodology has been applied to a sample of typical school buildings in Apulian Region, Southern Italy. The results obtained using the proposed RVS method were compared with those of more advanced numerical analyses in order to assess its effectiveness.
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In Surat city, the second largest city of Gujarat, 6930 buildings had been rapidly screened (RVS). RVS is known as a sidewalk evaluation, in which a skilled screener inspect a structure visually in order to recognize characteristics that influence the building's seismic output, for example the construction type, seismic zones, soil, and irregularities, etc. This study of RVS is based on the checklists in a RCC and Masonry Performa. Other significant structure information, including building occupancy and possible structural risks, are also collected during the screening. A performance score of the structure is calculated based on RVS values that correspond to these characteristics. In comparison with a cuts-off rating, the structure rating determines if a construction has possible vulnerabilities to be evaluated by a skilled engineer. We applied the Gaussian distribution methodology for cut off score in this study. The Gaussian distribution is also commonly called the normal distribution. Though, there are varied constructions practices, 74% constructions are RCC and 26% masonry structures. The performance results of surveyed buildings show that about 80 percent of both structures have high quality because they have a performance rating > 60. The survey's results also indicate that buildings practice have been changed from masonry to RCC after 2001 Bhuj earthquake (M7.7). Due to design, RCC buildings will have more shear capacity to tolerate the seismic shaking in comparison to the masonry buildings.
India is witnessing drastic urbanization and economic growth which in turn helps in building its infrastructure rapidly. A large amount of construction of multistorey buildings has been done in many metropolitan cities, where one such city is Chennai, Tamil Nadu. In the recent scenario, being an unplanned and most densely populated city, there is a chance of an increase in threats to several natural hazards viz, earthquake, fire etc.This shifts our focus in understanding the risk associated with these hazards to ensure the safety of the structures. Many studies have been carried out to estimate the risk of the structure but are proven to be quite cumbersome. To counterpart, such complex methods, a simple approach namely Rapid Visual Screening (RVS) Method is used which is proven to be simple and reliable. Rapid visual screening has been widely used but the application of this method in India is limited. The present study helps in identifying the seismic risk associated with an area of interest in Chennai (Mylapore, Santhome, Triplicane) and elaborates its usability for other metropolitan cities. A total of 100 buildings of different housing typologies have been studied and its RVS score is calculated based on various building parameters. The pushover analysis is done for selected 5 buildings based on obtained RVS score and the results are used for further investigation. The RVS scores were correlated with the damage state curves and it is observed that buildings with RVS score greater than 120 are known to have no damage for a design earthquake with peak ground acceleration of 0.16 g.Finally, the risk assessment in terms of building damages during an earthquake is correlated based on its RVS score and push over curve.
The paper presents the seismic vulnerability assessment and the subsequent retrofitting strategies of a reinforced concrete (RC) strategic building in Italy. At time of design, the erection site was not classified as a seismic area. With a structural layout widely spread in non-seismic zones and for buildings designed with obsolete seismic codes, the framed system was designed for gravity loads only, with an eccentric lift core and moment-resisting frames aligned in one direction. The structural seismic capacity is impaired by torsional deformability and the possible appearance of both brittle collapse mechanisms and pounding phenomena with an adjacent building, while the seismic demand is governed by the classification of “strategic building”. Two retrofitting strategies are here analysed, under the constraints of eliminating the torsional deformability and minimizing the interruption of normal activities in the building. The results highlight the advantages and disadvantages of the two strategies and the most important features of the structural response, providing indications for further actions. The adoption of a design spectrum reduced by a 0.6 factor, roughly equivalent to that for an ordinary building, extends the relevance of the work well beyond the case study.
Bhaktapur municipality, one of the historic urban area, suffered heavy damage to many of its public residential buildings due to April 25, 2015, Gorkha (Nepal) earthquake. Immediately after this devastating earthquake, rapid visual damage assessment of 3979 buildings, in seventeen wards of Bhaktapur municipality, was carried out. This study was motivated to bring consciousness, revealing the vulnerable parameters of traditional masonry construction practice, for future safer buildings construction practice at this neighbourhood. Moreover, the establishment of 2105 Gorkha earthquake induced damage databases are undertaken, aiming to increase the availability of damage data for future research work. In this paper, the results obtained from comparative analysis of damage database and chi-square test for its validity is presented. Nevertheless, it is necessary to carry out detail damage assessment to identify the seismic sensitivity of the common structural components.
Earthquakes are natural phenomena occurring in various parts of the globe. Severe earthquakes caused substantial loss of life and property when nearly populated districts. Although some progress has been made in the area of seismic prediction, earthquakes in time, magnitude or location can not be estimated correctly. The primary method of reducing casualties is therefore to build seismic resistant structures. Current earthquakes show that the old houses, which are not intended to withstand earthquakes, have been harmed rather than the structures intended according to seismic regulations. Many current structures in Indonesia were intended only without seismic provisions to withstand the gravity loads. There is a need to study these buildings' vulnerability in order to prevent a severe danger. A Rapid Visual Screening (RVS) technique is conducted in this study to determine a Final Level 1 Score, SL1, for Jenderal Soedirman University, Indonesia’s educational facility buildings. In nine constructions situated in Purwokerto and Purbalingga, the method was implemented. Moreover, the final SL1 score is an estimate of the collapse probability if an earthquake occurs with ground motions called the maximum considered earthquake targeted risk, MCER. These score estimates are based on restricted observed and analytical information, thus the probability of collapse is therefore an approximation.
Seismic risk of buildings is of great concern to public administration, insurance companies and building inhabitants, as well as structural engineers. This study developed a method to estimate seismic risk to unreinforced masonry (URM) buildings based on the use of binary logistic regression on a large database of 543 URM buildings with detailed seismic assessment analysis. The proposed method considers number of stories, type of slab system, vertical irregularities, visual damage, type of masonry material, typical story height and typical plan area as basic estimation variables. These variables have been assigned to some penalty scores depending on the coefficients derived from the binary logistic regression analysis. In total, 443 buildings from the database were used to generate penalty scores, and 100 buildings were reserved for testing of the proposed method. The correct overall estimation rates of the proposed method for the database (443 buildings) and the test database (100 buildings) were determined as approximately 95% and 86%, respectively.
The Northeast region of India is considered to be the most seismically active zone in India, having witnessed two major earthquakes (Mw > 8) in the past. Recently, the 2017 Ambasa earthquake (with Mw of 5.7) caused significant damage to unreinforced masonry (URM) buildings in Tripura, a Northeast state of India. The typical nature of damage observed in URM buildings during the post-earthquake damage survey highlights poor construction practices that have been used in this region even though the seismic hazard of the Northeast region of India is well established. In this context, the present study is an effort to evaluate through fragility analysis the vulnerability of existing low-rise URM buildings in Agartala, the capital city of Tripura, which in a broader sense represents the buildings of the entire Northeast region of India, through fragility analysis. In this regard, an assessment method based on a nonlinear static approach is used to develop bilinear capacity curve parameters. The capacity curve parameters are then used to estimate fragility functions. Fragility analysis shows that URM buildings would suffer heavy damage even for an earthquake having Peak Ground Acceleration (PGA) of 0.18 g, which is used to design buildings in the Northeast region of India according to the Indian seismic code. Fragility curves developed in this study may prove useful for assessing the seismic risk of the same building typology in other urban areas of Northeast India. In this first attempt, however, the effect of variability from construction quality and modelling uncertainty on the fragility curves is not considered in the limited scope of the present study.