Damage study and seismic vulnerability assessment of existing masonry buildings in Northeast India

Journal Pre-proof Damage study and seismic vulnerability assessment of existing masonry buildings in Northeast India Lipika Halder, Sekhar Chandra Dutta, Richi Prasad Sharma PII:

S2352-7102(19)31517-7

DOI:

https://doi.org/10.1016/j.jobe.2020.101190

Reference:

JOBE 101190

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Journal of Building Engineering

Received Date: 7 August 2019 Revised Date:

12 January 2020

Accepted Date: 13 January 2020

Please cite this article as: L. Halder, S. Chandra Dutta, R.P. Sharma, Damage study and seismic vulnerability assessment of existing masonry buildings in Northeast India, Journal of Building Engineering (2020), doi: https://doi.org/10.1016/j.jobe.2020.101190. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier Ltd.

Damage Study and Seismic Vulnerability Assessment of Existing Masonry Buildings in Northeast India Lipika Halder1,a, Sekhar Chandra Duttab,*, Richi Prasad Sharma2,a a

Department of Civil Engineering, National Institute of Technology Agartala, Tripura -799046, India Department of Civil Engineering, IIT (ISM) Dhanbad, Jharkhand - 826004, India

b

Corresponding Author’s information: Prof. Sekhar Chandra Dutta, Ph.D., M.ASCE, M.EERI, FICE, FIE Professor, Department of Civil Engineering, Indian Institute of Technology (ISM) Dhanbad, Jharkhand - 826004, India, Mobile-+91-9430351812, E-mail: [email protected], [email protected] All Author’s information Author 1 Lipika Halder, M.E. Assistant Professor, Department of Civil Engineering, National Institute of Technology Agartala, Tripura -799046, India, Mobile: + 91 9436167076; E-mail: [email protected] Author 2 Sekhar Chandra Dutta, Ph.D., M.ASCE, M.EERI, FICE, FIE Professor, Department of Civil Engineering, Indian Institute of Technology (ISM) Dhanbad, Jharkhand - 826004, India, Mobile-+91-9430351812, E-mail: [email protected], [email protected] Author 3 Richi Prasad Sharma, Ph.D., M.ASCE Professor, Department of Civil Engineering, National Institute of Technology Agartala, Tripura -799046, India, Mobile: + 91 9436463474; E-mail addresses: [email protected]

Damage Study and Seismic Vulnerability Assessment of Existing Masonry Buildings in Northeast India Lipika Halder1,a, Sekhar Chandra Duttab,*, Richi Prasad Sharma2,a a

Department of Civil Engineering, National Institute of Technology Agartala, Tripura -799046, India Department of Civil Engineering, IIT (ISM) Dhanbad, Jharkhand - 826004, India

b

ABSTRACT 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 0.18g, 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.

Keywords: Unreinforced masonry; Low-rise building; Capacity curve; Damage grade; Fragility function. _________ *

Corresponding author. E-mail address: [email protected] (S. C. Dutta), Mobile: + 91 7894407830 E-mail addresses: [email protected] (L. Halder), [email protected] (R. P. Sharma) 1 Mobile: + 91 9436167076; Fax: + 91 381 2546360 2 Mobile: + 91 9436463474; Fax: + 91 381 2546360

1. Introduction The entire Himalayan range, more specifically, the Northeast region of India has the most complex tectonics in India and one of the most seismically dynamic zones in the world [1-3]. This region witnessed two great earthquakes with magnitude larger than 8, the 1897 Shillong earthquake (with

M

w

of 8.1) and the 1950 Assam earthquake (with

M

w

of 8.7) and

consequently, huge loss of human lives besides massive damage to property and infrastructure were reported elsewhere [4, 5]. Recently, this region experienced a strong earthquake, the 2016 Manipur earthquake (with

M

w

of 6.7) that caused significant damage to

reinforced concrete (RC) buildings in Imphal, Manipur [6, 7]. Furthermore, a moderate earthquake, the 2017 Ambasa earthquake (with

M

w

of 5.7) with PGA of 0.052g caused

considerable damage to unreinforced brick masonry (URM) buildings besides massive destruction in mud houses in Dhalai and Unakoti district of Tripura, a Northeast state of India. The lessons learnt from any seismic event gives an opportunity to re-examine the seismicity of the region, the prevailing construction practices, assess the risk of the built environment as well as to take corrective measures for improving the seismic response of the deficient buildings during future earthquakes. Hence, the typical nature of damages observed in URM buildings to the 2017 Ambasa earthquake is examined and discussed later for the sake of understanding. Masonry building constitutes a considerable part of building stock in Northeast India. These buildings are generally constructed in a traditional way without much engineering contribution. In most of the cases, earthquake-resistant features such as horizontal seismic bands at various levels and corner reinforcement are missing in such buildings. Furthermore, the construction process, quality control besides proper maintenance are governed by the financial backing of the owner, and the maximum people of this region belong to the lower economic bracket. Hence, these URM buildings seem to be very vulnerable to earthquake 1

excitation and to forecast damage scenarios for future earthquake, the performance evaluation is of great importance. Accordingly, the URM buildings in Agartala, the capital city of Tripura, which may in a broader sense be the representative buildings of the urban areas of the entire Northeast India are considered in this present study. Failure of the masonry building is caused by the out-of-plane failure of walls when the buildings are made up of flexible floors/roofs and without connections at the floor/roof levels [8, 9]. However, in the case of masonry buildings with rigid floors/roofs along with adequate load-bearing walls, the seismic failure mode is governed by the in-plane-failure of walls. In this context, a limited effort has been made to understand the seismic vulnerability of URM buildings with rigid floors/roofs, considering the in-plane behaviour of the buildings. Such an effort incorporates the understanding obtained through a nonlinear static approach followed by fragility analyses based on nonlinear deformation capacity. However, in the present limited scope of the study, the variability from construction quality and modelling uncertainty is not considered as the procedure adopted in this study is considered to be a satisfactory compromise between computational effort and accuracy in the result. As a further scope of the study, these issues are already being consideration. 2. Overview of the study area 2.1 Seismicity of Northeast India The Northeast region of India is situated at the junction of the Himalayan arc, which is convex to the south and the Burmese arc that is convex to the west. This region shows the highest level of seismicity due to collision among the Indian plate and the Eurasian plate within the north, and the underthrusting of the Indian plate below the Burma plate within the east [10, 11]. The major background tectonic features of the Northeast region such as Main Central Thrust (MCT), Main Boundary Thrust (MBT), Main Frontal Fault (MFF), Dauki Fault (DF), Kopili Fault (KF), etc. are shown in Fig. 1. The figure also shows earthquake

2

(M > 7.0) epicentres since 1897 along with the most recent felt earthquakes since 1988 in the region. A few significant earthquake events that hit North and Northeast region of India is provided in tabular form too (Table 1) to present seismotectonics consequences of this region.

Fig. 1. Active faults and the large earthquake epicentres since 1897 (modified from Kayal [2]). Two red stars indicate the two great earthquakes (Mw > 8.0) with fault plane solutions, the 1762 great earthquake (M >8.0) in the adjoining region is also indicated by a black-bordered star. The red circles indicate large earthquakes (M > 7.0); the blue stars show strong earthquakes (M>6.0) in this region, and the yellow stars show the earthquakes in Tripura. Active Faults: MCT: Main Central Thrust, MBT: Main Boundary Thrust, MFT: Main Frontal Thrust, NT: Naga Thrust, DsT: Disang Thrust, KF: Kopili fault, DF: Dauki Fault, DT: Dapsi Thrust, OF: Oldhum Fault, DhF: Dudhnai Fault, BS: Barapani shear etc.

Agartala, the capital of the state Tripura, as well as the second-largest city in Northeast India, in terms of municipal area and population, is the present study area (see Fig.2). This city was affected by the occurrence of previous earthquakes in the neighbouring region (as

3

cited in Table 1). The 1869 Cachar earthquake caused substantial destruction at Silchar, in lower Assam as reported by Thomas Oldham [17], while the effect of it in Tripura was not reported. On the other hand, the 1897 Shillong earthquake severely damaged the royal palace at Agartala [Friend of India, 22-29 June 1897] and ruined several buildings and monuments [18]. Moreover, the 1918 Srimongal earthquake also caused extensive damage in Agartala [Englishman, 15 July 1918; [19]. Table 1. List of few notable earthquakes in the North and Northeast India along with adjoining region since eighteenth century. Date (local Magnitude Remarks Reference time) and place Aug. 23, 1833, Nearly 414 persons died in Nepal, the number of [12,13] M w 7.7 Bihar Nepal deaths in India is not reported Jan. 10, 1869, The death toll is not reported [14] M w ~7.4 Cachar June 12, 1897, About 1500 persons died, total devastation of [14] M w 8.1 Shillong Shillong. 1918, Srimangal M s 7.6 Caused extensive damage to buildings in eastern [14] Bangladesh. Substantial damage occurred in buildings of the nearby area of India July 2, 1930, No loss of life reported [14] M w 7.1 Dhubri Jan. 17, 1934, Nearly 10,653 persons died (7253 in India and 3400 [12] M w 8.2 Bihar-Nepal in Nepal) and caused liquefaction over a large area, houses destroyed Aug. 15, 1950, 1530 persons killed and caused massive landslides [14] M w 8.7 Assam Aug.21, 1988, M 6.6a About 1004 persons died. Caused damage to [12] Bihar-Nepal embankments, bridges, masonry buildings; largescale area affected by liquefaction and landslide a Oct. 20, 1991, M 6.4 Nearly 768 lives lost. Bridge collapsed; many [12] Uttarkashi masonry and RC buildings collapsed Oct.08,2005, About 20,600 died. Masonry buildings suffered [12] M w 7.6 India-Pakistan massive damage Sep. 18, 2011 More than 100 persons died, caused severe damage [15] M w 6.8 Sikkim to masonry buildings, monastery and RC buildings, area affected by the landslide Apr.25, 2015, The death toll reached to 8790. Nearly 498,852 [16] M w 7.8 Nepal buildings suffered complete damage and 256,697 were partially damaged M w , M : Moment magnitude; M s : Surface wave magnitude; RC: Reinforced concrete

Very recently, this region experienced a strong earthquake, the 2016 Manipur earthquake (with

M

w

of 6.7) which was strongly felt but no damage has been reported in Agartala. It is

4

reported that the seismic hazard level of Agartala city is quite high with probable Peak Ground Acceleration (PGA) in the range of 0.11-0.33g [20]. However, the Global Seismic Hazard Assessment Programme (GSHAP) set the PGA value in the range of 0.35-0.4g [21]. Furthermore, Indian seismic code IS 1893: Part 1 [22] proposed seismic hazard level of IX or above in Medvedev-Sponheuer-Karnik (MSK) intensity scale corresponding to a PGA value of 0.36 g for the seismic zone V, where the entire Northeast region of India falls. In this context, the next subsection describes the 2017 Ambasa earthquake (with M

w

of 5.7) and the

observed damage to a few unreinforced masonry (URM) buildings in Dhalai and Unakoti district of Tripura. NORTH EAST STATES OF INDIA CHINA

BHUTAN

MYANMAR

BANGLADESH Agartala

Fig. 2. Northeast states of India along with the location of the present study area as marked by a red circle. [image source [23] 2.2 The 2017 Ambasa, Tripura Earthquake On 3rd January 2017 a moderate earthquake of moment magnitude

M

w

5.7, hit Ambasa,

Tripura at 09:09:03 UTC (14:39:03 IST) with an epicentre at 24.01°N and 91.018°E and a focal depth of 32 km as reported by United States Geological Survey [24]. This earthquake 5

occurred due to the strike-slip motion of the Indian plate that situates below the IndoBurmese wedge as reported elsewhere [25]. The tremor was strongly felt in Guwahati, Shillong, Silchar, Imphal, even in Kolkata in India as well as many regions of Bangladesh and Myanmar. Fig. 3 shows PGA at different places as given by the USGS datasheet. The earthquake was followed by two aftershocks of magnitude 3.4 and 3.9 that occurred on 4th and 6th January 2017, respectively. This moderate earthquake caused considerable ground failures such as landslides, lateral spreading, and liquefaction in the vicinity of the epicentral region. As many as 6727 mud-wall houses suffered damage to different degrees (partial to full) as reported by Tripura State Disaster Management Authority on 9th January 2017 while information regarding the performance of the masonry and reinforced concrete buildings were not reported.

Fig.3. Peak ground acceleration map of January 3, 2017 Earthquake extracted from USGS [24].

6

Department of Civil Engineering, National Institute of Technology Agartala, India had sent a team of the researchers, comprising of six members (including two of the authors of this paper) to investigate the damage caused by this moderate earthquake. The postearthquake reconnaissance was carried out from January 6-12, 2017. The team investigated structural as well as geotechnical damage instigated by this event. However, this section addresses the damage observed only in few masonry buildings considering the main objective of this present paper. Damage features of three masonry buildings of the government of Tripura including one junior basic school, one public health centre and one staff quarter building are discussed here. (b) (a)

(c)

(d)

Fig.4. Damage to Tairumchara Junior Basic School building of Govt. of Tripura at Kamalpur: (a), (b) and (c) large shear cracks in both the orthogonal walls meeting at corner joint; (d) damage to the wall in between window openings [images by Lipika Halder]. 7

Figs. 4(a-d) show the damage suffered to Tairumchara Junior Basic School building at Kamalpur under Dhalai district, Tripura. This is a single-storey URM building with a flexible diaphragm as the roof is made up of light galvanized iron (GI) sheet. Moreover, the building was made up of 125 mm thick masonry wall along with 250 mm × 250 mm brick pillar on which roof trusses of GI pipe were supported. Hence, walls are subjected to lesser vertical load as compared to buildings with rigid diaphragm and resistance against in-plane loading was also very less due to lesser wall thickness. Fig. 4(a, d) show that cracks developed from the top and bottom corner of the windows and propagated horizontally through the walls. During the visual inspection of the building from outside, it was observed that cracks propagated in the same location from outside too rendering failure of the pier wall. (a)

(b)

(c)

(d)

8

(e)

Fig.5. Damage to Primary Health Centre under Govt. of Tripura at Machmara: (a) front view of the building; (b) and (c) large cracks in the outer wall from outside the building; (d) and (e) damage in the interior wall just below the roof [images by Lipika Halder]. A Public Health Centre, located at Machmara, Kumarghat under the Unakoti District of Tripura [Figs. 5(a-e)] suffered significant damage in some locations. This is a single-storey URM building with a rigid diaphragm as the roof is made up of a 100 mm thick RC slab. The building was built up of 250 mm thick brick wall. There is no major irregularity in the plan of the building as well as in the position of openings in the walls. However, dampness and growth of fungi in a few walls of the building indicate poor maintenance records. Fig. 5(b) shows the major diagonal shear cracks in the wall that generated from the bottom corner of the window and continued up to the lintel level. From visual inspection of the building, long horizontal cracks were also found in few walls under the roof [as shown in Fig. 5(d)]. These kinds of horizontal cracks are generally found in the walls under roofs, below the lintel band or even at the sill level. Such cracks may generally be a manifestation of shear failure mode. Mortar bed-joint, being the weakest region in the masonry wall, fails first due to large shear during ground shaking.

Moreover, in this moderate earthquake, this kind of damage

highlights the use of raw materials of inferior quality, low mortar mix ratio, poor quality construction, and absence of vertical reinforcement adjacent to the vertical edges of the openings as well as poor maintenance records. A Staff Quarter under the same public health centre suffered major damage and the building was vacated immediately by the government of Tripura. It was a three-storey URM 9

building, having two flats on each floor. The building was mostly regular in vertical direction except for the presence of the projected front balcony, however, plan irregularity was present. The staircase was placed at the centre of the building, but two opposite walls in the shorter direction were of 125 mm thick with a large opening in it at each landing level. Otherwise, all the load resisting walls were of 250 mm thick. The floors and the roof are made up of 100 mm thick RC slab.

10

(a)

(b)

(d)

(c)

(e)

Fig.6. (a) Overview of the staff quarter of Primary Health Centre (PHC), Machmara, kumarghat; (b), (c), (d) severe cracks in walls of mumty room; and (e) damage to the inner wall in the ground floor [images by Lipika Halder].

Figs. 6(a-e) show the extent of damage this building suffered in this moderate earthquake. Broken parts of plaster and bricks were spread over the floors. Mumty room of this building suffered severe damage, see

Figs. 6(b-d). The damage pattern can be attributed to shear

failure mode, indicating poor mortar bed-joint. Substantial horizontal and diagonal cracks were observed in many internal walls on the ground floor as well as on the first-floor level. Fig. 6(e) shows the damage caused in an internal wall at ground floor level. 11

A similar kind of damage was observed in many single-storey and two-storey URM buildings in Dhalai and Unakoti District of Tripura. These are not discussed for the sake of brevity. The level of damage triggered through this moderate earthquake can be treated as a warning to the built environment of this region. Further, similar damages were also observed during the Gorkha Nepal Earthquake of April 25, 2015 [26]. Accordingly, this event motivated the authors to arrive at the fragility curves for such frequently observed singlestorey or double-storey URM buildings. (a)

(b)

(c)

(d)

(e)

(f)

Fig.7. Typical URM buildings found in Northeast India: (a), (b), (c), and (d) in Agartala, Tripura; and (e) and (f) in Guwahati, Assam [(a-d) images by Lipika Halder; (e) and (f) after [27]. 2.3. Inventory of URM Buildings Masonry buildings have been traditionally constructed in this region using undressed rubble stone masonry, dressed stone masonry, URM with lime/cement mortar [27]. Wooden flooring, GCI roofs on wooden/steel truss or RC floors and roofs are common in these buildings. For example, many monasteries of the Northeast state Sikkim; heritage buildings like Ujjayanta Palace, Nirmahal of the state Tripura, etc. belong to these categories. URM building is a very popular building typology that was widely constructed as residential, office, school, and hospital buildings in Tripura, Assam, Sikkim, Meghalaya, Arunachal

12

Pradesh, etc. Fig. 7 shows the typical masonry buildings prevailing in the two major cities in Northeast India, Agartala and Guwahati, respectively. These are basically low-cost, low-rise traditional buildings which are built very quickly without special technical advice. This type of building is predominantly built to resist vertical loads only.

% of buildings

Masonry RCC

50 40 30 20 10 0

% of buildings

(a) Age of building

Masonry RCC

100 80 60 40 20 0 1

2

3

(b) Number of storey

Fig.8. Classification of the building based on age and number of the storey of the building. A detailed side-walk survey was previously conducted in a phased manner in-between August 2012 to April 2017 in various wards of Agartala Municipal Corporation (AMC), Tripura, to collect a detailed inventory of existing buildings. The main objective of this data collection was to judge the seismic vulnerability associated with this area by performing rapid visual screening of these buildings. From the collected inventory, the data of 350 buildings of Ward no 4 of AMC is considered here as an exemplary building inventory of Agartala city. It is observed that out of 350 buildings, 122 are URM buildings and 228 are

13

RC framed buildings with URM infill walls. Figs. 8(a and b) show the distribution of buildings according to the period of construction and number of stories. According to the period of construction (Fig. 8(a)), two periods have been identified. The majority of URM (i.e. about 70 % of the total) date before 1995, while most of the RC buildings were constructed after 1995. Of the buildings studied, it is observed that more than 80% of the assessed URM buildings are single-storey (Fig. 8(b)). On the other hand, nearly 45% of RC buildings are single-storey, 49% are double-storey and the rest are three-storey buildings. Hence, this limited survey-based data also justify that URM building is a significant building typology found in Agartala, and also in the Northeast region as a whole. The presence of this type of buildings may greatly influence the overall seismic risk of the city. 3. Methodology to Assess Seismic Capacity and demand A number of approaches are available in the literature to model masonry buildings for performing nonlinear static or dynamic analysis to evaluate the capacity of the building. Sophisticated micro modelling approach, where each brick unit and mortar joint is modeled separately considering inherent anisotropy through specific nonlinear material relationships for brick, mortar and brick-mortar joint is found in the literature. However, this approach is primarily used for modelling certain parts of building only, for example, wall, due to its high computational effort, rigour and time involved. Comparatively simpler equivalent frame and macro modelling approaches are used to model whole building with a limited number of degrees of freedom to represent in-plane failure mode, namely, rocking failure mode, diagonal tension failure mode and sliding failure mode [28-38]. However, this simplified nonlinear modelling solution is also excessively rigorous to evaluate a large number of buildings within a reasonable time and using a lesser amount of memory. In this context, rather, a simple analytical procedure that is easy to understand and can be applied with

14

confidence is required to assess a building stock in the seismically active region and is also seen in the literature [e.g., [39-43]. The analytical procedure proposed by Lang [41], and Lang and Bachmann [42] is adopted in this study for the evaluation of the structural capacity of building stock. This procedure depends on the nonlinear static method admitting the nonlinear deformation capacity. Moreover, the coupling effect of walls, that joined by floor and spandrels are also considered in this method. The procedure adopted in this study is discussed briefly and sequentially into four sections: analytical modelling, development of the capacity curve of the building, capacity-demand relationship, and damage grade in the sections below.

F1

hp

Pier F2

Htot hst

Spandrel

hst ho

Opening (a)

(b)

Foundation on

lw

Wall

lo lo Fig. 9. (a) Terminology used in the analytical modelling; (b) Bending moment distribution due to strong coupling effect and corresponding reactions (after Lang [41]).

15

2.0 F 1 /F 2 =0 F 1 /F 2 =0.5 F 1 /F 2 =0.75 F 1 /F 2 =1.0

1.5

F 1 /F 2 =1.25

h0/hst

F 1 /F 2 =1.5 F 1 /F 2 =1.75 F 1 /F 2 =2.0

1.0

0.5 0.0

0.5

1.0

1.5

2.0

2.5

( EI sp /l 0 ) / ( EI p /h st )

Fig.10. Variation of

EI spandrel / l0 h0 with for different force distribution of two-storey frame [42]. EI pier / hst hst

3.1 Analytical Modelling In the analytical modelling, the unit structural component of the building is the wall which has a dimension of length

lw and height Htot , the total height of the building as shown in Fig.

9(a) by the red solid line. Pier is the vertical element of the wall having a dimension of length

lw and height equal to the height of the adjacent opening, hp . Whereas spandrel is the horizontal element of the wall that separates the openings placed vertically above and below of it in two consecutive floors. Consecutive walls in one plane interconnected through floors and spandrel create a wall plane. The interaction of walls or piers with spandrels is known as the coupling effect. This effect is negligible when spandrels are not present and walls are considered as interactive cantilever walls, whereas this effect is very influential and has to be considered when deep spandrels are present [Fig. 9(b)]. The level of the coupling effect can be shown by the height of zero moment h 0 in the pier. The ratio of the flexural stiffness of the spandrels to the flexural stiffness of the piers is used to determine the height of zero moment. The polynomial

16

expression mentioned below is used to express h 0 to a two-storey frame with equivalent lateral loads at the storey level [42].

EI spandrel / l0 h0 F1 (1 + 12 x+ 18 x2 ) + F2 (2 + 15 x+ 18 x2 ) = , where x = hst F1(1 + 18 x+ 36 x 2 ) + F2 (1 + 18 x+ 36 x2 ) EI pier / hst

(1)

where hst represent the storey height; l0 is the centre to centre distance between walls; EI pier EI spandrel is the flexural stiffness of the spandrels and is the flexural stiffness of the hst l0 piers. F1 and F2 are equivalent earthquake forces. Fig. 10 shows the variation of function of

h0 as a hst

EI spandrel / l0 of two-storey frame with different load distribution. EI pier / hst

3.2 Development of the Capacity Curve The capacity curve is a graphical representation of the base shear as a function of the roof displacement of the building. This curve shows the lateral resistance of the building due to seismic action. To show the response of the building through the capacity curve, it is generally considered that the building vibrates predominantly in its first mode. The maximum permissible shear capacity of the wall, the nominal yield displacement and ultimate displacement at the top of the wall are used to develop a linearly elastic-perfectly plastic capacity curve followed by bilinear approximation. The curve is considered linearly elastic up to the point corresponds to the maximum shear capacity of the wall and beyond that perfectly plastic with zero stiffness. The capacity curve of the building is obtained in each orthogonal direction and by superposition of the capacity curves of each individual walls in the corresponding direction. In this connection, equal displacement of the walls at each floor level is assured from the assumption that the floor diaphragms are completely rigid. The method of obtaining the capacity curve is expressed below through Eq. 2. n

Vb ( ∆ ) = ∑Vi ( ∆ )

(2)

i =1

17

where i represents the wall index, and equal to 1…n, n is the total number of walls considered in one direction. The stiffness of the linear-elastic portion of the capacity curve is obtained by adding up the effective stiffnesses of the walls as expressed by Eq. 3. n Vbm k= = ∑ keffi ∆by i =1

(3)

where Vbm is the shear capacity of the building and ∆by the nominal yield displacement at the top of the building. The maximum permissible shear capacity of the wall without violating the stress and the sliding criteria is calculated by the expression mentioned below. For the details of the computation of this equation, one may refer to [41].

Vm = where

fm y

fmylwt Ntan φ

(4)

N + N ( tan φ ) + 2 fmyth0 tan φ 2

refers to compressive strength parallel to the mortar bed; l w is the length of wall-

pier; t signifies thickness of wall-pier; N is the total vertical load on wall-pier; and tan φ represents the angle of internal friction. Yield displacement of wall considering flexural, shear and coupling effect all together is calculated by the equation presented below:

(

)

 hp 3h0 − hp κ ∆y = Vm Htot  +  6EIeff GAeff 

   

where EIeff is effective flexural stiffness; GAeff is effective shear stiffness, and

(5)

κ is a shape

factor which depends on the shape of the cross-section of the pier. For a rectangular crosssection, κ becomes 1.2. Failure in the URM wall does not occur as soon as the shear strength of the wall reaches its maximum. Though in general masonry is considered as brittle, significant plastic deformation capacity as compared to yield deformation were observed in experimental studies of the URM walls [44]. One of the sources of absorbing energy is perhaps the frictional behaviour 18

due to the relative movement of various structural elements. Hence, this linear elasticperfectly plastic behaviour is considered to calculate the ultimate displacement using the expression as presented below [41].

∆u = µW ∆ y

(6)

where µW represents the displacement ductility of the URM wall and is calculated as follows.

µW = 1 +

hp H tot

( µWE − 1)

(7) where

µWE

is the ductility of the pier and can be found by the equation as given below:

 δ   u  ,12 δy     

µWE = max 

(8)

where δ y is drift at yield displacement of the pier; and δu represents the maximum admissible drift of the pier and can be determined by using expressions mentioned below:

δy =

∆y H tot

hp  0.8 0.8 − 0.25 σ , < 0.5 ( )  n l w   hp δu = (0.8 − 0.25σ n ) ,0.5 < < 1.5 lw   h  1.2.( 0.8 − 0.25σ n ) , p > 1.5 lw  where

(9)

(10)

σn is normal stress acting on the pier and can be calculated as follows: σn =

N tlw

(11)

where N , l w , and t are the same as already expressed by Eq. 4. Htot is the total height of the wall. 3.3 Seismic Demand Seismic demand is expressed as displacement demand which is calculated using a displacement response spectrum, a plot of the maximum displacement of a single-degree-of19

freedom (SDOF) system with 5% damping as a function of its fundamental frequency. Generally, the acceleration response spectrum is proposed in most of the earthquake codes as found in IS 1893: Part 1 [22] too. However, the acceleration response spectrum is converted to the displacement spectrum to use in this study using the well-known relationship mentioned below. Sd =

where

Sa

ω2

with ω = 2π f

(12)

Sd and Sa are the spectral displacement and the spectral acceleration respectively; ω

is the circular frequency; and f is the frequency in Hz. In order to apply this spectrum, a multi-degree-of-freedom (MDOF) system with concentrated masses at the floor levels is converted to an equivalent single-degree-offreedom (ESDOF) system. The nonlinear behaviour of the building is moreover considered by using inelastic demand spectra to get the displacement demand at the top of the building. Displacement demand

∆D at the top of the building is obtained from the equations given by

Lang [41] as follows.

∆D = cn∆be and ∆be = ΓϕnSd ( f1 ) where

∆be

is the elastic displacement at the top of the building;

(13)

cn accounts for the effect of

nonlinear behaviour and is expressed as follows:

cn =

µD R

with µ D =

∆D V be and R = ∆ by V bm

where µ D is the ductility demand; R is the strength reduction factor;

(14)

∆by

and V

bm

are the

same as already prescribed by Eq. 3. Moreover, based on the principle of equal maximum displacement and principle of equal energy, the relation between R and µ D is given by Veletsos and Newmark [45], as presented below by the Eq. 15. 20

µD R=  2µD − 1

for

f1 < f c1 f1 > f c2

where fc1 and fc2 are limiting the frequency with typical values respectively [42]. Further,

ϕn

(15) ≈

1.4 Hz and 2 Hz

resembles the top storey displacement of the MDOF system corresponding to

the first mode shape;

Γ represents

the modal participation factor; and Sd ( f1 ) signifies

spectral displacement of the ESDOF system. 3.4 Damage Grades Damage grades that give an idea to the user about the physical condition of the building are expressed in various ways as found in the literature. EMS-98 [46] proposed five damage grades as G1 to G5 signifying negligible damage to destruction based on damage observed in seven earthquakes from 1992 to 1998 in Europe. These damage grades were primarily developed for determining the seismic intensity after the post-earthquake survey in Europe. In HAZUS [47], four distinct damage states are mentioned as slight, moderate, extensive and complete damage state. The damage states are expressed as a function of the physical parameter, like threshold values of inter-storey drift or floor acceleration. Many researchers have proposed different damage grades primarily based on either EMS-98 [46]/HAZUS [47] or both with suitable modification [e.g., [42, 48-50]. Table 2 shows the identification of damage grades for masonry building used in this study. Although, column 1 shows five damage grades, out of these five grades only four damage grades are considered in this study. These damage grades are designated as DG1DG4, which are mostly equivalent to slight, moderate, extensive and complete damage states as given by HAZUS [47]. It is worth noting that DG4 and DG5 both signify 100% financial loss or maybe more, as the building has to be demolished completely before constructing a new building and thus increasing the cost. Therefore, the failure of the first wall may instigate 21

the collapse of the building, and so DG4 is considered as complete damage grade and DG5 is not considered. Table 2 shows the identification of damage grade in terms of cracking, yielding or failure of the wall. Hence, to calculate the cracking displacement ∆cr of the wall, at first, the shear capacity V

cr

of the wall at the onset of cracking is calculated by using Eq. (16) as mentioned

below [41]. This value V

cr

is then used on Eq. (5) to get cracking displacement ∆cr .

Smallest cracking displacement of the wall determines the first damage grade i.e. DG1.

Nl Vcr = w 6h0

(16)

4. Description of the Existing URM buildings Building plans were collected from the office of AMC, Tripura. The buildings were mostly built before 1995 and are of the single- or double-storey with an average floor height of 3.00 to 3.20 m. The load-bearing walls of these buildings are made off traditional burnt clay bricks bonded with cement mortar and are of 0.25 m thick. The external walls of the buildings have mostly regular openings for windows and doors along with opening for a door in the internal wall as per requirement. The thickness of the RC roof and floor slabs are ranging from 0.1 to 0.12 m. Table 2. Damage grade description and identification. Damage grade DG 1

DG 2

Description of damagea Negligible to slight damage (no structural damage, slight non-structural damage) Hair-line cracks in very few walls; drop of small pieces of plaster only; drop of loose stones from upper parts of buildings in very few cases Moderate damage (slight structural damage, moderate non-structural damage) Cracks in many walls; drop of fairly large pieces of plaster; the partial collapse of chimneys

22

Damage identificationb

Cracks on the first wall

Performance of the building becomes nonlinear as the stiffness of the building starts to reduce ~Yield of the first wall

DG 3

DG 4

Substantial to heavy damage (moderate structural damage, heavy non-structural damage) Large and extensive cracks in most walls; detachment of roof tiles; fracture of chimneys at the roofline, failure of individual non-structural elements (partitions, gable walls) Very heavy damage (heavy structural damage, very heavy non-structural damage) Serious failure of walls; partial structural failure of roofs and floors

DG5

Destruction (very heavy structural damage) Total or near-total collapse a based on EMS-98 [46]; bbased on Lang and Bachman [42]

The stiffness of the building tends to zero ~Yield of the last wall

Failure of first wall

The drop of the base shear of the building Vb<0.67Vbm.

The capacity curve parameters may vary due to the variation on material properties, quality of construction, the age of the buildings, geometrical configurations, etc. Hence, it is essential to construct the capacity curve for the individual building to develop a comprehensive earthquake damage scenario of any geographic area or a city by considering variability and uncertainty associated with capacity curve properties. However, it is not a practical approach to deal with a huge number of buildings and also not feasible. Hence, representative buildings from a large building stock are to be selected and analysed to obtain capacity curves and to develop data required to estimate statistical parameters like median

12

12

10 Average wall density

10

Wall Density (%)

Wall density (%)

and standard deviation. The uncertainty in capacity is represented by the standard deviation.

8 6 4

Threshold wall density 6.25%

2 0

Average wall 8 density 6 4

Threshold wall density 6.25%

2

Single Storey

0

Double Storey

Single Storey

Number of Storey of Building

Double Storey

Number of Storey of Building

(a) (b)

Fig.11. Percentage of wall density for single and double-storey masonry buildings along with average wall density and threshold wall density in: (a) X direction; and (b) Y direction.

23

Accordingly, a total number of 48 URM buildings are identified from the collected data to represent the URM building stock of Agartala city and grouped into two classes based on the number of storey i.e., single-storey and double-storey building. Out of these buildings, 24 numbers of buildings are single-storey and rest 24 numbers are double-storey. These buildings are observationally irregular in plan view but irregularity in plan offsets is below the permissible limit as per IS 1893: Part 1 [22] i.e., no wing is beyond 15% of the plan dimension. Wall density is an important parameter that influences the responses of the buildings under seismic action. The wall density of a building is calculated by a ratio of the total crosssectional area of the load-bearing wall in any orthogonal direction of the building plan to the total floor area of the building. For any residential building having a plinth area of 100 sqm should have a minimum of 25 m length of the load-bearing wall in both orthogonal directions [51] i.e., minimum wall density in any direction must be 6.25% considering load-bearing walls with 250 mm full brick blocks. Fig.11 shows wall densities of the 48 buildings. The black solid line shows the threshold wall density of 6.25%. The buildings having wall densities below this black line have inadequate load-bearing walls to provide sufficient seismic resistance against lateral load and above this line shows that these buildings have sufficient wall density in the orthogonal directions. The black dash lines indicate the mean wall density of the buildings in each class as considered and it shows that the majority of the buildings possess sufficient wall densities in their plan orthogonal directions. Table 3. Mechanical properties of brick masonry considered in the study. Parameter Compressive strength orthogonal to the mortar bed Compressive strength parallel to mortar bed Young’s modulus (E)

Value 6 MPa 1.8 MPa 2000 MPa

24

Parameter Shear modulus (G)

Value 700 MPa

Friction coefficient

0.8

Since these buildings are located at various locations within the municipality area of Agartala, it can be considered that the construction practice and properties of the material are almost similar. Furthermore, during the study it was not possible to determine the properties of brick masonry through experiments, as well as no specific information about the properties of brick masonry at Agartala city was reported in the literature. In this context, the material properties of burnt clay brick masonry with 1:6 cement-sand mortar have taken from the Manual of Indian Society for Earthquake Technology [52]. The property like self-weight of brick is obtained from IS 875: Part I [53] as 18.85 kN/m3, the shear modulus is considered as 0.35 times Young’s modulus and the friction coefficient is considered as 0.8. Table 3 shows all the properties of brick masonry used in this present study. 5. Analytical Capacity Curves The analytical modelling of the buildings has been developed by the approach discussed in the previous section. In this modelling, piers are identified and their height and length are calculated on each structural wall plane of the buildings. The analytical method explained above is followed to develop the bilinear capacity curve of each wall as well as of the whole building along each orthogonal direction. Among two orthogonal directions, the direction corresponds to the minimum shear capacity of a building is the weaker direction and the capacity curve along that weaker direction is used for further analysis. Fig. 12 shows the capacity curve of a double-storey building developed by overlaying the bilinear capacity curves of walls. Four different damage grades considered in this study are marked too on the global capacity curve. Figs. 13(a) and (b) show the capacity curves obtained from the analysis for single and double-storey buildings in their respective weaker direction. Each curve of the plot gives information about the two points corresponding to the achievement of maximum base shear resistance and the ultimate condition. The significant dispersion of the maximum base shear capacity, as well as yield displacement, are observed in both single and

25

double-storey buildings. This variation in the capacity curve is present due to the variation in the geometrical configuration of the building, size of the wall and its position, etc.

500

Base shear (kN)

400

300 Individual wall Building DG1 DG2 DG3 DG4

200

100

0

0

3

6

9

12

15

Top displacement (mm)

18

21

24

27

300

600

250

500

200

Base Shear (kN)

Base Shear (kN)

Fig. 12 Capacity curve of a double-storey building along with bilinear capacity curves of all walls.

150

100

300

200

100

50

0

400

0

0

3

6

9

12

15

Displacement (mm)

18

21

24

27

0

3

6

9

12

15

18

21

24

Displacement (mm)

(b) Double-storey building (a) Single-storey building

Fig.13. Capacity curves of the URM buildings corresponding to their weaker direction.

26

27

2 .0

Probability density function

DG1 DG2 DG3 DG4

1 .5

1 .0

0 .5

0 .0

0

2

4

6

8

10

12

14

D is p la c e m e n t (m m )

Fig. 14. Probability density function of damage grades for double-storey building. The dispersion of the capacity curves and associated damage grades in both single and double-storey building classes advocated to express fragility function using probability density function. Hence, the probability density function for various damage grades is evaluated for each single and double-storey building classes for further use. Fig.14 is a representation of the probability density functions related to each four considered damage grades for double-storey building class. 6. Fragility Analysis Seismic fragility curve is expressed as the conditional probability of failure of a structure for a specific seismic hazard level. Failure not necessarily means the collapse of the structure. Failure can be described through a threshold damage state when the seismic performance of the structure is expressed by an appropriate damage measure. Hence, the probability of failure is described as the probability of exceeding a certain damage grade for a given PGA. The probability of failure of a certain damage grade is calculated as follows [54]. P f ( PGA ) =

∞

∫ [1 − FD | PGA (α )] f c (α ) d α

0

27

(17)

where FDPGA is the cumulative distribution function (CDF) of the displacement demand for a | certain level of PGA and fc is the probability density function (PDF) of the capacity for a given damage grade.

1.0

1.0

0.8

0.8

0.36 g

0.6

1- CDF

1- CDF

0.6

0.36 g

0.30 g

0.4

0.4

0.30 g 0.12 g 0.18 g 0.24 g 0.06 g

0.2

0.06 g

0.2

0.12 g

0.18 g 0.24 g

0.0

0.0 0

2

4

6

8

Displacement (mm)

10

12

0

14

5

10

15

20

25

30

Displacement (mm)

(a)

(b)

Fig. 15. Complementary cumulative distribution function of displacement demand for different PGA levels for; (a) single-storey building; and (b) double-storey building. The seismic displacement demand is expressed using the acceleration response spectrum as already mentioned in the previous section. The acceleration response spectrum of IS 1893: Part 1 [22] for 5% damping, considering medium soil condition and having PGA 0.36 g is used in this present study. This acceleration response spectrum is then scaled to the different levels of PGA and displacement demand for each building at each level of PGA is computed to incorporate variability associated with the demand. To derive the fragility curve, the convolution of the complementary cumulative distribution function of the displacement demand with the probability density function of each considered displacement limit (i.e. damage grade limit) is carried out as mentioned in the Eq. (17). For the details of the procedure, one may refer to [54]. Fig. 15(a and b) show the complementary cumulative distribution function of the displacement demand for single and double-storey building classes.

28

2.0 PDF for DG 1 PDF for DG 2 PDF for DG 3 PDF for DG 4 PF for DG 1 PF for DG 2 PF for DG 3 PF for DG 4 1-CDF for 0.12g

Probability

1.5

1.0

0.5

0.0

0

2

4

6

8

10

12

14

Displacement (mm)

Fig. 16. Derivation of fragility points for double-storey buildings at a PGA = 0.12g from the convolution of PDF of displacement limit states and complementary CDF of demand.

Fig. 16 is an exemplary graphical illustration of the procedure used to obtained fragility points using complementary cumulative distribution function of the displacement demand (red-dashed-dotted line) for 0.12 g PGA, and probability density functions of various damage grades (solid-line bell curves) for double-storey buildings. The two density functions are convolved and consequently, a probability distribution function (black-dashed-dotted line bell curves) is obtained for each damage grade and these functions are known as the probability of failure (PF) for each damage grade. The area under this probability of failure function for a certain damage grade is integrated to obtain the probability of exceeding that damage grade for the selected level of PGA. These values are the fragility points for that considered level of PGA. Once the continuation of the process of convolution for all damage grades and for all considered levels of PGA is completed, the fragility points so obtained are then fitted using a continuous density function such as lognormal probability density function to derive fragility curve for the single and double-storey building for a range of PGA. Table 4 shows the parameters (µ and σ) of the lognormal distributions.

29

Table 4. Parameters of the lognormal distributions fitting the analytical fragility points. Single-storey building µ σ -5.45 1.29 -3.46 0.71 -2.70 0.59 -1.90 0.57

Double-storey building µ σ -5.45 1.29 -3.77 0.96 -2.76 0.59 -2.26 0.47

1.0

Probability of exceeding damage states

Probability of exceeding damage states

Damage grade DG1 DG2 DG3 DG4

0.8 0.6 0.4

DG1 DG2 DG3 DG4

0.2 0.0 0.00

0.06

0.12

0.18

PGA (g)

0.24

0.30

0.36

(a) Single-storey building

1.0 0.8 0.6 0.4

DG1 DG2 DG3 DG4

0.2 0.0 0.00

0.06

0.12

0.18 PGA ( g)

0.24

0.30

0.36

(b) Double-storey building

Fig.17. Fragility curves of the masonry buildings. Figs. 17(a and b) show the derived analytical fragility curves of the single and doublestorey buildings based on the procedure described in the literature [54]. Each curve describes the probability of exceeding a particular damage grade for a given level of PGA of a certain building class. The figures clearly demonstrate that for a Maximum Considered Earthquake (MCE) hazard level (PGA level of 0.36g) which is prescribed for this Northeast zone of India by IS 1893: Part 1 [22], both single and double-storey buildings have 100% probability of exceeding substantial to heavy damage (DG3). Such probabilities are 94%, and 100% for very heavy damage (DG4) to the single and double-storey building, respectively. However, in the case of a design basis earthquake (DBE) hazard level (PGA level of 0.18g), the probability of exceeding DG4 damage grade is 62% for single-storey building and has increased to 85% for double-storey buildings. Moreover, 94% probability is observed for buildings of both the classes to experience DG3 damage that signifies substantial to heavy damage.

30

It is important to notice here that for a level of PGA 0.052g that was recorded during the 2017 Ambasa Earthquake, the probability of suffering very heavy damage (DG4) appears to be very low (2% for single-storey building and 5% for double-storey building), but significantly high probability of exceeding substantial to heavy damage (DG3) and moderate damage (DG2) is observed for the same level of PGA. It is also to be noticed that the probability of suffering DG3 damage grade, which is 30% for the single-storey buildings has increased to 34% when compared with the corresponding probability for double-storey buildings. Similarly, the probability of exceeding moderate damage (DG2) for single-storey buildings is 74% and the same for double-storey building comes to be 79 %. Moreover, the probability of suffering slight damage (DG1) is 97 % for both single and double-storey buildings. Hence, even the repetition of the same 2017 Ambasa earthquake in the Agartala city can cause substantial to heavy damage (DG3) to the URM buildings of this area. The damage suffered by the three URM buildings, Tairumchara Junior Basic School, Primary Health Centre and Staff Quarter under Primary Health Centre by the 2017 Ambasa earthquake is already discussed in the earlier section. The damage of these three buildings has been recalculated from the fragility curves developed in the present study. Here, damage grades are assigned on these buildings based on EMS-98 [46] to compare with the outcome of the fragility analysis. Table 5 shows the observed damage grade and the probability of exceedance of certain damage grade obtained from the fragility curves. The buildings considered in the analysis have a wall thickness of 250 mm for all the buildings. Moreover, two building classes based on the number of storey namely single-storey building and double-storey building are considered. Hence, in case of Tairumchara Junior basic School which have 125 mm thick wall, the observed damage grade is DG3, which is higher than the probability of suffering this damage grade for single-storey building (30% for the PGA level of 0.052g) having a wall thickness 250 mm and it is justified. In the case of single-storey

31

Primary Health Centre which has a 250 mm thick wall, the observed damage grade is DG2 and according to the derived fragility curve, a high probability of exceedance (74%) of DG2 is observed for single-storey building. Table 5. Observed damage grade and the probability of exceeding damage grade. Name of building

Description of observed Observed damage Damage Grade

Probability of exceeding damage grade for PGA level 0.052g from the present study with comments

Single-storey building Large and extensive DG2/DG3 with GCI sheet roofing; continuous horizontal wall thickness is 125 mm cracks in two walls; in other walls minor crack

DG3 30%

Primary Health Centre

DG2 74%

Single-storey with RC roof slab

Cracks in many walls; DG2 drop of fairly large building pieces of plaster

Staff Quarter under Large and extensive DG2/DG3 Primary Health Centre cracks in the wall of mumty room; cracks in Three-storey building many walls; drop of with RC roof slab fairly large pieces of plaster

DG2 74% The flexible diaphragm is not considered in the present study, moreover lesser wall thickness increased the damage level

DG2 79% DG3 34% Three-storey building is not considered in this study; values of the double-storey building are given

The Staff Quarter under Primary Health Centre is a three-storey building and the walls of mumty room of this building suffered substantial to heavy damage (DG3). However, for other walls the observed damage grade is DG2. Though this category of building is not considered in this study but from the fragility curve of the double-storey building which shows 34% probability of suffering DG3 damage grade, an idea of the higher probability of suffering this damage grade, in reality, can be made.

7. Conclusions The present study attempts to assess the seismic risk of existing low-rise unreinforced masonry buildings in the Northeast region of India, a most seismically active zone of this 32

country. Agartala, the capital city of Tripura is selected as a study area representative of the urban areas of the Northeast region of India. A number of masonry buildings are damaged during the 2017 Ambasa earthquake (with M w of 5.7) and the typical nature of damage to masonry buildings is discussed at the beginning to signify the importance of the present study. Similar damage was also observed during the earthquake in Sikkim [15] and the recent earthquake in Nepal [26]. Such huge damage to structures acted as a motivation for further study on the vulnerability of the Northeast region of India. The following broad conclusions can be summarized from the present study 1. A simple but rather more precise analytical evaluation method based on a nonlinear static approach is used to develop bilinear capacity curve parameters and have been used to estimate fragility functions. This method is a balance between conceptual rigour and computational feasibility. It helps to deal with a large number of buildings. Total 48 URM buildings comprised of single- and double-storey are grouped in two classes as single-storey building and double-storey building and are analysed to develop fragility curves. 2. The investigation of the three damaged masonry buildings shows the absence of horizontal seismic bands and vertical reinforcement adjacent to the vertical edges of the openings, poor quality construction practice as well as the poor maintenance records. As these are the primary parameters that control the response of the URM buildings, the absence of this parameter result substantial to heavy damage in these building even by the earthquake of having PGA level of 0.052g which is quite low as compared to design basis earthquake (0.18 g). 3. The fragility curves show that in case of design basis earthquake (DBE) hazard level (PGA level of 0.18g) as proposed by IS 1893: Part 1 [22], the probability of suffering very heavy damage is 62% for the single-storey building. It is further found to increase to 85% for the double-storey building. Moreover, the very high probability is observed for buildings of 33

both the classes to experience substantial to heavy damage. In the Maximum Considered Earthquake (MCE) hazard level (PGA level of 0.36g), all the buildings would surely suffer substantial to heavy damage (DG3) and very heavy damage (DG4). 4. More importantly, the fragility curves show that for a PGA level of 0.052g, that recorded during the 2017 Ambasa Earthquake, the probability of suffering moderate damage (DG2) which signifies the formation of cracks in many walls along with falling of large pieces of plaster is considerably high. Moreover, the probability of suffering slight damage (DG1) is 97 % for both single and double-storey building classes. This broadly conforms to real-life observations during an earthquake. The study with its results presented in terms of the fragility curves suggests that the seismic vulnerability of the residential URM buildings in Agartala city is considerably high. The fragility curves developed in this study can be used to find the seismic risk of other areas also but only applicable to the buildings belonging to the same typology. However, using the proposed approach other types of building specifically office buildings, hospital buildings, school buildings, heritage buildings, etc. can be assessed in large numbers to develop the fragility curves in order to assess the risk of the whole urban area of the Northeast region of India. In the limited scope of the present study, the uncertainty in construction quality and modelling uncertainty have not been taken into consideration which may have a significant effect on the fragility curves [55, 56]. Hence, further detailed studies considering the effect of other variability from construction quality and modelling uncertainty, seismic demand, etc. are needed to be carried out to assess the vulnerability of URM buildings more accurately.

Acknowledgements The authors acknowledge financial support from the National Institute of Technology Agartala for conducting damage survey after the 2017 Ambasa Earthquake. The support received from Mr. Abhijit Sarkar, a graduate student of the Civil Engineering Department and

34

a Junior Engineer of Public Works Department, Govt. of Tripura, towards the survey work, is gratefully acknowledged.

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[26] Dutta SC, Nayak S, Acharjee G, Panda S K, Das P K. Gorkha (Nepal) earthquake of April 25, 2015: actual damage, retrofitting and prediction by RVS for a few typical structures, Soil Dyn. Earthq. Eng. 89 (2016) 171-184. https://doi.org/10.1016/j.soildyn.2016.08.010. [27] National Disaster Management Authority (NDMA), Seismic Vulnerability Assessment of Building Types in

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Highlights •

Low-rise unreinforced masonry buildings, which greatly increase the seismic risk of any area are frequently observed in north-eastern India.

•

A moderate earthquake ( M w 5.7) caused considerable damage to unreinforced masonry buildings in Tripura, a north-east state of India.

•

To assess the seismic vulnerability of low-rise URM buildings of Tripura, fragility analysis is carried out using bilinear capacity curve parameters through a nonlinear static approach.

•

The fragility curves may be used to assess the seismic risk of the same building typology to the other city in north-east India.