Analytical evaluation of damage probability matrices for hill-side RC buildings using different seismic intensity measures

Surana, Mitesh; Meslem, Abdelghani; Singh, Yogendra; Lang, Dominik H.

doi:10.1016/j.engstruct.2020.110254

Cited by 26 publications

(12 citation statements)

References 35 publications

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“…This observation is also in agreement with that in a similar study by Surana et al. 30 on fixed‐base hill‐side buildings.…”

Section: Seismic Fragility Of Coupled Building‐slope Systemsupporting

confidence: 93%

“…It can be observed from the table that the considered buildings have probability of collapse almost in acceptable range when considered to have fixed‐base. This observation is in good agreement with the past studies 30,99 on hill‐side buildings ignoring the effect of slope. However, when the buildings are located near the crest of the slopes (3B‐A), the probability of collapse is unacceptably high.…”

Section: Seismic Fragility Of Coupled Building‐slope Systemsupporting

confidence: 93%

“…Only a few studies are available on seismic fragility for buildings located on slopes. Most of the past studies have considered only the effect of the irregular configurations of the hill-side buildings, ignoring slope-building interaction (SBI), 26,[29][30][31][32][33][34][35] whereas others [36][37][38][39] have considered the topographic effect and nonlinear slope movement but have ignored the effect of irregular structural configuration. Fotopoulou, Pitilakis 36 used a two-step uncoupled approach to assess the vulnerability of low-rise (single storey, single bay) reinforced concrete (RC) frame buildings supported on isolated and continuous slab foundation.…”

Section: Noveltymentioning

confidence: 99%

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Seismic fragility analysis of coupled building‐slope systems

Raj,

Singh,

Kaynia

2023

Earthq Engng Struct Dyn

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Buildings located on hill slopes are subjected to additional effects under seismic action compared with those on flat ground. This article presents Incremental Dynamic Analyses of coupled building‐slope systems incorporating topographic amplification, nonlinear slope movement and irregular structural configuration of hill‐side buildings. Two different stable slopes, supporting single and multiple adjacent ductile moment resisting reinforced concrete frame buildings with step‐back configuration, prevalent in Indian and Chinese hilly regions, are modelled and analyzed using the finite element software ABAQUS. A suite of 21 ground motions is incrementally scaled and used to compute the seismic response of the coupled system. Fragility curves for different damage states, derived as lognormal probability distributions in terms of three different Intensity Measures (IMs) and damage probabilities of the considered buildings, are derived and compared. The spectrum‐based IMs (e.g., spectral acceleration at fundamental period, and average of the spectral acceleration over a period range) result in lower record‐to‐record variability, compared with the peak ground acceleration as the IM. The results reveal that ignoring the effect of slope significantly underestimates the fragility for all the damage states.

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“…This observation is also in agreement with that in a similar study by Surana et al. 30 on fixed‐base hill‐side buildings.…”

Section: Seismic Fragility Of Coupled Building‐slope Systemsupporting

confidence: 93%

Section: Seismic Fragility Of Coupled Building‐slope Systemsupporting

confidence: 93%

Section: Noveltymentioning

confidence: 99%

See 1 more Smart Citation

Seismic fragility analysis of coupled building‐slope systems

Raj,

Singh,

Kaynia

2023

Earthq Engng Struct Dyn

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“…From the technical and social points of view, multi-storey reinforced concrete (RC) residential buildings are a particularly important group of buildings. In the literature, damage to these type of buildings is analyzed mainly in terms of safety [1,2]; however, damage often also causes the deterioration of thermal insulation properties, raising heating costs. In addition, damages contribute to the formation of thermal bridges, but they can also be the cause of disruption of the waterproof layers, leading to the penetration of moisture into the building.…”

Section: Introductionmentioning

confidence: 99%

Convolutional Neural Network and Support Vector Machine for Prediction of Damage Intensity to Multi-Storey Prefabricated RC Buildings

2022

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This paper presents the results of a comparative analysis of Convolutional Neural Network (CNN) and Support Vector Machine (SVM) models created for the prediction of the extent and intensity of damage caused to multi-storey reinforced concrete (RC) buildings. The research was conducted on a group of residential buildings, which were subjected to mining impacts in the form of surface deformations and rock mass tremors during their technical life cycle. Damage to buildings poses a significant threat to the safety of the structure and the serviceability of the buildings. They are often the cause of breaks in thermal insulation, which leads to excessive consumption of thermal energy used for space heating, which in turn contributes to over-emissions of CO2 into the atmosphere. Therefore, this problem is important, not only from a technical dimension, but also includes social, economic, and environmental aspects, which allows it to be classified as an issue of sustainable development in the building industry. As a result of the conducted analysis, among the CNN models, the highest level of classification accuracy was the model obtained using the ADAM (derived from adaptive moment estimation) algorithm, which was also characterized by a very high level of generalization, obtaining 80.35% correctly classified patterns for the training set and 80.52% for the test set. However, its accuracy level was slightly lower than that of the SVM model (85.15% for the training set and 84.42% for the test set), in which Bayesian optimization was used to determine the parameters. The analysis confirmed the effectiveness of the adopted methodology for predicting the extent and intensity of damage. The developed tool can support the optimization of building maintenance management, resulting in reduced economic and environmental expenditures for renovations.

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“…Mohammad et al [2] studied the vertical irregularity in the structure and its effect during the earthquake was analyzed in the ETABs software. Mitesh Surana et al [3] observed the seismic vulnerability of the hillside building in the Indian Himalayan region. Siva et al [4] studied the different types of irregularity present in the structures.…”

Section: Introductionmentioning

confidence: 99%

Effect of position of steel bracing in L-shape reinforced concrete buildings under lateral loading

Bohara¹,

Ganaie²,

Saha³

2021

Res. Eng. Struct. Mater.

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The level of damage in irregular structures is more compared to regular structures. In this study, L shaped RC buildings are investigated with and without steel bracings in different positions in frames. The response spectrum analysis has been done by using ETABs software. The two cases considered, case I and case II for understanding the effect in inverted V bracing in L shape building. Case II shows the suitable seismic parameters when bracing is used properly. Interstory drift, displacements, base shear, fundamental time period, torsional irregularity ratio and the capacity ratio of the columns are evaluated. It is also noticed that adding the steel bracing decreases the inter-story drift, displacements of the structure effectively. The torsional irregularity ratio of each 12 models are studied carefully. The capacity ratio of the selected columns is studied to understand the performance of the columns while using the steel bracing in the buildings. The steel bracings are effectively used as retrofitting in L shaped buildings if the position of bracings are considered in the frames appropriately. While designing irregular buildings with steel bracings, the torsional effect should be checked.

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Analytical evaluation of damage probability matrices for hill-side RC buildings using different seismic intensity measures

Cited by 26 publications

References 35 publications

Seismic fragility analysis of coupled building‐slope systems

Seismic fragility analysis of coupled building‐slope systems

Convolutional Neural Network and Support Vector Machine for Prediction of Damage Intensity to Multi-Storey Prefabricated RC Buildings

Effect of position of steel bracing in L-shape reinforced concrete buildings under lateral loading

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