Treatment of uncertainties in seismic fragility assessment of RC frames with masonry infill walls

Choudhury, Trishna; Kaushik, Hemant B.

doi:10.1016/j.soildyn.2019.105771

Cited by 33 publications

(14 citation statements)

References 36 publications

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“…In this study, a subset of RVs was considered, in line with similar assumptions in previous studies. 4,16,19,60 Figure 3 depicts the target correlation coefficients (i.e. correlation matrix), together with the obtained correlation matrix, using CLHS 11 and the one that would in turn have been obtained with classical LHS, 10,11 demonstrating the benefits of the former, given by a drastic reduction of the spurious correlation modes.…”

Section: Generation Of Structural Model Realizationsmentioning

confidence: 92%

Epistemic uncertainty in poorly detailed existing frames accounting for masonry infill variability and RC shear failure

Mucedero

Perrone

Monteiro

2022

Earthq Engng Struct Dyn

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Robust performance‐based earthquake assessment should consider the effects of both aleatory and epistemic uncertainty on seismic response parameters. While the effects of modelling uncertainty on specific engineering demand parameters and collapse fragility curves have been widely investigated to date on bare frame structural typologies, little attention has been paid to the impact of masonry infill properties variability on the uncertainty estimation in existing infilled RC frames. Previous studies available in the literature are mainly related to seismically designed RC buildings and the suggestions provided in international guidelines cannot be reasonably adopted for poorly detailed RC existing frames. As regards the uncertainty in existing RC frames, the role of masonry infills was often neglected or their interaction with the surrounding frames was not rigorously accounted for in the uncertainty estimation. With such limitations in mind, the aim of this study is to provide more realistic modelling uncertainty quantities to be adopted in seismic assessment of existing infilled RC frames, including, in a thorough manner, the impact of the variability of the masonry infill typologies and the occurrence of RC frame shear failure. Both the aleatory and epistemic uncertainties are estimated, in terms of the overall dispersion on specific engineering demand parameters and collapse fragility curves. Finally, the impact of such uncertainties on seismic risk estimates, quantified through expected annual losses, is also thoroughly investigated. The inclusion of additional random variables, not considered so far, in the uncertainty estimation framework, led to importantly higher modelling uncertainty quantities than those currently available from previous studies.

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Section: Generation Of Structural Model Realizationsmentioning

confidence: 92%

Epistemic uncertainty in poorly detailed existing frames accounting for masonry infill variability and RC shear failure

Mucedero

Perrone

Monteiro

2022

Earthq Engng Struct Dyn

View full text Add to dashboard Cite

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“…SI is the structural index that was derived by multiplying five components, viz., (A) seismicity index; (B) effect of soil condition; (C) type of structure; (D) building irregularities; and (E) importance of the building. The non-structural index (NSI) is the product of three components: B, E, and F, as formulated in Equations ( 4) and (5). Here, F is the highest value between F1 for life-threatening falling hazards and F2 for a threat to key operations.…”

Section: Rvs-canadian Methodsmentioning

confidence: 99%

“…Over the years, various vulnerability assessment approaches have been developed, by which the variation between approaches depends on the scale of the complexity of the region and the types of buildings under investigation. Mainly, when investigating a small number of buildings with small numbers of components, the most critical vulnerability assessment approach is related to the analytical methods, such as a detailed and simplified analytical approach for conducting fragility functions and the analytical Vulnerability Index (VI) [3][4][5][6][7]. The analytical method needs a complex computational process and a broad knowledge of structural characteristics and components, where the method can 2 of 33 be categorized into three main approaches: (i) the collapse mechanism approach, (ii) the capacity spectrum approach, and (iii) the displacement approach [8].…”

Section: Research Backgroundmentioning

confidence: 99%

Assessment of Seismic Building Vulnerability Using Rapid Visual Screening Method through Web-Based Application for Malaysia

et al. 2021

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Rapid visual screening is a quick and simple approach often used by researchers to estimate the seismic vulnerability of buildings in an area. In this study, preliminary seismic vulnerability assessment of 500 buildings situated at Northern and Eastern George Town, Malaysia, was carried out by utilizing a modified FEMA-154 (2002) method that suits Malaysian conditions. Data were collected from online sources via Google Maps and Google Earth instead of traditional surveying data collection through street screening. The seismic assessment analysis of this study was based on the RVS performance score and the damage state classification for each building typology. This approach generates, for each building, a final performance score based on governing parameters such as structural resisting system, height, structural irregularities, building age, and soil type. The findings revealed the immediate need for effective seismic mitigation strategies, as 90% of the studied buildings required a further detailed analyses to pinpoint their exact seismic vulnerability performance. Most of the surveyed buildings were predicted to experience moderate-to-substantial damage, with 220 out of 500 being classed as damage state 2 (D2) and damage state 3 (D3). A GIS map, “RVS Malaysian Form-George Town Area”, was generated via ArcGIS and shared with the public to provide vital information for further research.

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“…The standard deviation of the residuals, i.e., vertical distance between the data point and the regression line, defines the variability of the seismic demand [40]. It is commonly referred as β D (see also Table 5) and describes the uncertainty in response due to variation in ground motion properties [78]. Panchireddi and Ghosh [79] applied an approach based on the Park and Ang damage index [80] to investigate the vulnerability of bridges against earthquakes.…”

Section: Methodsmentioning

confidence: 99%

Seismic Vulnerability Assessment Methodologies for Roadway Assets and Networks: A State-of-the-Art Review

2020

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Road networks are considered as one of the most important transport infrastructure systems, since they attain the economic and social prosperity of modern societies. For this reason, it is vital to improve the resiliency of road networks in order to function normally under daily stressors and recover quickly after natural disasters such as an earthquake event. In the last decades, vulnerability assessment studies for road networks and their assets gained great attention among the research community. This literature review includes a brief introduction about seismic vulnerability assessment, followed by the roadway assets damage and their damage states, and then the main typologies for the vulnerability assessment of roadway assets. Moreover, it focuses on available assessment methods, which were proposed to quantify the vulnerability of road networks and its assets. These methods are divided into two main categories, physical and traffic-based approaches. Methods based on fragility functions and vulnerability indexes were investigated in physical approach for roadways and its assets. On the other hand, accessibility and link importance index were explored in traffic-based approach for road networks. This paper reviews and comments the most common vulnerability assessment methods for road networks and its assets and points out their advantages and disadvantages. The main gaps and needs are identified and recommendations for future studies are provided.

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Treatment of uncertainties in seismic fragility assessment of RC frames with masonry infill walls

Cited by 33 publications

References 36 publications

Epistemic uncertainty in poorly detailed existing frames accounting for masonry infill variability and RC shear failure

Epistemic uncertainty in poorly detailed existing frames accounting for masonry infill variability and RC shear failure

Assessment of Seismic Building Vulnerability Using Rapid Visual Screening Method through Web-Based Application for Malaysia

Seismic Vulnerability Assessment Methodologies for Roadway Assets and Networks: A State-of-the-Art Review

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