Practical Development and Application of Fragility Functions

Hamburger, Ronald O.; Kennedy, R.P.

doi:10.1061/40944(249)23

Cited by 29 publications

(20 citation statements)

References 8 publications

(7 reference statements)

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“…The probability density function of R, also known as the fragility function, follows a lognormal distribution characterized by its logarithmic mean and standard deviation [12,13]. In other words, the probability density function may be represented by a lognormal distribution as in Eq.…”

Section: Fragility Functionmentioning

confidence: 99%

“…(15) depends on the hazard analysis for a specific area and the statistics of resistance in terms of logarithmic mean λ and logarithmic standard deviation ξ. The values of ξ depend on record-to-record variation, the amount of data used in the analysis, material variability, and the structure model error given by [13].…”

Section: Io Smrfs Io Imrfs Ls Smrfs Ls Imrfs Cp Smrfs Cp Imrfsmentioning

confidence: 99%

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Probabilistic Modeling of Seismic Risk Based Design for a Dual System Structure

Sidi

2017

J. Eng. Technol. Sci.

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Abstract. The dual system structure concept has gained popularity in the construction of high-rise buildings over the last decades. Meanwhile, earthquake engineering design provisions for buildings have moved from the uniform hazard concept to the uniform risk concept upon recognizing the uncertainties involved in the earthquake resistance of concrete structures. In this study, a probabilistic model for the evaluation of such risk is proposed for a dual system structure consisting of shear walls or core walls and a moment frame structure as earthquake resistant structure. Uncertainties in the earthquake resistance of the dual system structure due to record-to-record variability, limited amount of data, material variability and structure modeling are included in the formulation by means of the first-order second-moment method. The statistics of resistance against earthquake forces are estimated by making use of incremental nonlinear time history analysis using 10 recorded earthquake histories. Then, adopting the total probability theorem, the reliability of the structure is evaluated through a risk integral scheme by combining the earthquake resistance of the structure with the annual probability of exceedance for a given location where the building is being constructed.

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Section: Fragility Functionmentioning

confidence: 99%

Section: Io Smrfs Io Imrfs Ls Smrfs Ls Imrfs Cp Smrfs Cp Imrfsmentioning

confidence: 99%

Probabilistic Modeling of Seismic Risk Based Design for a Dual System Structure

Sidi

2017

J. Eng. Technol. Sci.

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“…Fragility functions are probability distributions that are used to indicate the probability that a component, element or system will be damaged to a given or more severe damage state as a function of a single predictive demand parameter, such as storey drift or floor acceleration (Porter, Hamburger and Kennedy 2007). In earthquake engineering, global collapse, which is considered in this study, refers to the instability of a structural system to sustain gravity loads in the presence of seismic effects.…”

Section: Collapse Fragility Curvementioning

confidence: 99%

A method to calculate spectral shape factor

Nicknam

Ganjvar

Mazarei

2015

The IES Journal Part A: Civil & Structural Engineering

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A method to calculate spectral shape factor (SSF) is proposed which permits the calculation of individual structure. The proposed algorithm efficiently relates the 50th percentile collapse capacity of the given structure to the spectral amplitudes of the rare events. The traditional target epsilon and the conditional mean spectrum are used to estimate the collapse capacity given the hazard level. The process of calculating SSF including the general ground motion set presented in FEMA P695 are performed by the developed MATLAB code. The OPENSEES software is used for dynamic analysis of the structure using the incremental dynamic analysis method. The two reinforced concrete special moment frame structures having eight and four stories previously designed and used by Haselton are tested. The results are compared with those of the FEMA P695 and Haselton ending up with smaller SSF values. The result of this study is useful for calculating the structural collapse margin ratio and risk-targeted specific site response spectrum.

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“…Liel andLynch 2012 and, and, then, to implement a Bayesian updating of those fragility functions by including the additional information provided by the new data (e.g., Miano et al 2016). The regression parameters of the new earthquake data are employed, providing a novel interpretation of the consolidated Bayesian update of fragilities with respect to other studies (e.g., Singhal and Kiremidjian 1998;Porter et al 2007a;Jaiswal et al 2011;Miano et al 2016).…”

Section: Introductionmentioning

confidence: 99%

RC infilled building performance against the evidence of the 2016 EEFIT Central Italy post-earthquake reconnaissance mission: empirical fragilities and comparison with the FAST method

Luca

Woods

Galasso

et al. 2017

Bull Earthquake Eng

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Damage data on low-to-mid-rise Reinforced Concrete (RC) buildings, collected during the UK Earthquake Engineering Field Investigation Team post-earthquake reconnaissance mission on the August 24 Central Italy earthquake, are employed to derive empirical fragility relationships. Given the small dataset, the new data distributions are used for the Bayesian update of fragility functions derived for the L'Aquila earthquake (same seismic region and similar construction typologies). Other properties such as number of storeys, age of construction and shape in plan of the buildings are also analyzed. This information is employed to assess the ability of the FAST method to predict damage states in non-regular infilled RC buildings for the municipalities of Amatrice, Accumoli, Arquata del Tronto and Norcia, all severely affected by the 2016 Central Italy sequence. FAST is a spectral-based method to derive capacity curves and peak ground acceleration damage state thresholds for buildings. It is a dedicated methodology for regular RC frame buildings with masonry infills, first calibrated on damage data from the 2009 L'Aquila earthquake and applied to the 2011 Lorca (Spain), the 2012 Emilia (Italy) events for damage backanalyses. The new data from the August 2016 Central Italy earthquake provide a test-bed for FAST further employments in case of less homogenous building samples. The application of FAST presented here accounts for different shake-maps produced by both the United States Geological Survey and the Italian National Institute of Geophysics and Volcanology which are significantly different and representative of different refinements of the demand scenario. For the area of Amatrice, where the two shake-maps provide similar estimates and the buildings considered match reasonably well the typology for which FAST is calibrated, the comparison between damage level observed and as provided by

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Practical Development and Application of Fragility Functions

Cited by 29 publications

References 8 publications

Probabilistic Modeling of Seismic Risk Based Design for a Dual System Structure

Probabilistic Modeling of Seismic Risk Based Design for a Dual System Structure

A method to calculate spectral shape factor

RC infilled building performance against the evidence of the 2016 EEFIT Central Italy post-earthquake reconnaissance mission: empirical fragilities and comparison with the FAST method

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