Techno Press
Techno Press

Smart Structures and Systems   Volume 14, Number 5, November 2014, pages 847-867
DOI: http://dx.doi.org/10.12989/sss.2014.14.5.847
 
A new methodology of the development of seismic fragility curves
Young-Joo Lee and Do-Soo Moon

 
Abstract     [Full Text]
    There are continuous efforts to mitigate structural losses from earthquakes and manage risk through seismic risk assessment; seismic fragility curves are widely accepted as an essential tool of such efforts. Seismic fragility curves can be classified into four groups based on how they are derived: empirical, judgmental, analytical, and hybrid. Analytical fragility curves are the most widely used and can be further categorized into two subgroups, depending on whether an analytical function or simulation method is used. Although both methods have shown decent performances for many seismic fragility problems, they often oversimplify the given problems in reliability or structural analyses owing to their built-in assumptions. In this paper, a new method is proposed for the development of seismic fragility curves. Integration with sophisticated software packages for reliability analysis (FERUM) and structural analysis (ZEUS-NL) allows the new method to obtain more accurate seismic fragility curves for less computational cost. Because the proposed method performs reliability analysis using the first-order reliability method, it provides component probabilities as well as useful byproducts and allows further fragility analysis at the system level. The new method was applied to a numerical example of a 2D frame structure, and the results were compared with those by Monte Carlo simulation. The method was found to generate seismic fragility curves more accurately and efficiently. Also, the effect of system reliability analysis on the development of seismic fragility curves was investigated using the given numerical example and its necessity was discussed.
 
Key Words
    seismic fragility curve; seismic risk assessment; earthquake loss; reliability analysis; system reliability; first order reliability method; Monte Carlo simulation
 
Address
Young-Joo Lee:School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 689-798, Republic of Korea
Do-Soo Moon:Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign,
Urbana, IL 61801, USA
 

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