Evaluation of analytical methodologies used to derive vulnerability functions

• Published in: Earthquake engineering & structural dynamics Vol. 43; no. 2; pp. 181 - 204
• Main Authors: Silva, V., Crowley, H., Varum, H., Pinho, R., Sousa, R.
• Format: Journal Article
• Language: English
• Published: Chichester Blackwell Publishing Ltd 01-02-2014; Wiley; Wiley Subscription Services, Inc
• Subjects: analytical methodologies; Computation; Earth sciences; Earth, ocean, space; Earthquakes, seismology; Engineering and environment geology. Geothermics; Engineering geology; Estimating; Exact sciences and technology; Fragility; Internal geophysics; loss assessment; Mathematical analysis; Mathematical models; Seismic hazard; Seismic phenomena; vulnerability; risk assessment; damage; models; accuracy; vulnerability; earthquakes; loss assessment; propagation; balance; buildings; earthquake engineering; uncertainties; fragility; stability; seismic risk; analytical methodologies
• DOI: 10.1002/eqe.2337
• EISSN: 1096-9845
• ISSN: 0098-8847

SUMMARY
The recognition of fragility and vulnerability functions as a fundamental tool in seismic risk assessment has led to the development of more and more complex and elaborate procedures for their computation. Although these functions have been traditionally produced using observed damage and loss data, more recent studies propose the employment of analytical methodologies as a way to overcome the frequent lack of post‐earthquake data. The variation of the structural modelling approach on the estimation of building capacity has been the target of many studies in the past; however, its influence on the resulting vulnerability model for classes of buildings, the impact in loss estimations or propagation of the uncertainty to the seismic risk calculations has so far been the object of limited scrutiny. In this paper, an extensive study of static and dynamic procedures for estimating the nonlinear response of buildings has been carried out to evaluate the impact of the chosen methodology on the resulting capacity, fragility, vulnerability and risk outputs. Moreover, the computational effort and numerical stability provided by each approach have been evaluated and conclusions drawn regarding the optimal balance between accuracy and complexity. Copyright © 2013 John Wiley & Sons, Ltd.