|Title||Development of Empirical and Analytical Fragility Functions Using Gaussian Kernel Smoothing Methods|
|Publication Type||Conference Paper|
|Year of Publication||2013|
|Authors||Noh HY, Lallemant D, Kiremidjian A|
|Conference Name||11th International Conference on Structural Safety & Reliability (ICOSSAR 2013)|
|Conference Location||New York, N.Y.|
The Global Earthquake Model Consortium has undertaken the complex task of formulating guidelines for heuristic, empirical and analytical vulnerability functions development. As part of the empirical and analytical vulnerability functions developments, Gaussian kernel smoothing (GKS) methods are intro- duced for fitting the form of the vulnerability function to either the observed or simulated ground motion ver- sus damage data. In this paper, three approaches using GKS are introduced for developing analytical and em- pirical fragility functions. These methods enable the treatment of uncertainty in either or both of ground motion intensity and structural damage. The methods are applied to a set of numerically simulated data for a four-story steel moment-resisting frame and a set of field observations collected after 2010 Haiti earthquake. The results demonstrate that these methods can develop continuous representation of fragility functions with- out specifying their functional forms and treat sparse data sets more efficiently than conventional data binning methods.