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Multivariate return period‐based ground motion selection for improved hazard consistency over a vector of intensity measures
Ground motion selection is a crucial step in probabilistic seismic performance assessment of structural systems. Particularly, identifying ground motion records compatible with a specific hazard level has been the major focus of past studies. We propose a multivariate return period (MRP)‐based record selection methodology to further improve the multivariate hazard consistency over a vector of intensity measures (IMs). Unlike the traditional univariate return period anchored on a scalar IM, MRP generalizes the return period concept by accommodating the joint rate of exceedance of a vector of IMs, thereby providing more holistic seismic hazard characterization. By leveraging MRP in linking the seismic hazard to a vector IMs, the proposed MRP‐based ground motion selection methodology for the first time offers a mathematically rigorous yet practical solution for multivariate hazard consistency in ground motion selection. The merit of the MRP‐based ground motion selection is demonstrated by comparing the resulting target spectra and seismic demand estimates for several case‐study structures with other state‐of‐the‐art ground motion selection alternatives. From the results, the MRP‐based ground motion selection employing Kendall's distribution function turns out to be a promising alternative, offering favorable new features including (a) moderate target spectra intensity and moderately low target spectra standard deviation; (b) superior convergence with the increase of the conditioning IM dimension and ability to approximate higher‐dimensional multivariate hazard consistency with lower dimensional conditioning IMs; and (c) capability to realistically capture the multimodal spectral shape owing to the incorporation of multivariate Gaussian mixture distribution in generating target spectra.
Multivariate return period‐based ground motion selection for improved hazard consistency over a vector of intensity measures
Ground motion selection is a crucial step in probabilistic seismic performance assessment of structural systems. Particularly, identifying ground motion records compatible with a specific hazard level has been the major focus of past studies. We propose a multivariate return period (MRP)‐based record selection methodology to further improve the multivariate hazard consistency over a vector of intensity measures (IMs). Unlike the traditional univariate return period anchored on a scalar IM, MRP generalizes the return period concept by accommodating the joint rate of exceedance of a vector of IMs, thereby providing more holistic seismic hazard characterization. By leveraging MRP in linking the seismic hazard to a vector IMs, the proposed MRP‐based ground motion selection methodology for the first time offers a mathematically rigorous yet practical solution for multivariate hazard consistency in ground motion selection. The merit of the MRP‐based ground motion selection is demonstrated by comparing the resulting target spectra and seismic demand estimates for several case‐study structures with other state‐of‐the‐art ground motion selection alternatives. From the results, the MRP‐based ground motion selection employing Kendall's distribution function turns out to be a promising alternative, offering favorable new features including (a) moderate target spectra intensity and moderately low target spectra standard deviation; (b) superior convergence with the increase of the conditioning IM dimension and ability to approximate higher‐dimensional multivariate hazard consistency with lower dimensional conditioning IMs; and (c) capability to realistically capture the multimodal spectral shape owing to the incorporation of multivariate Gaussian mixture distribution in generating target spectra.
Multivariate return period‐based ground motion selection for improved hazard consistency over a vector of intensity measures
Du, Ao (author) / Padgett, Jamie E. (author)
Earthquake Engineering & Structural Dynamics ; 50 ; 415-435
2021-02-01
21 pages
Article (Journal)
Electronic Resource
English