In:
Earthquake Spectra, SAGE Publications, Vol. 38, No. 4 ( 2022-11), p. 2371-2397
Abstract:
Empirical ground-motion prediction equations (GMPEs) such as the Next Generation Attenuation-West2 (NGA-West2) GMPEs are limited in the number of recordings on hard-rock stations used to develop the models. Therefore, the site response scaling in the GMPEs cannot be reliably extrapolated to hard-rock conditions. The state of practice for the development of hard-rock adjustment factors involves the use of analytical methods that typically assign small values to the small-strain damping parameter ([Formula: see text]) for hard-rock sites resulting in large scaling factors at short periods. Alternatively, the hard-rock scaling factors developed in Ktenidou and Abrahamson (KA16) based on empirical ground-motion data are used. These empirical factors, developed for a broad rock site category, show that the average hard-rock scaling factors observed in ground-motion data are small in amplitude contrary to the large factors typically obtained from analytical studies. The empirically derived KA16 factors also suffer from limitations due to the relatively small number of rock sites in the data set and do not distinguish between different hard-rock conditions. To address the shortcomings in the current state of practice, we present a methodology to develop linear site adjustment factors to adjust the NGA-West2 GMPEs from V S30 of 760 m/s to target hard-rock site conditions with V S30 ranging from 1000 to 2200 m/s. These factors are analytically derived using the inverse random vibration theory (IRVT) approach of Al Atik et al. but with inputs constrained using the empirical KA16 factors and normalized to the scaling of the NGA-West2 GMPEs for V S30 of 1000 m/s. The proposed factors merge the results of the NGA-West2 site response scaling for V S30 ≤ 1000 m/s with the KA16 hard-rock category factors to produce a site factor model that is a continuous function of V S30 . The epistemic uncertainty of these factors is evaluated.
Type of Medium:
Online Resource
ISSN:
8755-2930
,
1944-8201
DOI:
10.1177/87552930221092467
Language:
English
Publisher:
SAGE Publications
Publication Date:
2022
detail.hit.zdb_id:
2183411-8
SSG:
16,13
