Abstract
Online Material: Tables and figures of GMPE parameters, NGA‐East database summary statistics, mean residuals, skewness and kurtosis, results from log‐likelihood analysis, and ranking. A number of ground‐motion prediction equations (GMPEs) have been introduced in recent years that are redefining the state of practice for probabilistic seismic‐hazard analysis (PSHA) in many earthquake‐prone regions worldwide. For example, the Next Generation Attenuation (NGA)‐East is developing a new ground‐motion characterization (GMC) model for the central and eastern North American (CENA) region. The GMC model will consist of a set of new GMPEs for median and standard deviation of ground motions and their associated weights in the logic trees for use in PSHA. An example is the empirical GMPE by Al Noman (2013). GMPEs are developed for specific tectonic environments using multivariate regression on ground‐motion databases, and the relationships are updated as more earthquake data are obtained (Kramer, 1996; Abrahamson and Shedlock, 1997). Because of the improvement of seismological networks, and increasing size and quality of ground‐motion databases, the number of proposed ground‐motion models has increased significantly in the last decade to reflect the seismological features of the seismic‐prone regions worldwide, that is, Douglas (2011) gives 289 empirical GMPEs for PGA and 188 models for the prediction of elastic response spectral ordinates. The NGA‐East project has developed an updated database of CENA ground motions (Cramer et al. , 2009, 2010, 2013) containing over 11,000 records and covering distance and magnitude ranges of 1–3500 km and M w 2.2–7.6, but mostly less than M w 6.0 (Fig. 1). The selection of candidate GMPEs, especially the assignment of logic‐tree weights, and selecting appropriate predictive models to calculate hazard in a site (or a region) of interest has become a popular topic in engineering seismology. The ground shaking in the target region must be well reflected …
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.