A model for estimating horizontal aftershock ground motions for active crustal regions. Issue 92 (January 2017)

• Record Type: Journal Article
• Authors: Kim, Byungmin; Shin, Moochul
• Is Part Of: Soil dynamics and earthquake engineering. Issue 92(2017)
• Page Start: 165
• Page End: 175
• Publication Date: 2017-01
• Subjects: Aftershock -- Active crustal region -- Ground motion prediction -- NGA-West2 -- Spectral acceleration; Soil dynamics -- Periodicals; Earthquake engineering -- Periodicals; Sols -- Dynamique -- Périodiques; Génie parasismique -- Périodiques; 624.176205
• DOI: 10.1016/j.soildyn.2016.09.040
• Languages: English
• ISSNs: 0267-7261

Abstract

Abstract: Inconsistent observations on the characteristics of ground motions from aftershocks have been found, while there is increasing attention to effects of aftershock ground motions on structural behaviors. This study examines differences in ground motions from main shock and aftershock earthquakes using the NGA-West2 database, and propose an empirical model to estimate the average horizontal components of peak ground acceleration ( PGA ), and peak ground velocity ( PGV ), and 5% damped pseudo spectral acceleration ( PSA ) at various spectral periods of aftershock earthquakes for tectonically active crustal regions, as a function of aftershock to main shock magnitude ratio, distance ratio, and time-averaged shear-wave velocity in the upper 30 m of soil deposits ( V S 30 ). Spectral accelerations from aftershock earthquakes are smaller than those from main shock earthquakes given the same magnitude, especially at short periods. Performance of the proposed model is evaluated using a mixed-effects residuals analysis. Period-dependent standard deviation of residuals is also presented. Highlights: An empirical model to estimate aftershock ground motions for active crustal regions is developed. The developed model is in a function of magnitude ratio, distance ratio, and VS30 . The NGA-West2 database is used for main shock and aftershock ground motion records. Performance of the developed model is evaluated using mixed-effects analyses.