Parametric Statistical Generalization of Uniform-Hazard Earthquake Ground Motions

Abstract

Sets of ground motion records used for seismic hazard analyses typically have intensity measures corresponding to a particular hazard level for a site (perhaps conditioned on a particular intensity value and hazard). In many cases the number of available ground motions that match required spectral ordinates and other criteria (such as duration, fault rupture characteristics, and epicentral distance) may not be sufficient for high-resolution seismic hazard analysis. In such cases it is advantageous to generate additional ground motions using a parameterized statistical model calibrated to records of the smaller data set. This study presents a statistical parametric analysis of ground motion data sets that are classified according a seismic hazard level and a geographic region, and which have been used extensively for structural response and seismic hazard analyses. Parameters represent near-fault effects such as pulse velocity and pulse period, far field effects such as velocity amplitude and power spectral attributes, and envelope characteristics. A systematic fitting of parameterized pulse functions to the individual ground motion records, of parameterized envelopes to individual instantaneous ground motion amplitudes, and of parameterized power spectral density functions to averaged power spectra result in probability distributions for ground motion parameters representative of particular seismic hazard levels for specific geographical regions. This methodology presents a means to characterize the variability in a set of ground motions records in terms of physically meaningful parameters.

Quantitative Identification of Near-Fault Pulse-Like Ground Motions Based on Energy

“…In the past, numerous researchers have tried to capture the above pulse-like feature by different approaches, in which simple pulse models are commonly used (Hall et al, 1995;Makris, 1997;Alavi and Krawinkler, 2001;Mavroeidis and Papageorgiou, 2003;Bray and Rodriguez-Marek, 2004;He and Agrawal, 2008;Dickinson and Gavin, 2011;Tang and Zhang, 2011). These models include the rectangular displacement pulses (Hall et al, 1995), piece-wise linear triangular velocity pulses (Alavi and Krawinkler, 2001), sinusoidal velocity pulses (Sasani and Bertero, 2000;Bray and *Also at Institute of Engineering Mechanics, China Earthquake Administration, No.…”

Would RC wide-beam buildings in Spain have survived Lorca earthquake (11-05-2011)?

“…PI is pulse index [Baker 2007], which ranges between 0 and 1; records with scores above 0.85 and below 0.15 are classified as pulses and non-pulses, respectively. E p is relative pulse energy [Zhai et al 2013], representing portion of ground motion energy that corresponds to pulse; pulse is extracted by peak-point method [Dickinson, Gavin 2011]. Values of E p greater than 0.3 correspond to pulse-like records and values equal to or below 0.3 are ambiguous.…”

A non-separable stochastic model for pulse-like ground motions

“…Alavi & Krawinkler 2001) or of more involved oscillatory functions with decaying envelopes: "wavelets" (e.g. Mavroeidis & Papageorgiou 2003, He & Agrawal 2008, Moustafa & Takewaki 2010, Dickinson & Gavin 2011. The underlying parameters used to define these functions are related to salient pulse features such as the pulse peak value (amplitude) and its time location, the "dominant" pulse frequency or period, and the number of pulse cycles (oscillations).…”

“…These parameters are obtained by "fitting" operations to field recorded GMs (e.g. Mavroeidis & Papageorgiou 2003, Dickinson & Gavin 2011 or by joint time-frequency signal analyses techniques used as "matched filtering" tools to detect/extract pulses from recorded GMs. For instance, Baker (2007) has considered the application of the discrete wavelet transform using a Daubechies wavelet family for pulse identification, extraction, and characterization, while Vasileiou and Makris (2012) considered a heuristic form of the Gaussian chirplet transform for the purpose (see Spanos et al 2007 and references therein).…”

“…Commonly, the HF content is modeled by standard approaches used for modeling and simulating pulse-free GMs (e.g. Mavroeidis & Papageorgiou 2003, Fu & Menun 2004, Dickinson & Gavin 2011, Dabaghi et al 2011. Further, with very few exceptions (e.g.…”