An Empirically Calibrated Framework for Including the Effects of Near-Fault Directivity in Probabilistic Seismic Hazard Analysis

Abstract

Forward directivity effects are known to cause pulselike ground motions at near-fault sites. We propose a comprehensive framework to incorporate the effects of near-fault pulselike ground motions in probabilistic seismic hazard analysis (PSHA) computations. Also proposed is a new method to classify ground motions as pulselike or non-pulselike by rotating the ground motion and identifying pulses in all orientations. We have used this method to identify 179 recordings in the Next Generation Attenuation (NGA) database , where a pulselike ground motion is observed in at least one orientation. Information from these 179 recordings is used to fit several data-constrained models for predicting the probability of a pulselike ground motion occurring at a site, the orientations in which they are expected relative to the strike of the fault, the period of the pulselike feature, and the response spectrum amplification due to the presence of a pulselike feature in the ground motion. An algorithm describing how to use these new models in a modified PSHA computation is provided. The proposed framework is modular, which will allow for modification of one or more models as more knowledge is obtained in the future without changing other models or the overall framework. Finally, the new framework is compared with existing methods to account for similar effects in PSHA computation. Example applications are included to illustrate the use of the proposed framework, and implications for selection of ground motions for analysis of structures at near-fault sites are discussed.

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“…This is quantified by the indicator I P, which expresses the probability of a pulse (with a value of 1 indicating the existence of a pulse and 0 its absence), as recommended by Shahi and Baker. [44] The seismic hazard is assumed to originate from strike-slip faults, with a probability model formulated as …”

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“…Different IM are used in these equations (in this work S a (T 1 ) is adopted). PSHA has been recently modified to account for near source conditions, i.e., Near-source Probabilistic Seismic Hazard Analysis (NS-PSHA); more details, including implementation and applications, can be found in [2,[45][46][47][48][49]. According to this methodology, Equation (4) is adjusted to account for potential near-source directivity by an additional term, Z, which defines the site-to-source geometry: …”

“…The probability of a pulse occurring is a function of site-to-source geometry and decreases with distance from the fault and for shorter fault rupture lengths [2,46]. The pulse period distribution is a function of earthquake magnitude, with larger magnitude events usually causing longer pulse periods [46,50].…”

“…The location of earthquake epicenters is uniformly distributed along the fault while six sites with site-to-source distances equal to 5, 10 and 15 km at the end ("End-of-Fault" sites) and midpoint ("Midfault" sites) of the fault line are considered in this study (Figure 6(a)). The probability of a pulse occurring is computed by using the model in [2] and depends, in the case of a SS rupture, on rupture-to-site distance, R, the distance from the epicenter to the site measured along the rupture direction, s, and angle between the fault strike and the path from the epicenter to the site,  (a similar model is introduced in [46]). As noted in [49], a deterministic relationship between these parameters and rupture length, position of the rupture on the fault and epicenter location exist, allowing to easily simulate the uncertainty involved for the hazard computations.…”

“…Finally, the pulse period prediction is based on the empirical model in [47], although others are available (e.g., [46]). More details for the NS-PSHA calculation used here, including the GMPE modification to account for the 'bump' of spectral ordinates around the pulse period, can be found in [48].…”