A method is described for quantitatively identifying ground motions containing strong velocity pulses, such as those caused by near-fault directivity. The approach uses wavelet analysis to extract the largest velocity pulse from a given ground motion. The size of the extracted pulse relative to the original ground motion is used to develop a quantitative criterion for classifying a ground motion as "pulselike." The criterion is calibrated by using a training data set of manually classified ground motions. To identify the subset of these pulselike records of greatest engineering interest, two additional criteria are applied: the pulse arrives early in the ground motion and the absolute amplitude of the velocity pulse is large. The period of the velocity pulse (a quantity of interest to engineers) is easily determined as part of the procedure, using the pseudoperiods of the basis wavelets. This classification approach is useful for a variety of seismology and engineering topics where pulselike ground motions are of interest, such as probabilistic seismic hazard analysis, groundmotion prediction ("attenuation") models, and nonlinear dynamic analysis of structures. The Next Generation Attenuation (NGA) project ground motion library was processed using this approach, and 91 large-velocity pulses were found in the faultnormal components of the approximately 3500 strong ground motion recordings considered. It is believed that many of the identified pulses are caused by near-fault directivity effects. The procedure can be used as a stand-alone classification criterion or as a filter to identify ground motions deserving more careful study.

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Estimation of fragility functions using dynamic structural analysis is an important step in a number of seismic assessment procedures. This paper discusses the applicability of statistical inference concepts for fragility function estimation, describes appropriate fitting approaches for use with various structural analysis strategies, and studies how to fit fragility functions while minimizing the required number of structural analyses. Illustrative results show that multiple stripe analysis produces more efficient fragility estimates than incremental dynamic analysis for a given number of structural analyses, provided that some knowledge of the building's capacity is available prior to analysis so that relevant portions of the fragility curve can be approximately identified. This finding has other benefits, given that the multiple stripe analysis approach allows for different ground motions to be used for analyses at varying intensity levels, to represent the differing characteristics of low-intensity and high-intensity shaking. The proposed assessment approach also provides a framework for evaluating alternate analysis procedures that may arise in the future.

SUMMARYSelection of earthquake ground motions is considered with the goal of accurately estimating the response of a structure at a speciÿed ground motion intensity, as measured by spectral acceleration at the ÿrst-mode period of the structure, Sa(T 1 ). Consideration is given to the magnitude, distance and epsilon ( ) values of ground motions. First, it is seen that selecting records based on their values is more e ective than selecting records based on magnitude and distance. Second, a method is discussed for ÿnding the conditional response spectrum of a ground motion, given a level of Sa(T 1 ) and its associated mean (disaggregation-based) causal magnitude, distance and value. Records can then be selected to match the mean of this target spectrum, and the same beneÿts are achieved as when records are selected based on . This mean target spectrum di ers from a Uniform Hazard Spectrum, and it is argued that this new spectrum is a more appropriate target for record selection. When properly selecting records based on either spectral shape or , the reductions in bias and variance of resulting structural response estimates are comparable to the reductions achieved by using a vector-valued measure of earthquake intensity.

Dynamic structural analysis often requires the selection of input ground motions with a target mean response spectrum. The variance of the target response spectrum is usually ignored or accounted for in an ad hoc manner, which can bias the structural response estimates. This manuscript proposes a computationally efficient and theoretically consistent algorithm to select ground motions that match the target response spectrum mean and variance. The selection algorithm probabilistically generates multiple response spectra from a target distribution, and then selects recorded ground motions whose response spectra individually match the simulated response spectra. A greedy optimization technique further improves the match between the target and the sample means and variances. The proposed algorithm is used to select ground motions for the analysis of sample structures in order to assess the impact of considering ground-motion variance on the structural response estimates. The implications for code-based design and performance-based earthquake engineering are discussed.