Summary A parameterized stochastic model of near‐fault ground motion in two orthogonal horizontal directions is developed. The major characteristics of recorded near‐fault ground motions are represented. These include near‐fault effects of directivity and fling step; temporal and spectral non‐stationarity; intensity, duration, and frequency content characteristics; directionality of components; and the natural variability of ground motions. Not all near‐fault ground motions contain a forward directivity pulse, even when the conditions for such a pulse are favorable. The proposed model accounts for both pulse‐like and non‐pulse‐like cases. The model is fitted to recorded near‐fault ground motions by matching important characteristics, thus generating an ‘observed’ set of model parameters for different earthquake source and site characteristics. A method to generate and post‐process synthetic motions for specified model parameters is also presented. Synthetic ground motion time series are generated using fitted parameter values. They are compared with corresponding recorded motions to validate the proposed model and simulation procedure. The use of synthetic motions in addition to or in place of recorded motions is desirable in performance‐based earthquake engineering applications, particularly when recorded motions are scarce or when they are unavailable for a specified design scenario. Copyright © 2016 John Wiley & Sons, Ltd.

Summary A procedure to generate horizontal pairs of synthetic near‐fault ground motion components for specified earthquake source and site characteristics is presented. Some near‐fault ground motions contain a forward directivity pulse; others do not, even when the conditions for such a pulse are favorable. The proposed procedure generates pulse‐like and non‐pulse‐like motions in appropriate proportions. We use our recent stochastic models of pulse‐like and non‐pulse‐like near‐fault ground motions that are formulated in terms of physically meaningful parameters. The parameters of these models are fitted to databases of recorded pulse‐like and non‐pulse‐like motions. Using these empirical “observations,” predictive relations are developed for the model parameters in terms of the earthquake source and site characteristics (type of faulting, earthquake magnitude, depth to top of rupture plane, source‐to‐site distance, site characteristics, and directivity parameters). The correlation coefficients between the model parameters are also estimated. For a given earthquake scenario, the probability of occurrence of a directivity pulse is first computed; pulse‐like and non‐pulse‐like motions are then simulated according to the predicted proportions using the empirical predictive models. The resulting time series are realistic and reproduce important features of recorded near‐fault ground motions, including the natural variability. Moreover, the statistics of their elastic response spectra agree with those of the NGA‐West2 dataset, with the additional feature of distinguishing between pulse‐like and non‐pulse‐like cases and between forward and backward directivity scenarios. The synthetic motions can be used in addition to or in place of recorded motions in performance‐based earthquake engineering, particularly when recorded motions are scarce.

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This study presents an efficient algorithm that can be used to simulate ground motion waveforms using the site-based approach developed by Dabaghi and Der Kiureghian, and Rezaeian and Der Kiureghian that not only correspond to a specified seismic scenario (e.g. magnitude, distance, site conditions) but are also certain to achieve a target ground motion intensity measure within a narrow range. The suggested algorithm alleviates the need to scale simulated ground motions generated using the above-mentioned site-based approach; the resulting hazard-targeted simulated ground motions have consistent amplitude and time- and frequency-domain characteristics, which are required for proper seismic demand analysis of structures. The proposed algorithm takes as input a set of seismic Event Parameters and the target hazard intensity measure [Formula: see text] and generates a corresponding set of Model Parameters (i.e. input to the site-based ground motion simulation model). These Model Parameters are then used to simulate ground motion waveforms that not only represent the set of input Event Parameters ( Mw, Rrup, Vs30) but also maintain the target [Formula: see text]. To generate the set of Model Parameters, predictive relations between the Model Parameters and [Formula: see text] of ground motions are developed. Among the Model Parameters, the ones classified as important by statistical procedures (such as Random Forests, Forward Selection) are used to develop the predictive relations. The developed relations are then validated against a large dataset of recorded ground motions. The final implementation is provided in terms of graphic-user interface (GUI) called “Hazard-Targeted Time-Series Simulator” ( HATSim), which efficiently simulates site-based ground motions with minimum inputs.

This paper examines the behavior of reinforced concrete shear wall buildings subjected to strong earthquake ground motions, with a focus on collapse performance. The effect of varying the number of stories, shear wall and boundary element dimensions, and reinforcement detailing on the seismic collapse fragility is investigated. The buildings are seismically designed based on the ASCE 7-10 and ACI 318-14 codes with additional provisions for capacity design and dynamic amplification. The shear walls are modeled using the shear-flexure interaction multiple vertical line element model with nonlinear hysteretic material models. Incremental dynamic analysis is performed to simulate the structural collapse of the two-dimensional building models subjected to the FEMA-P695 set of far field recorded ground motions scaled to increasing intensity values. For each building, a lognormal collapse fragility curve is fitted to the results. A collapse assessment of the studied buildings shows how the seismic performance is significantly affected by the varied parameters.