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 presented.) 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 presented.). To generate the set of Model Parameters, predictive relations between the Model Parameters and (Formula presented.) 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.
Bibliographical noteFunding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is based on work supported by the California Department of Transportation (Caltrans) under Award No. 65A0647. This financial support is gratefully acknowledged. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of sponsors.
© The Author(s) 2020.