Abstract
An efficient algorithm is presented to simulate site-based ground motions using Dabaghi and Der Kiureghian (2018) and Rezaeian and Der Kiureghian (2012) that achieve target ground motion intensity measures between a range of periods. The proposed algorithm uses predictive relations between the model parameters (MP) and the RotD50 spectral acceleration spectrum, RotD50Sa,Tar(T), of the site-based ground motions. A correlation structure is estimated to account for the cross-spectral correlations between the periods. The algorithm requires a set of five seismic event parameters (including Magnitude, Rupture Distance, Soil Shear-Wave Velocity, Fault Mechanism, Fault Geometry) and the target spectrum (including the range of periods whose corresponding spectral accelerations are required to be matched). The proposed algorithm uses event parameters to generate appropriate sets of model parameters. Using the developed predictive relations and correlation structure, the algorithm then carefully selects the model parameters that are statistically likely to generate a ground motion waveform possessing the required target spectrum between the inputted range of periods. Unlike the traditional scaling methods, this algorithm does not alter the amplitude, time- and frequency-domain characteristics of the ground motions; hence, it leads to realistic simulated ground motions. The algorithm is used to generate ground motions for response assessment of a two-span ordinary box-girder bridge structure, and the results are compared against the traditional methods of selecting and scaling recorded ground motions. This demonstration indicates that the conventional methods of selecting and scaling recorded ground motions lead to a bias in the bridge's responses and the proposed algorithm leads to statistical consistency in the results.
| Original language | English |
|---|---|
| Pages (from-to) | 3532-3549 |
| Number of pages | 18 |
| Journal | Earthquake Engineering and Structural Dynamics |
| Volume | 50 |
| Issue number | 13 |
| DOIs | |
| Publication status | Published - 25 Oct 2021 |
| Externally published | Yes |
Bibliographical note
Funding Information:The authors thank the University of California‐Irvine for providing financial aid through Henry Samueli Endowed Fellowship and Graduate Dean's Dissertation Fellowship to the first author. The authors thank Dr. Mayssa Dabaghi for providing her assistance in working with the DRD simulation tool and providing valuable comments on this study. The authors would also like to acknowledge the efforts of undergraduate student Jia (Jerry) Shen, who assisted in data organization and preliminary analysis.
Funding Information:
The authors thank the University of California-Irvine for providing financial aid through Henry Samueli Endowed Fellowship and Graduate Dean's Dissertation Fellowship to the first author. The authors thank Dr. Mayssa Dabaghi for providing her assistance in working with the DRD simulation tool and providing valuable comments on this study. The authors would also like to acknowledge the efforts of undergraduate student Jia (Jerry) Shen, who assisted in data organization and preliminary analysis.
Publisher Copyright:
© 2021 John Wiley & Sons Ltd.