Abstract

The choice of spectral targets for ground motion selection has a strong impact on structural demands resulting from nonlinear time history analysis. In particular, the conditional mean spectrum (CMS) has been recognized as an appealing alternative to the uniform hazard spectrum (UHS) as a spectral target due to the former’s more realistic shape and reduced conservatism. Using a tall building case study in a high-seismicity region, this paper evaluates the building demands generated by UHS- and CMS-based selection procedures. Theoretically rigorous implementation of CMS-based selection using 17 different conditioning periods is shown to reduce maximum considered earthquake (MCE)–level demands on the case study building by 9%–35% relative to UHS-based selection. Furthermore, the simplified CMS-based procedure in the building code with apt choice of only two conditioning periods is found to satisfactorily capture the demands generated by the theoretically rigorous approach. Findings also highlight the degree of sensitivity of CMS-based results to the choice of conditioning periods and to enforcement of lower bounds on spectral targets, such as 75% of the UHS. The presented analysis procedure can be replicated in future studies for explicit evaluation of simplified CMS ground motion selection in other structural systems or analysis cases.

Practical Applications

Since its introduction to the building code, the alternative, conditional mean spectrum-based method for ground motion selection has gained traction among practitioners due to its reduced conservatism relative to traditional selection methods. To simplify the implementation of conditional mean spectra in practice, the building code alternative method requires a minimum of only two target spectra be used, so long as their envelope satisfies a lower bound within a specified period range. However, there are few quantitative studies of the impacts of these simplifications on the resulting building demands. In this study, we demonstrate how building demands vary when a tall building in a high-seismicity region is analyzed using either a traditional or a conditional mean spectrum-based selection approach. We find that using two reasonable target spectra in accordance with the alternative method produces acceptable building demands as compared to the demands obtained from performing exhaustive nonlinear analysis with a large number of target spectra. Furthermore, we illustrate how different choices of conditional mean spectrum targets maximize different types of building demands (e.g., interstory drift, base shear, floor acceleration) and how some types of demands are more sensitive to this choice than others. This work provides a procedure for evaluating conditional mean spectrum-based ground motion selection that can be replicated in the future for other buildings or structural systems.

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Data Availability Statement

Some or all data, models, or code generated or used during the study are available in a repository online (Bassman 2022).

Acknowledgments

The authors thank Stanford University and the Stanford Research Computing Center for providing high-performance computing resources on the Sherlock cluster that were used for running structural analysis. Thanks to Peter Powers, Sanaz Rezaeian, and Nicolas Luco at the USGS for providing seismic hazard disaggregation data. Thanks to John Hooper and the team at Magnusson Klemencic Associates as well as two anonymous reviewers for insightful comments and discussion that improved the quality of this paper.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 148Issue 11November 2022

History

Received: Jan 18, 2022
Accepted: May 26, 2022
Published online: Aug 29, 2022
Published in print: Nov 1, 2022
Discussion open until: Jan 29, 2023

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Graduate Student Researcher, Dept. of Civil and Environmental Engineering, Stanford Univ., Stanford, CA 94305 (corresponding author). ORCID: https://orcid.org/0000-0001-5784-1933. Email: [email protected]
Kuanshi Zhong, A.M.ASCE [email protected]
Postdoctoral Researcher, Dept. of Civil and Environmental Engineering, Stanford Univ., Stanford, CA 94305. Email: [email protected]
Professor, Dept. of Civil and Environmental Engineering, Stanford Univ., Stanford, CA 94305. ORCID: https://orcid.org/0000-0003-2744-9599. Email: [email protected]

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  • Spectrum-matched ground motion selection method based on Siamese Convolutional Neural Networks, Soil Dynamics and Earthquake Engineering, 10.1016/j.soildyn.2022.107515, 163, (107515), (2022).

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