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A Holistic Review of GM/IM Selection Methods from a Structural Performance-Based Perspective

Author

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  • Mohsen Zaker Esteghamati

    (Department of Civil and Environmental Engineering, Utah State University, Logan, UT 84322, USA)

Abstract

Current fully probabilistic approaches to performance-based earthquake engineering describe structures’ behavior under a wide range of seismic hazard levels. These approaches require a detailed representation of ground motion (GM) uncertainty at all considered hazard levels, yet different GM selection methods lead to different estimations of structural performance. This paper presents a holistic review of the current practices in GM representation and selection for structural demand analysis through a performance-based lens. The multidisciplinary nature of GM selection, ranging from earth science to engineering seismology and statistics, has created a preponderance of literature to find the best practice for probabilistic assessment of structures in terms of computational efficiency and statistical accuracy. Many of these studies focus individually on GM selection or structural analysis, and the relatively scarce review papers either focus on code-based GM selection or do not specifically address risk-based evaluations by overlooking the interaction between GM selection and structural analysis. This paper aims to aid researchers in selecting appropriate GMs as part of a statistically valid and robust probabilistic demand analysis without performing an exhaustive literature review. Discussion on the available computational tools and their trade-offs for risk-based assessment of single structures is provided. While the problem-specific nature of GM selection means that no pre-selected set of GM/IM is applicable to all cases, the comprehensive narrative of this paper is expected to aid analysts in reaching a more informed decision.

Suggested Citation

  • Mohsen Zaker Esteghamati, 2022. "A Holistic Review of GM/IM Selection Methods from a Structural Performance-Based Perspective," Sustainability, MDPI, vol. 14(20), pages 1-26, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:12994-:d:939074
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