A Computational Tool for Ground-Motion Simulations Incorporating Regional Crustal Conditions

Author:

Tang Yuxiang12,Lam Nelson23,Tsang Hing-Ho34

Affiliation:

1. School of Civil Engineering, Guangzhou University, Guangzhou, China

2. Department of Infrastructure Engineering, The University of Melbourne, Melbourne, Victoria, Australia

3. Bushfire and Natural Hazards Cooperative Research Centre, Melbourne, Victoria, Australia

4. Centre for Sustainable Infrastructure, Swinburne University of Technology, Melbourne, Australia

Abstract

Abstract This article introduces a computational tool, namely ground-motion simulation system (GMSS), for generating synthetic accelerograms based on stochastic simulations. The distinctive feature of GMSS is that it has two independently developed upper-crustal models (expressed in the form of shear-wave velocity profiles), which have been built into the program for deriving the frequency-dependent crustal factors, and one of these models was originally developed by the authors. GMSS also has provisions to allow the user to specify their own preferred crustal profile. Sufficient details of both crustal models (forming part of the seismological model) and the accelerogram simulation methodology are presented herein in one article, to allow any person who has programming skills (on a user-friendly platform such as MATLAB, see Data and Resources), to develop their computational tools to implement any further innovations in crustal modeling for direct engineering applications. Crustal properties deep into bedrock can only be accounted for implicitly by conventional ground-motion prediction equation (GMPE) as much depends on the region where the ground motion was recorded. This limitation of existing GMPEs poses a challenge to engineering in regions that are not well represented by any strong-motion database. Toward the end of this article, readers are enlightened with the potential transdisciplinary utility of using GMSS, to facilitate the retrieval and scaling of accelerograms sourced from a database of real earthquake records through the construction of a conditional mean spectrum.

Publisher

Seismological Society of America (SSA)

Subject

Geophysics

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