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Evaluation of the requirement of complex functional forms in ground-motion prediction equations in terms of distance metrics: Regional and global applications

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Abstract (EN)

The Turkish and global scale ground-motion databases are firstly compiled in the scope of the study. Joyner-Boore (RJB) and closest distance to the fault rupture (RRUP) ground-motion prediction equations (GMPEs) are developed from the Turkish ground-motion database and their comparisons are performed under different earthquake scenarios. In the GMPEs application conducted in Turkey and Europe, the RJB distance metric is preferred by a significant part of the researchers because of its simple calculation steps. In the light of comparisons conducted in this study, suitability of the RRUP distance metric that is not preferred in Turkey and Europe is evaluated for its potential use for Turkey. In addition, statistical dependence of the selected RJB and developed RRUP GMPEs to the hypocentral depth term are examined by the help of residual analysis. In the next stage of the study, the evaluations of the basic and complex functional form GMPEs are conducted by employing global ground-motion database. In this stage, the GMPEs in complex functional form are developed by firstly adding the hypocentral depth term and dip terms, and then the hanging wall terms to the basic functional form. In this vein, advantages and disadvantages of complex functional form, the existence of any difference related the definition of RJB and RRUP distances, and the existence of epistemic uncertainty depending on the distance types are evaluated. As a result, development of the RJB based models can be considered as more sufficient with respect to the RRUP based GMPEs. In addition, it is observed that the median predictions and standard deviations of GMPEs include epistemic uncertainty depending on the selected distance metric.

Author

Oğuz Salih Okçu

How to Cite

Oğuz Salih Okçu (Master Thesis). Evaluation of the requirement of complex functional forms in ground-motion prediction equations in terms of distance metrics: Regional and global applications, 2020, Hacettepe University.

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