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A ground motion prediction equation for novel peak ground fractional order response intensity measures

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Abstract

Peak ground fractional order responses (PGRα) as a generalization of conventional seismic intensity measures (IMs) such as peak ground acceleration (PGA) and peak ground velocity (PGV) can better predict the seismic performance of structural systems. This paper proposes the first ground motion prediction equation (GMPE) for PGRα for active shallow crustal regions using a subset of the PEER NGA-West2 ground motion database. The model development database consists of 4491 accelerograms from 82 different earthquakes in California with the magnitude and rupture distance ranges of Mw 4.0–7.9 and RRUP 0–300 km, respectively. PGRα intensity measures are computed from the modified Oustaloup’s recursive approximation to Caputo’s definition of differintegral operator. The main functional form of the predictive model is decided by implementing statistical ground motion data-driven testing methods such as the likelihood approach and Euclidean distance concept. The final functional form of the predictive model accounts for magnitude, distance, style-of-faulting, linear and nonlinear site, hanging wall, basin response, and anelastic distance attenuation effects, and models the aleatory variability with respect to Mw and VS30. The final predictive model produces PGA (α = 0), PGV (α = −1), and peak ground fractional order responses at 19 different α values ranging from −0.05 to −0.95 for the average horizontal component. The proposed predictive model draws estimates of ground motion amplitudes that are consistent with those from the NGA-West2 models for PGA and PGV for sample earthquake scenarios. Moreover, it can offer a basis for predictive modeling of peak ground fractional order response quantities for performance assessment of structures and infrastructures across a region.

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Acknowledgements

The authors gratefully acknowledge the support of this research by the National Science Foundation of United States through Grants 1462177 and 1462183. The first author of this article was also supported by the Department of Science Fellowships and Grant Programs of the Scientific and Technological Research Council of Turkey (TUBITAK) for conducting his post-doctoral research studies at Rice University. Any opinions, findings and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the sponsors. The authors thank Professors Sinan Akkar and M. Abdullah Sandıkkaya for providing random effects regression algorithms. The authors are also very grateful to two anonymous reviewers for their constructive feedback on the original version of this paper.

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Authors and Affiliations

  1. Department of Civil Engineering, TED University, Ziya Gökalp Cad. No: 48, 06420, Çankaya, Ankara, Turkey

    Özkan Kale

  2. Department of Civil and Environmental Engineering, Rice University, 6100 Main St., MS-318, Houston, TX, 77005, USA

    Jamie E. Padgett

  3. Department of Civil, Environmental, and Geodetic Engineering, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Ave, Columbus, OH, 43210, USA

    Abdollah Shafieezadeh

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  1. Özkan Kale
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  2. Jamie E. Padgett
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  3. Abdollah Shafieezadeh
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Correspondence to Özkan Kale.

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Kale, Ö., Padgett, J.E. & Shafieezadeh, A. A ground motion prediction equation for novel peak ground fractional order response intensity measures. Bull Earthquake Eng 15, 3437–3461 (2017). https://doi.org/10.1007/s10518-017-0122-x

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