摘要
Research Article| March 05, 2019 Incorporating Nonergodic Path Effects into the NGA‐West2 Ground‐Motion Prediction Equations Nicolas M. Kuehn; Nicolas M. Kuehn aB. John Garrick Institute for the Risk Sciences, University of California, Los Angeles, Engineering VI 5th Floor, 404 Westwood Plaza, Los Angeles, California 90095 U.S.A., kuehn@ucla.edudAlso at Richmond Field Station, Building 451, Office 22, 1301 S. 46th Street, Richmond, California 94804‐4698 U.S.A. Search for other works by this author on: GSW Google Scholar Norman A. Abrahamson; Norman A. Abrahamson bDepartment of Civil Engineering, University of California, Berkeley, 447 Davis Hall, Berkeley, California 94720‐1792 U.S.A. Search for other works by this author on: GSW Google Scholar Melanie A. Walling Melanie A. Walling cGeoEngineers, Inc., 17425 NE Union Hill Road, Suite 250, Redmond, Washington 98052 U.S.A. Search for other works by this author on: GSW Google Scholar Bulletin of the Seismological Society of America (2019) 109 (2): 575–585. https://doi.org/10.1785/0120180260 Article history first online: 05 Mar 2019 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Nicolas M. Kuehn, Norman A. Abrahamson, Melanie A. Walling; Incorporating Nonergodic Path Effects into the NGA‐West2 Ground‐Motion Prediction Equations. Bulletin of the Seismological Society of America 2019;; 109 (2): 575–585. doi: https://doi.org/10.1785/0120180260 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search Abstract Typical ground‐motion prediction equations (GMPEs) do not account for systematic path effects, which leads to an overestimation of aleatory variability. We provide an update to the Californian GMPE model of Abrahamson et al. (2014) that explicitly accounts for path effects in California by replacing the anelastic attenuation coefficient with a regionally varying one. The updated attenuation model is based on the approach of Dawood and Rodriguez‐Marek (2013). Accounting for path effects leads to a smaller value of the aleatory variability, and results in different median predictions, depending on source and site location. The model is cast as a Bayesian hierarchical model, which allows one to capture the epistemic uncertainties in the anelastic attenuation coefficients. We show that it is important to account for the uncertainty in the attenuation coefficients when using the model for prediction. The differences in attenuation decrease with increasing spectral period. The updated attenuation model is developed with respect to the GMPE of Abrahamson et al. (2014) but can be easily extended for other models and other regions as well. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.