Skip to main content Accessibility help
×
Home
Hostname: page-component-7ccbd9845f-w45k2 Total loading time: 2.292 Render date: 2023-01-28T08:14:57.281Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue true

References

Published online by Cambridge University Press:  14 December 2021

Jack Baker
Affiliation:
Stanford University, California
Brendon Bradley
Affiliation:
University of Canterbury, Christchurch, New Zealand
Peter Stafford
Affiliation:
Imperial College of Science, Technology and Medicine, London
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aagaard, B. T., Brocher, T. M., Dolenc, D., Dreger, D., Graves, R. W., Harmsen, S., Hartzell, S., Larsen, S., and Zoback, M. L. 2008. Ground-Motion Modeling of the 1906 San Francisco Earthquake, Part I: Validation Using the 1989 Loma Prieta Earthquake. Bulletin of the Seismological Society of America, 98 (2), 9891011.CrossRefGoogle Scholar
Aagaard, B. T., Hall, J. F., and Heaton, T. H. 2001. Characterization of Near-Source Ground Motions with Earthquake Simulations. Earthquake Spectra, 17 (2), 177207.CrossRefGoogle Scholar
Abrahamson, N. A. 1993. Spatial Variation of Multiple Support Inputs. In: Proc of 1st US Seminar on Seismic Evaluation and Retrofit of Steel Bridges.Google Scholar
Abrahamson, N. A. 2006. Seismic Hazard Assessment: Problems with Current Practice and Future Developments. In: First European Conference on Earthquake Engineering and Seismology.Google Scholar
Abrahamson, N., Atkinson, G., Boore, D., Bozorgnia, Y., Campbell, K., Chiou, B., Idriss, I. M., Silva, W., and Youngs, R. 2008. Comparisons of the NGA Ground-Motion Relations. Earthquake Spectra, 24 (1), 4566.CrossRefGoogle Scholar
Abrahamson, N. A., and Bommer, J. J. 2005. Probability and Uncertainty in Seismic Hazard Analysis. Earthquake Spectra, 21 (2), 603607.CrossRefGoogle Scholar
Abrahamson, N. A., Kuehn, N. M., Walling, M., and Landwehr, N. 2019. Probabilistic Seismic Hazard Analysis in California Using Nonergodic Ground-Motion Models. Bulletin of the Seismological Society of America, 109 (4), 12351249.CrossRefGoogle Scholar
Abrahamson, N., Schneider, J. F., and Stepp, J. C. 1991. Spatial Coherency of Shear Waves from the Lotung, Taiwan Large-Scale Seismic Test. Structural Safety, 10 (1), 145162.CrossRefGoogle Scholar
Abrahamson, N., and Silva, W. 2008. Summary of the Abrahamson & Silva NGA Ground-Motion Relations. Earthquake Spectra, 24 (1), 6797.CrossRefGoogle Scholar
Abrahamson, N. A., Silva, W. J., and Kamai, R. 2014. Summary of the ASK14 Ground Motion Relation for Active Crustal Regions. Earthquake Spectra, 30 (3), 10251055.CrossRefGoogle Scholar
Abrahamson, N., and Youngs, R. R. 1992. A Stable Algorithm for Regression Analysis Using the Random Effects Model. Bulletin of the Seismological Society of America, 82 (1), 505510.CrossRefGoogle Scholar
Adachi, T., and Ellingwood, B. 2007. Impact of Infrastructure Interdependency and Spatial Correlation of Seismic Intensities on Performance Assessment of a Water Distribution System. In: Proceedings of the 10th International Conference on Applications of Statistics and Probability in Civil Engineering.Google Scholar
Adachi, T., and Ellingwood, B. R. 2009. Serviceability Assessment of a Municipal Water System under Spatially Correlated Seismic Intensities. Computer-Aided Civil and Infrastructure Engineering, 24 (4), 237248.CrossRefGoogle Scholar
Aki, K. 1980. Scattering and Attenuation of Shear Waves in the Lithosphere. Journal of Geophysical Research: Solid Earth, 85 (B11), 64966504.Google Scholar
Aki, K. 2003. A Perspective on the History of Strong Motion Seismology. Physics of the Earth and Planetary Interiors, 137 (May), 511.CrossRefGoogle Scholar
Aki, K., and Richards, P. G. 2002. Quantitative Seismology. University Science Books.Google Scholar
Akkar, S., and Bommer, J. J. 2006. Influence of Long-Period Filter Cut-off on Elastic Spectral Displacements. Earthquake Engineering & Structural Dynamics, 35 (9), 11451165.CrossRefGoogle Scholar
Akkar, S., Sandıkkaya, M. A., and Ay, B. Ö. 2014. Compatible Ground-Motion Prediction Equations for Damping Scaling Factors and Vertical-to-Horizontal Spectral Amplitude Ratios for the Broader Europe Region. Bulletin of Earthquake Engineering, 12 (1), 517547.CrossRefGoogle Scholar
Al Atik, L., and Abrahamson, N. 2010. An Improved Method for Nonstationary Spectral Matching. Earthquake Spectra, 26 (3), 601617.CrossRefGoogle Scholar
Al Atik, L., Abrahamson, N., Bommer, J. J., Scherbaum, F., Cotton, F., and Kuehn, N. 2010. The Variability of Ground-Motion Prediction Models and Its Components. Seismological Research Letters, 81 (5), 794801.CrossRefGoogle Scholar
Al Atik, L., and Youngs, R. R. 2014. Epistemic Uncertainty for NGA-West2 Models. Earthquake Spectra, 30 (3), 13011318.CrossRefGoogle Scholar
Alavi, B., and Krawinkler, H. 2004. Behavior of Moment-Resisting Frame Structures Subjected to Near-Fault Ground Motions. Earthquake Engineering & Structural Dynamics, 33 (6), 687706.CrossRefGoogle Scholar
Aldor-Noiman, S., Brown, L. D., Buja, A., Rolke, W., and Stine, R. A. 2013. The Power to See: A New Graphical Test of Normality. The American Statistician, 67 (4), 249260.CrossRefGoogle Scholar
Alexander, N. A., Chanerley, A. A., Crewe, A. J., and Bhattacharya, S. 2014. Obtaining Spectrum Matching Time Series Using a Reweighted Volterra Series Algorithm (RVSA). Bulletin of the Seismological Society of America, 104 (4), 16631673.CrossRefGoogle Scholar
Allen, T. I., and Hayes, G. P. 2017. Alternative Rupture-Scaling Relationships for Subduction Interface and Other Offshore Environments. Bulletin of the Seismological Society of America, 107 (3), 12401253.Google Scholar
Ameri, G., Gallovic, F., Pacor, F., and Emolo, A. 2009. Uncertainties in Strong Ground-Motion Prediction with Finite-Fault Synthetic Seismograms: An Application to the 1984 M 5.7 Gubbio, Central Italy, Earthquake. Bulletin of the Seismological Society of America, 99 (2A), 647663.CrossRefGoogle Scholar
American Society of Civil Engineers. 2010. Minimum Design Loads for Buildings and Other Structures, ASCE 7-10. American Society of Civil Engineers/Structural Engineering Institute.Google Scholar
Amrhein, V., Greenland, S., and McShane, B. 2019. Scientists Rise up against Statistical Significance. Nature, 567 (7748), 305307.CrossRefGoogle ScholarPubMed
Anagnos, T., and Kiremidjian, A. S. 1984. Stochastic Time-Predictable Model for Earthquake Occurrences. Bulletin of the Seismological Society of America, 74 (6), 25932611.CrossRefGoogle Scholar
Anagnos, T., and Kiremidjian, A. S. 1988. A Review of Earthquake Occurrence Models for Seismic Hazard Analysis. Probabilistic Engineering Mechanics, 3 (1), 311.CrossRefGoogle Scholar
Ancheta, T. D., Darragh, R. B., Stewart, J. P., Seyhan, E., Silva, W. J., Chiou, B. S.-J., Wooddell, K. E., Graves, R. W., Kottke, A. R., Boore, D. M., Kishida, T., and Donahue, J. L. 2014. NGA-West2 Database. Earthquake Spectra, 30 (3), 9891005.Google Scholar
Ancheta, T. D., Stewart, J. P., and Abrahamson, N. A. 2010. Engineering Characterization of Spatially Variable Ground Motions. PhD Thesis, University of California, Los Angeles.Google Scholar
Anderson, E. L. 1983. Quantitative Approaches in Use to Assess Cancer Risk. Risk Analysis, 3 (4), 277295.CrossRefGoogle Scholar
Anderson, J. G., and Brune, J. N. 1999. Probabilistic Seismic Hazard Analysis without the Ergodic Assumption. Seismological Research Letters, 70 (1), 1928.CrossRefGoogle Scholar
Anderson, J. G., and Hough, S. E. 1984. A Model for the Shape of the Fourier Amplitude Spectrum of Acceleration at High Frequencies. Bulletin of the Seismological Society of America, 74 (5), 19691993.Google Scholar
Anderson, J. G., and Uchiyama, Y. 2011. A Methodology to Improve Ground-Motion Prediction Equations by Including Path Corrections. Bulletin of the Seismological Society of America, 101 (4), 18221846.CrossRefGoogle Scholar
Anderson, J. G., Wesnousky, S. G., and Stirling, M. W. 1996. Earthquake Size as a Function of Fault Slip Rate. Bulletin of the Seismological Society of America, 86 (3), 683690.2.0.CO;2>CrossRefGoogle Scholar
Andrews, D. J., Hanks, T. C., and Whitney, J. W. 2007. Physical Limits on Ground Motion at Yucca Mountain. Bulletin of the Seismological Society of America, 97 (6), 17711792.CrossRefGoogle Scholar
Andrews, D. J., and Schwerer, E. 2000. Probability of Rupture of Multiple Fault Segments. Bulletin of the Seismological Society of America, 90 (6), 14981506.CrossRefGoogle Scholar
Ang, A. H.-S., and Tang, W. 2007. Probability Concepts in Engineering Emphasis on Applications in Civil & Environmental Engineering. New York: Wiley.Google Scholar
Apostolakis, G. 1990. The Concept of Probability in Safety Assessments of Technological Systems. Science, 250 (4986), 13591364.CrossRefGoogle ScholarPubMed
Arias, A. 1970. A Measure of Earthquake Intensity. Pages 438483 of: Hansen, R. (ed.), Seismic Design for Nuclear Power Plants. Cambridge, MA: MIT Press.Google Scholar
Arroyo, D., and Ordaz, M. 2011. On the Forecasting of Ground-Motion Parameters for Probabilistic Seismic Hazard Analysis. Earthquake Spectra, 27 (1), 121.CrossRefGoogle Scholar
ASCE. 2016. Minimum Design Loads for Buildings and Other Structures, ASCE 7-16. Reston, VA: American Society of Civil Engineers/Structural Engineering Institute.Google Scholar
Aspinall, W. 2010. A Route to More Tractable Expert Advice. Nature, 463 (7279), 294295.CrossRefGoogle ScholarPubMed
Assatourians, K., and Atkinson, G. M. 2013. EqHaz: An Open-Source Probabilistic Seismic-Hazard Code Based on the Monte Carlo Simulation Approach. Seismological Research Letters, 84 (3), 516524.Google Scholar
Atkinson, G. M. 2008. Ground-Motion Prediction Equations for Eastern North America from a Referenced Empirical Approach: Implications for Epistemic Uncertainty. Bulletin of the Seismological Society of America, 98 (3), 13041318.CrossRefGoogle Scholar
Atkinson, G. M., and Beresnev, I. 1997. Don’t Call It Stress Drop. Seismological Research Letters, 68 (1), 34.CrossRefGoogle Scholar
Atkinson, G. M., Bommer, J. J., and Abrahamson, N. A. 2014. Alternative Approaches to Modeling Epistemic Uncertainty in Ground Motions in Probabilistic Seismic-Hazard Analysis. Seismological Research Letters, 85 (6), 11411144.CrossRefGoogle Scholar
Atkinson, G. M., and Silva, W. 2000. Stochastic Modeling of California Ground Motions. Bulletin of the Seismological Society of America, 90 (2), 255274.CrossRefGoogle Scholar
Atwater, B. F., Tuttle, M. P., Schweig, E. S., Rubin, C. M., Yamaguchi, D. K., and Hemphill-Haley, E. 2003. Earthquake Recurrence Inferred from Paleoseismology. Pages 331350 of: Developments in Quaternary Sciences. The Quaternary Period in the United States, vol. 1. Elsevier.Google Scholar
Azarbakht, A., Mousavi, M., Nourizadeh, M., and Shahri, M. 2014. Dependence of Correlations between Spectral Accelerations at Multiple Periods on Magnitude and Distance. Earthquake Engineering & Structural Dynamics, 43 (8), 11931204.CrossRefGoogle Scholar
Baker, J. W. 2007. Probabilistic Structural Response Assessment Using Vector-Valued Intensity Measures. Earthquake Engineering & Structural Dynamics, 36 (13), 18611883.Google Scholar
Baker, J. W. 2011. Conditional Mean Spectrum: Tool for Ground Motion Selection. Journal of Structural Engineering, 137 (3), 322331.CrossRefGoogle Scholar
Baker, J. W. 2015. Efficient Analytical Fragility Function Fitting Using Dynamic Structural Analysis. Earthquake Spectra, 31 (1), 579599.CrossRefGoogle Scholar
Baker, J. W., Abrahamson, N. A., Whitney, J. W., Board, M. P., and Hanks, T. C. 2013. Use of Fragile Geologic Structures as Indicators of Unexceeded Ground Motions and Direct Constraints on Probabilistic Seismic Hazard Analysis. Bulletin of the Seismological Society of America, 103 (3), 18981911.CrossRefGoogle Scholar
Baker, J. W., and Bradley, B. A. 2017. Intensity Measure Correlations Observed in the NGA-West2 Database, and Dependence of Correlations on Rupture and Site Parameters. Earthquake Spectra, 33 (1), 145156.CrossRefGoogle Scholar
Baker, J. W., and Chen, Y. 2020. Ground Motion Spatial Correlation Fitting Methods and Estimation Uncertainty. Earthquake Engineering & Structural Dynamics, 49 (15), 16621681.CrossRefGoogle Scholar
Baker, J. W., and Cornell, C. A. 2006a. Correlation of Response Spectral Values for Multi-component Ground Motions. Bulletin of the Seismological Society of America, 96 (1), 215227.CrossRefGoogle Scholar
Baker, J. W., and Cornell, C. A. 2006b. Spectral Shape, Epsilon and Record Selection. Earthquake Engineering & Structural Dynamics, 35 (9), 10771095.CrossRefGoogle Scholar
Baker, J. W., and Cornell, C. A. 2006c. Which Spectral Acceleration Are You Using? Earthquake Spectra, 22 (2), 293312.CrossRefGoogle Scholar
Baker, J. W., and Jayaram, N. 2008. Correlation of Spectral Acceleration Values from NGA Ground Motion Models. Earthquake Spectra, 24 (1), 299317.CrossRefGoogle Scholar
Baker, J. W., and Lee, C. 2018. An Improved Algorithm for Selecting Ground Motions to Match a Conditional Spectrum. Journal of Earthquake Engineering, 22 (4), 708723.CrossRefGoogle Scholar
Baker, J. W., Lin, T., Shahi, S. K., and Jayaram, N. 2011. New Ground Motion Selection Procedures and Selected Motions for the PEER Transportation Research Program. PEER Technical Report 2011/03.Google Scholar
Bao, H., Bielak, J., Ghattas, O., Kallivokas, L. F., O’Hallaron, D. R., Shewchuk, J. R., and Xu, J. 1998. Large-Scale Simulation of Elastic Wave Propagation in Heterogeneous Media on Parallel Computers. Computer Methods in Applied Mechanics and Engineering, 152 (1), 85102.CrossRefGoogle Scholar
Båth, M. 1965. Lateral Inhomogeneities of the Upper Mantle. Tectonophysics, 2 (6), 483514.CrossRefGoogle Scholar
Bauer, P., Thorpe, A., and Brunet, G. 2015. The Quiet Revolution of Numerical Weather Prediction. Nature, 525 (7567), 4755.CrossRefGoogle ScholarPubMed
Bayless, J., and Abrahamson, N. A. 2018. Evaluation of the Interperiod Correlation of Ground-Motion Simulations. Bulletin of the Seismological Society of America, 108 (6), 34133430.CrossRefGoogle Scholar
Bayless, J., and Abrahamson, N. A. 2019. An Empirical Model for the Interfrequency Correlation of Epsilon for Fourier Amplitude Spectra. Bulletin of the Seismological Society of America, 109 (3), 10581070.CrossRefGoogle Scholar
Bazzurro, P., and Cornell, C. A. 1999. Disaggregation of Seismic Hazard. Bulletin of the Seismological Society of America, 89 (2), 501520.CrossRefGoogle Scholar
Bazzurro, P., and Cornell, C. A. 2002. Vector-Valued Probabilistic Seismic Hazard Analysis. In: 7th U.S. National Conference on Earthquake Engineering. Boston: Earthquake Engineering Research Institute.Google Scholar
Bazzurro, P., and Cornell, C. A. 2004a. Ground-Motion Amplification in Nonlinear Soil Sites with Uncertain Properties. Bulletin of the Seismological Society of America, 94 (6), 20902109.CrossRefGoogle Scholar
Bazzurro, P., and Cornell, C. A. 2004b. Nonlinear Soil-Site Effects in Probabilistic Seismic-Hazard Analysis. Bulletin of the Seismological Society of America, 94 (6), 21102123.CrossRefGoogle Scholar
Bazzurro, P., and Luco, N. 2005. Accounting for Uncertainty and Correlation in Earthquake Loss Estimation. In: 9th International Conference on Structural Safety and Reliability (ICOSSAR05).Google Scholar
Bazzurro, P., and Luco, N. 2006. Do Scaled and Spectrum-Matched Near-Source Records Produce Biased Nonlinear Structural Responses? In: Proceedings, 8th National Conference on Earthquake Engineering.Google Scholar
Beauval, C., Bard, P. Y., Hainzl, S., and Gueguen, P. 2008. Can Strong-Motion Observations Be Used to Constrain Probabilistic Seismic-Hazard Estimates? Bulletin of the Seismological Society of America, 98 (2), 509520.CrossRefGoogle Scholar
Beauval, C., Honoré, L., and Courboulex, F. 2009. Ground-Motion Variability and Implementation of a Probabilistic–Deterministic Hazard Method. Bulletin of the Seismological Society of America, 99 (5), 29923002.CrossRefGoogle Scholar
Beauval, C., Tasan, H., Laurendeau, A., Delavaud, E., Cotton, F., Guéguen, P., and Kuehn, N. 2012. On the Testing of Ground-Motion Prediction Equations against Small-Magnitude Data. Bulletin of the Seismological Society of America, 102 (5), 19942007.CrossRefGoogle Scholar
Bedford, T., and Cooke, R. 2001. Probabilistic Risk Analysis: Foundations and Methods. Cambridge University Press.CrossRefGoogle Scholar
Bender, B. 1983. Maximum-Likelihood Estimation of b-Values for Magnitude Grouped Data. Bulletin of the Seismological Society of America, 73 (3), 831851.CrossRefGoogle Scholar
Benjamin, J. R., and Cornell, C. A. 2014. Probability, Statistics, and Decision for Civil Engineers. Mineola, NY: Dover Publications.Google Scholar
Berrill, J. B. 1988. Diversion of Faulting by Hills. Quarterly Journal of Engineering Geology and Hydrogeology, 21 (4), 371374.CrossRefGoogle Scholar
Berryman, K., Hamling, I., Kaiser, A., and Stahl, T. 2018. Introduction to the Special Issue on the 2016 Kaikōura Earthquake. Bulletin of the Seismological Society of America, 108 (3B), 14911495.CrossRefGoogle Scholar
Beyer, K., and Bommer, J. J. 2007. Selection and Scaling of Real Accelerograms for Bi-directional Loading: A Review of Current Practice and Code Provisions. Journal of Earthquake Engineering, 11 (suppl. 1), 1345.CrossRefGoogle Scholar
Biasi, G. P. 2013. Appendix H: Maximum Likelihood Recurrence Intervals for California Paleoseismic Sites. Open File Report 2013-1165. United States Geological Survey.Google Scholar
Biasi, G. P., and Weldon, R. J. I. 2006. Estimating Surface Rupture Length and Magnitude of Paleoearthquakes from Point Measurements of Rupture Displacement. Bulletin of the Seismological Society of America, 96 (5), 16121623.CrossRefGoogle Scholar
Biasi, G. P., and Weldon, R. J. 2009. San Andreas Fault Rupture Scenarios from Multiple Paleoseismic Records: Stringing Pearls. Bulletin of the Seismological Society of America, 99 (2A), 471498.CrossRefGoogle Scholar
Biasi, G. P., Weldon, R. J. I., and Dawson, T. E. 2013. Appendix F: Distribution of Slip in Ruptures. Open File Report 2013-1165. United States Geological Survey.Google Scholar
Biasi, G. P., Weldon, R. J., Fumal, T. E., and Seitz, G. G. 2002. Paleoseismic Event Dating and the Conditional Probability of Large Earthquakes on the Southern San Andreas Fault, California. Bulletin of the Seismological Society of America, 92 (7), 27612781.CrossRefGoogle Scholar
Bielak, J., Graves, R. W., Olsen, K. B., Taborda, R., Ramírez-Guzmín, L., Day, S. M., Ely, G. P., Roten, D., Jordan, T. H., Maechling, P. J., Urbanic, J., Cui, Y., and Juve, G. 2010. The ShakeOut Earthquake Scenario: Verification of Three Simulation Sets. Geophysical Journal International, 180 (1), 375404.CrossRefGoogle Scholar
Bielak, J., Karaoglu, H., and Taborda, R. 2011. Memory-Efficient Displacement-Based Internal Friction for Wave Propagation Simulation. Geophysics, 76 (6), T131T145.CrossRefGoogle Scholar
Bielak, J., Loukakis, K., Hisada, Y., and Yoshimura, C. 2003. Domain Reduction Method for Three-Dimensional Earthquake Modeling in Localized Regions, Part I: Theory. Bulletin of the Seismological Society of America, 93 (2), 817824.CrossRefGoogle Scholar
Bird, P. 2003. An Updated Digital Model of Plate Boundaries. Geochemistry Geophysics Geosystems, 4 (3), 1027.CrossRefGoogle Scholar
Bizzarri, A. 2011. On the Deterministic Description of Earthquakes. Reviews of Geophysics, 49 (RG3002).CrossRefGoogle Scholar
Bocchini, P., and Frangopol, D. M. 2011. Generalized Bridge Network Performance Analysis with Correlation and Time-Variant Reliability. Structural Safety, 33 (2), 155164.CrossRefGoogle Scholar
Bommer, J., Abrahamson, N., Strasser, F., A, P., Bard, P., Bungum, H., Cotton, F., Fah, D., Sabetta, F., Scherbaum, F., and Studer, J. 2004. The Challenge of Defining Upper Bounds on Earthquake Ground Motions. Seismological Research Letters, 75 , 8295.CrossRefGoogle Scholar
Bommer, J., Douglas, J., and Strasser, F. 2003. Style-of-Faulting in Ground-Motion Prediction Equations. Bulletin of Earthquake Engineering, 1 (2), 171203.CrossRefGoogle Scholar
Bommer, J. J. 2012. Challenges of Building Logic Trees for Probabilistic Seismic Hazard Analysis. Earthquake Spectra, 28 (4), 17231735.CrossRefGoogle Scholar
Bommer, J. J., and Abrahamson, N. A. 2006. Why Do Modern Probabilistic Seismic-Hazard Analyses Often Lead to Increased Hazard Estimates? Bulletin of the Seismological Society of America, 96 (6), 19671977.CrossRefGoogle Scholar
Bommer, J. J., and Acevedo, A. B. 2004. The Use of Real Earthquake Accelerograms as Input to Dynamic Analysis. Journal of Earthquake Engineering, 8 (Special Issue 1), 4391.CrossRefGoogle Scholar
Bommer, J. J., and Akkar, S. 2012. Consistent Source-to-Site Distance Metrics in Ground-Motion Prediction Equations and Seismic Source Models for PSHA. Earthquake Spectra, 28 (1), 115.CrossRefGoogle Scholar
Bommer, J. J., Coppersmith, K. J., Coppersmith, R. T., Hanson, K. L., Mangongolo, A., Neveling, J., Rathje, E. M., Rodriguez-Marek, A., Scherbaum, F., Shelembe, R., Stafford, P. J., and Strasser, F. O. 2015. A SSHAC Level 3 Probabilistic Seismic Hazard Analysis for a New-Build Nuclear Site in South Africa. Earthquake Spectra, 31 (2), 661698.CrossRefGoogle Scholar
Bommer, J. J., and Crowley, H. 2017. The Purpose and Definition of the Minimum Magnitude Limit in PSHA Calculations. Seismological Research Letters, 88 (4), 10971106.CrossRefGoogle Scholar
Bommer, J. J., Douglas, J., Scherbaum, F., Cotton, F., Bungum, H., and Fah, D. 2010. On the Selection of Ground-Motion Prediction Equations for Seismic Hazard Analysis. Seismological Research Letters, 81 (5), 783793.CrossRefGoogle Scholar
Bommer, J. J., and Martinez-Pereira, A. 1999. The Effective Duration of Earthquake Strong Motion. Journal of Earthquake Engineering, 3 (2), 127172.CrossRefGoogle Scholar
Bommer, J. J., and Scherbaum, F. 2008. The Use and Misuse of Logic Trees in Probabilistic Seismic Hazard Analysis. Earthquake Spectra, 24 (4), 9971009.CrossRefGoogle Scholar
Bommer, J. J., and Stafford, P. J. 2016. Chapter 2: Seismic Hazard and Earthquake Actions. Pages 740 of: Seismic Design of Buildings to Eurocode 8. CRC Press.CrossRefGoogle Scholar
Bommer, J. J., and Stafford, P. J. 2020. Selecting Ground-Motion Models for Site-Specific PSHA: Adaptability versus Applicability. Bulletin of the Seismological Society of America, 110 (6), 28012815.CrossRefGoogle Scholar
Bommer, J. J., Stafford, P. J., and Alarcon, J. E. 2009. Empirical Equations for the Prediction of the Significant, Bracketed, and Uniform Duration of Earthquake Ground Motion. Bulletin of the Seismological Society of America, 99 (6), 32173233.CrossRefGoogle Scholar
Bommer, J. J., Stafford, P. J., Alarcon, J. E., and Akkar, S. 2007. The Influence of Magnitude Range on Empirical Ground-Motion Prediction. Bulletin of the Seismological Society of America, 97 (6), 2152.CrossRefGoogle Scholar
Bommer, J. J., Stafford, P. J., Edwards, B., Dost, B., van Dedem, E., Rodriguez-Marek, A., Kruiver, P., van Elk, J., Doornhof, D., and Ntinalexis, M. 2017. Framework for a Ground-Motion Model for Induced Seismic Hazard and Risk Analysis in the Groningen Gas Field, the Netherlands. Earthquake Spectra, 33 (2), 481498.CrossRefGoogle Scholar
Bommer, J. J., Strasser, F. O., Pagani, M., and Monelli, D. 2013. Quality Assurance for Logic-Tree Implementation in Probabilistic Seismic-Hazard Analysis for Nuclear Applications: A Practical Example. Seismological Research Letters, 84 (6), 938945.CrossRefGoogle Scholar
Boore, D. M. 2003. Simulation of Ground Motion Using the Stochastic Method. Pure and Applied Geophysics, 160 , 635676.CrossRefGoogle Scholar
Boore, D. M. 2004. Estimating (or NEHRP Site Classes) from Shallow Velocity Models (Depths < 30 m). Bulletin of the Seismological Society of America, 94 (2), 591597.CrossRefGoogle Scholar
Boore, D. M. 2009. Comparing Stochastic Point-Source and Finite-Source Ground-Motion Simulations: SMSIM and EXSIM. Bulletin of the Seismological Society of America, 99 (6), 32023216.CrossRefGoogle Scholar
Boore, D. M. 2010. Orientation-Independent, Nongeometric-Mean Measures of Seismic Intensity from Two Horizontal Components of Motion. Bulletin of the Seismological Society of America, 100 (4), 18301835.CrossRefGoogle Scholar
Boore, D. M. 2013. The Uses and Limitations of the Square-Root-Impedance Method for Computing Site Amplification. Bulletin of the Seismological Society of America, 103 (4), 23562368.CrossRefGoogle Scholar
Boore, D. M. 2016. Determining Generic Velocity and Density Models for Crustal Amplification Calculations, with an Update of the Boore and Joyner (1997) Generic Site Amplification for VS(Z) = 760 m/s. Bulletin of the Seismological Society of America, 106 (1), 313317.CrossRefGoogle Scholar
Boore, D. M., and Boatwright, J. 1984. Average Body-Wave Radiation Coefficients. Bulletin of the Seismological Society of America, 74 (5), 16151621.CrossRefGoogle Scholar
Boore, D. M., and Bommer, J. J. 2005. Processing of Strong-Motion Accelerograms: Needs, Options and Consequences. Soil Dynamics and Earthquake Engineering, 25 , 93115.CrossRefGoogle Scholar
Boore, D. M., Gibbs, J. F., Joyner, W. B., Tinsley, J. C., and Ponti, D. J. 2003. Estimated Ground Motion from the 1994 Northridge, California, Earthquake at the Site of the Interstate 10 and La Cienega Boulevard Bridge Collapse, West Los Angeles, California. Bulletin of the Seismological Society of America, 93 (6), 27372751.CrossRefGoogle Scholar
Boore, D. M., and Joyner, W. B. 1997. Site Amplifications for Generic Rock Sites. Bulletin of the Seismological Society of America, 87 (2), 327341.CrossRefGoogle Scholar
Boore, D. M., Joyner, W. B., and Fumal, T. E. 1997. Equations for Estimating Horizontal Response Spectra and Peak Acceleration from Western North American Earthquakes: A Summary of Recent Work. Seismological Research Letters, 68 (1), 128153.CrossRefGoogle Scholar
Boore, D. M., Joyner, W. B., and Wennerberg, L. 1992. Fitting the Stochastic ω−2 Source Model to Observed Response Spectra in Western North America: Trade-offs between Δσ and κ. Bulletin of the Seismological Society of America, 82 (4), 19561963.CrossRefGoogle Scholar
Boore, D. M., Stewart, J. P., Seyhan, E., and Atkinson, G. M. 2014. NGA-West2 Equations for Predicting PGA, PGV, and 5% Damped PSA for Shallow Crustal Earthquakes. Earthquake Spectra, 30 (3), 10571085.CrossRefGoogle Scholar
Boore, D. M., and Thompson, E. M. 2014. Path Durations for Use in the Stochastic-Method Simulation of Ground Motions. Bulletin of the Seismological Society of America, 104 (5), 25412552.CrossRefGoogle Scholar
Boore, D. M., and Thompson, E. M. 2015. Revisions to Some Parameters Used in Stochastic-Method Simulations of Ground Motion. Bulletin of the Seismological Society of America, 105 (2A), 10291041.CrossRefGoogle Scholar
Boore, D., Watson-Lamprey, J., and Abrahamson, N. 2006. Orientation-Independent Measures of Ground Motion. Bulletin of the Seismological Society of America, 96 (4A), 15021511.CrossRefGoogle Scholar
Bora, S. S., Scherbaum, F., Kuehn, N., and Stafford, P. J. 2014. Fourier Spectral- and Duration Models for the Generation of Response Spectra Adjustable to Different Source-, Propagation-, and Site Conditions. Bulletin of Earthquake Engineering, 12 , 467493.CrossRefGoogle Scholar
Bora, S. S., Scherbaum, F., Kuehn, N., and Stafford, P. J. 2016. On the Relationship between Fourier and Response Spectra: Implications for the Adjustment of Empirical Ground-Motion Prediction Equations (GMPEs). Bulletin of the Seismological Society of America, 106 (3), 12351253.CrossRefGoogle Scholar
Bourne, S. J., Oates, S. J., and van Elk, J. 2018. The Exponential Rise of Induced Seismicity with Increasing Stress Levels in the Groningen Gas Field and Its Implications for Controlling Seismic Risk. Geophysical Journal International, 213 (3), 16931700.CrossRefGoogle Scholar
Box, G. E. P. 1980. Sampling and Bayes’ Inference in Scientific Modelling and Robustness. Journal of the Royal Statistical Society. Series A (General), 143 (4), 383430.CrossRefGoogle Scholar
Boyd, O. S. 2012. Including Foreshocks and Aftershocks in Time-Independent Probabilistic Seismic-Hazard Analyses. Bulletin of the Seismological Society of America, 102 (3), 909917.CrossRefGoogle Scholar
Bozorgnia, Y., and Campbell, K. 2004. The Vertical-to-Horizontal Response Spectral Ratio and Tentative Procedures for Developing Simplified V/H and Vertical Design Spectra. Journal of Earthquake Engineering, 8 (2), 175207.CrossRefGoogle Scholar
Bradley, B. 2009. Seismic Hazard Epistemic Uncertainty in the San Francisco Bay Area and Its Role in Performance-Based Assessment. Earthquake Spectra, 25 (4), 733753.CrossRefGoogle Scholar
Bradley, B. 2010a. Epistemic Uncertainty in Component Fragility Functions. Earthquake Spectra, 26 (1), 4162.CrossRefGoogle Scholar
Bradley, B. A. 2010b. A Generalized Conditional Intensity Measure Approach and Holistic Ground-Motion Selection. Earthquake Engineering & Structural Dynamics, 39 (12), 13211342.Google Scholar
Bradley, B. A. 2011. Correlation of Significant Duration with Amplitude and Cumulative Intensity Measures and Its Use in Ground Motion Selection. Journal of Earthquake Engineering, 15 (6), 809832.CrossRefGoogle Scholar
Bradley, B. A. 2012a. Empirical Correlations between Cumulative Absolute Velocity and Amplitude-Based Ground Motion Intensity Measures. Earthquake Spectra, 28 (1), 3754.CrossRefGoogle Scholar
Bradley, B. A. 2012b. A Ground Motion Selection Algorithm Based on the Generalized Conditional Intensity Measure Approach. Soil Dynamics and Earthquake Engineering, 40 , 4861.CrossRefGoogle Scholar
Bradley, B. A. 2012c. The Seismic Demand Hazard and Importance of the Conditioning Intensity Measure. Earthquake Engineering & Structural Dynamics, 41 (11), 14171437.CrossRefGoogle Scholar
Bradley, B. A. 2013a. A Comparison of Intensity-Based Demand Distributions and the Seismic Demand Hazard for Seismic Performance Assessment. Earthquake Engineering & Structural Dynamics, 42 (15), 22352253.CrossRefGoogle Scholar
Bradley, B. A. 2013b. A Critical Examination of Seismic Response Uncertainty Analysis in Earthquake Engineering. Earthquake Engineering & Structural Dynamics, 42 (11), 17171729.CrossRefGoogle Scholar
Bradley, B. A. 2013c. Practice-Oriented Estimation of the Seismic Demand Hazard Using Ground Motions at Few Intensity Levels. Earthquake Engineering & Structural Dynamics, 42 (14), 21672185.Google Scholar
Bradley, B. A. 2015. Correlation of Arias Intensity with Amplitude, Duration and Cumulative Intensity Measures. Soil Dynamics and Earthquake Engineering, 78 , 8998.CrossRefGoogle Scholar
Bradley, B. A., Burks, L. S., and Baker, J. W. 2015. Ground Motion Selection for Simulation-Based Seismic Hazard and Structural Reliability Assessment. Earthquake Engineering & Structural Dynamics, 44 (13), 23212340.CrossRefGoogle Scholar
Bradley, B. A., and Dhakal, R. P. 2008. Error Estimation of Closed-Form Solution for Annual Rate of Structural Collapse. Earthquake Engineering & Structural Dynamics, 37 (15), 17211737.CrossRefGoogle Scholar
Bradley, B. A., Dhakal, R. P., MacRae, G. A., and Cubrinovski, M. 2010. Prediction of Spatially Distributed Seismic Demands in Specific Structures: Ground Motion and Structural Response. Earthquake Engineering & Structural Dynamics, 39 (2), 501520.Google Scholar
Bradley, B. A., Pettinga, D., Baker, J. W., and Fraser, J. 2017. Guidance on the Utilization of Earthquake-Induced Ground Motion Simulations in Engineering Practice. Earthquake Spectra, 33 (3), 809835.CrossRefGoogle Scholar
Bray, J. D., and Travasarou, T. 2007. Simplified Procedure for Estimating Earthquake-Induced Deviatoric Slope Displacements. Journal of Geotechnical and Geoenvironmental Engineering, 133 (4), 381392.CrossRefGoogle Scholar
Brillinger, D. R., and Preisler, H. K. 1984. An Exploratory Analysis of the Joyner–Boore Attenuation Data. Bulletin of the Seismological Society of America, 74 (4), 14411450.Google Scholar
Brillinger, D. R., and Preisler, H. K. 1985. Further Analysis of the Joyner–Boore Attenuation Data. Bulletin of the Seismological Society of America, 75 (2), 611614.CrossRefGoogle Scholar
Brocher, T. M. 2005. Empirical Relations between Elastic Wavespeeds and Density in the Earth’s Crust. Bulletin of the Seismological Society of America, 95 (6), 20812092.CrossRefGoogle Scholar
Brune, J. 1970. Tectonic Stress and the Spectra of Seismic Shear Waves from Earthquakes. Journal of Geophysical Research, 75 (26), 49975009.CrossRefGoogle Scholar
Brune, J. 1971. Correction. Journal of Geophysical Research, 76 (20), 5002.Google Scholar
Brune, J. 1999. Precarious Rocks along the Mojave Section of the San Andreas Fault, California: Constraints on Ground Motion from Great Earthquakes. Seismological Research Letters, 70 (1), 2933.CrossRefGoogle Scholar
BSSC. 2009. NEHRP Recommended Seismic Provisions for New Buildings and Other Structures. FEMA P-750. Building Seismic Safety Council, Washington, DC.Google Scholar
BSSC. 2015. NEHRP Recommended Seismic Provisions for New Buildings and Other Structures. FEMA P-1050. Building Seismic Safety Council, Washington, DC.Google Scholar
Budnitz, R. J., Amico, P. J., Cornell, C. A., Hall, W. J., Kennedy, R. P., Reed, J. W., and Shinozuka, M. 1985. An Approach to the Quantification of Seismic Margins in Nuclear Power Plants. NUREG/CR 4334. US Nuclear Regulatory Commission, Washington, DC.Google Scholar
Bullock, Z. 2019. Log-Logistic Uncertainty Is More Durable than Lognormal Uncertainty in Ground-Motion Prediction Equations. Bulletin of the Seismological Society of America, 109 (2), 567574.CrossRefGoogle Scholar
Buratti, N., Stafford, P. J., and Bommer, J. J. 2011. Earthquake Accelerogram Selection and Scaling Procedures for Estimating the Distribution of Drift Response. Journal of Structural Engineering, 137 (3), 345357.CrossRefGoogle Scholar
Burbank, D. W., and Anderson, R. S. 2011. Tectonic Geomorphology, 2nd ed. Chichester, UK: John Wiley & Sons.CrossRefGoogle Scholar
Burridge, R., and Knopoff, L. 1964. Body Force Equivalents for Seismic Dislocations. Bulletin of the Seismological Society of America, 54 (6), 18751888.CrossRefGoogle Scholar
Burridge, R., and Knopoff, L. 1967. Model and Theoretical Seismicity. Bulletin of the Seismological Society of America, 57 (3), 341371.CrossRefGoogle Scholar
Calvi, G. M., Pinho, R., Magenes, G., Bommer, J. J., Restrepo-Vílez, L. F., and Crowley, H. 2006. Development of Seismic Vulnerability Assessment Methodologies over the Past 30 Years. ISET Journal of Earthquake Technology, 43 (3), 75104.Google Scholar
Campbell, K. W. 2003. Prediction of Strong Ground Motion Using the Hybrid Empirical Method and Its Use in the Development of Ground-Motion (Attenuation) Relations in Eastern North America. Bulletin of the Seismological Society of America, 93 (3), 10121033.CrossRefGoogle Scholar
Campbell, K. W., and Bozorgnia, Y. 2014. NGA-West2 Ground Motion Model for the Average Horizontal Components of PGA, PGV, and 5% Damped Linear Acceleration Response Spectra. Earthquake Spectra, 30 (3), 10871115.CrossRefGoogle Scholar
Carballo, J. E. 2000. Probabilistic Seismic Demand Analysis: Spectrum Matching and Design. Dept. of Civil and Environmental Engineering. Stanford, CA: Stanford University.Google Scholar
Carlson, J. M., and Langer, J. S. 1989. Mechanical Model of an Earthquake Fault. Physical Review A, 40 (11), 64706484.CrossRefGoogle ScholarPubMed
Carlson, J. M., Langer, J. S., Shaw, B. E., and Tang, C. 1991. Intrinsic Properties of a Burridge– Knopoff Model of an Earthquake Fault. Physical Review A, 44 (2), 884897.CrossRefGoogle ScholarPubMed
Carlton, B., and Abrahamson, N. 2014. Issues and Approaches for Implementing Conditional Mean Spectra in Practice. Bulletin of the Seismological Society of America, 104 (1), 503512.CrossRefGoogle Scholar
CEN. 2004. Eurocode 8: Design of Structures for Earthquake Resistance—Part 1: General Rules, Seismic Actions and Rules for Buildings. Comité Européen de Normalisation, European Standard EN 1998-1:2004: E. Brussels.Google Scholar
Cesca, S., Zhang, Y., Mouslopoulou, V., Wang, R., Saul, J., Savage, M., Heimann, S., Kufner, S. K., Oncken, O., and Dahm, T. 2017. Complex Rupture Process of the Mw 7.8, 2016, Kaikoura Earthquake, New Zealand, and Its Aftershock Sequence. Earth and Planetary Science Letters, 478 , 110120.CrossRefGoogle Scholar
Chaljub, E., Maufroy, E., Moczo, P., Kristek, J., Hollender, F., Bard, P.-Y., Priolo, E., Klin, P., de Martin, F., Zhang, Z., Zhang, W., and Chen, X. 2015. 3-D Numerical Simulations of Earthquake Ground Motion in Sedimentary Basins: Testing Accuracy through Stringent Models. Geophysical Journal International, 201 (1), 90111.CrossRefGoogle Scholar
Chaljub, E., Moczo, P., Tsuno, S., Bard, P.-Y., Kristek, J., Käser, M., Stupazzini, M., and Kristekova, M. 2010. Quantitative Comparison of Four Numerical Predictions of 3D Ground Motion in the Grenoble Valley, France. Bulletin of the Seismological Society of America, 100 (4), 14271455.CrossRefGoogle Scholar
Chandramohan, R., Baker, J. W., and Deierlein, G. G. 2016. Impact of Hazard-Consistent Ground Motion Duration in Structural Collapse Risk Assessment. Earthquake Engineering & Structural Dynamics, 45 (8), 13571379.CrossRefGoogle Scholar
Chang, S. E., Shinozuka, M., and Moore, J. E. 2000. Probabilistic Earthquake Scenarios: Extending Risk Analysis Methodologies to Spatially Distributed Systems. Earthquake Spectra, 16 (3), 557572.CrossRefGoogle Scholar
Chen, Y., and Baker, J. W. 2019. Spatial Correlations in CyberShake Physics-Based Ground-Motion Simulations. Bulletin of the Seismological Society of America, 109 (6), 24472458.CrossRefGoogle Scholar
Chen, P., Zhao, L., and Jordan, T. H. 2007. Full 3D Tomography for the Crustal Structure of the Los Angeles Region. Bulletin of the Seismological Society of America, 97 (4), 10941120.CrossRefGoogle Scholar
Chen, Y.-H., and Tsai, C.-C. P. 2002. A New Method for Estimation of the Attenuation Relationship with Variance Components. Bulletin of the Seismological Society of America, 92 (5), 19841991.CrossRefGoogle Scholar
Chiou, B., Darragh, R., Gregor, N., and Silva, W. 2008. NGA Project Strong-Motion Database. Earthquake Spectra, 24 (1), 2344.CrossRefGoogle Scholar
Chiou, B., Youngs, R., Abrahamson, N., and Addo, K. 2010. Ground-Motion Attenuation Model for Small-to-Moderate Shallow Crustal Earthquakes in California and Its Implications on Regionalization of Ground-Motion Prediction Models. Earthquake Spectra, 26 (4), 907926.CrossRefGoogle Scholar
Chiou, B. S.-J., and Youngs, R. R. 2008. An NGA Model for the Average Horizontal Component of Peak Ground Motion and Response Spectra. Earthquake Spectra, 24 (1), 173215.CrossRefGoogle Scholar
Chiou, B. S.-J., and Youngs, R. R. 2014. Update of the Chiou and Youngs NGA Model for the Average Horizontal Component of Peak Ground Motion and Response Spectra. Earthquake Spectra, 30 (3), 11171153.CrossRefGoogle Scholar
Choi, Y., and Stewart, J. P. 2005. Nonlinear Site Amplification as Function of 30 m Shear Wave Velocity. Earthquake Spectra, 21 (1), 130.CrossRefGoogle Scholar
Choi, Y., Stewart, J. P., and Graves, R. W. 2005. Empirical Model for Basin Effects Accounts for Basin Depth and Source Location. Bulletin of the Seismological Society of America, 95 (4), 14121427.CrossRefGoogle Scholar
Chopra, A. 2016. Dynamics of Structures, 5th ed. Hoboken, NJ: Pearson.Google Scholar
Clough, R., and Penzien, J. 1975. Dynamics of Structures. New York: McGraw-Hill.Google Scholar
Coburn, A., and Spence, R. 2002. Earthquake Protection. John Wiley & Sons.CrossRefGoogle Scholar
Cochran, W. G. 1977. Sampling Techniques, 3rd ed. New York: John Wiley & Sons.Google Scholar
Console, R., and Murru, M. 2001. A Simple and Testable Model for Earthquake Clustering. Journal of Geophysical Research, 106 (B5), 86998711.CrossRefGoogle Scholar
Cook, R., Malkus, D., and Plesha, M. 1989. Concepts and Applications of Finite Element Analysis, 3rd ed. New York: John Wiley and Sons.Google Scholar
Cooke, R. 1991. Experts in Uncertainty: Opinion and Subjective Probability in Science. Oxford University Press on Demand.Google Scholar
Cordova, P. P., Deierlein, G. G., Mehanny, S. S., and Cornell, C. 2001. Development of a Two-Parameter Seismic Intensity Measure and Probabilistic Assessment Procedure. Pages 187–206 of: The Second U.S.–Japan Workshop on Performance-Based Earthquake Engineering Methodology for Reinforced Concrete Building Structures.Google Scholar
Cornell, C. A. 1968. Engineering Seismic Risk Analysis. Bulletin of the Seismological Society of America, 58 (5), 15831606.CrossRefGoogle Scholar
Cornell, C. A. 1994. Statistical Analysis of Maximum Magnitudes. In: The Earthquakes of Stable Continential Regions. EPRI Report, nos. TR–102261s–V1–V5. Electric Power Research Institute.Google Scholar
Cornell, C. A., Banon, H., and Shakal, A. F. 1979. Seismic Motion and Response Prediction Alternatives. Earthquake Engineering & Structural Dynamics, 7 (4), 295315.CrossRefGoogle Scholar
Cornell, C. A., Jalayer, F., Hamburger, R. O., and Foutch, D. A. 2002. Probabilistic Basis for 2000 SAC Federal Emergency Management Agency Steel Moment Frame Guidelines. Journal of Structural Engineering, 128 (4), 526533.CrossRefGoogle Scholar
Cornell, C. A., and Krawinkler, H. 2000. Progress and Challenges in Seismic Performance Assessment. PEER Center News, 3 (2).Google Scholar
Cornell, C. A., and Vanmarcke, E. H. 1969. The Major Influences on Seismic Risk. Pages 69–83 of: Proceedings of the Fourth World Conference on Earthquake Engineering, vol. 1.Google Scholar
Cornell, C. A., and Winterstein, S. R. 1988. Temporal and Magnitude Dependence in Earthquake Recurrence Models. Bulletin of the Seismological Society of America, 78 (4), 15221537.Google Scholar
Cotton, F., Scherbaum, F., Bommer, J., and Bungum, H. 2006. Criteria for Selecting and Adjusting Ground-Motion Models for Specific Target Regions: Application to Central Europe and Rock Sites. Journal of Seismology, 10 , 137156.CrossRefGoogle Scholar
Crempien, J. G. F., and Archuleta, R. J. 2015. UCSB Method for Simulation of Broadband Ground Motion from Kinematic Earthquake Sources. Seismological Research Letters, 86 (1), 6167.CrossRefGoogle Scholar
Crowley, H., and Pinho, R. 2011. Global Earthquake Model: Community-Based Seismic Risk Assessment. Pages 319 of: Protection of Built Environment against Earthquakes. Springer.CrossRefGoogle Scholar
Crowley, H., Pinho, R., and Bommer, J. J. 2004. A Probabilistic Displacement-Based Vulnerability Assessment Procedure for Earthquake Loss Estimation. Bulletin of Earthquake Engineering, 2 (2), 173219.CrossRefGoogle Scholar
Crowley, H., Stafford, P. J., and Bommer, J. J. 2008. Can Earthquake Loss Models Be Validated Using Field Observations? Journal of Earthquake Engineering, 12 (7), 10781104.CrossRefGoogle Scholar
Daniell, J. E., Khazai, B., Wenzel, F., and Vervaeck, A. 2011. The CATDAT Damaging Earthquakes Database. Natural Hazards and Earth System Sciences, 11 (8), 2235.CrossRefGoogle Scholar
Day, S. M., and Bradley, C. R. 2001. Memory-Efficient Simulation of Anelastic Wave Propagation. Bulletin of the Seismological Society of America, 91 (3), 520531.CrossRefGoogle Scholar
Day, S. M., Graves, R., Bielak, J., Dreger, D., Larsen, S., Olsen, K. B., Pitarka, A., and Ramirez-Guzman, L. 2008. Model for Basin Effects on Long-Period Response Spectra in Southern California. Earthquake Spectra, 24 (1), 257277.CrossRefGoogle Scholar
D’Ayala, D., Meslem, A., Vamvatsikos, D., Porter, K., Rossetto, T., Crowley, H., and Silva, V. 2014. Guidelines for Analytical Vulnerability Assessment of Low-to Mid-Rise Buildings—Methodology. GEM Technical Report 2014-12 V1.0.0. Global Earthquake Model.Google Scholar
de la Puente, J., Dumbser, M., Käser, M., and Igel, H. 2008. Discontinuous Galerkin Methods for Wave Propagation in Poroelastic Media. Geophysics, 73 (5), T77T97.CrossRefGoogle Scholar
de la Torre, C. A., Bradley, B. A., and Lee, R. L. 2020. Modeling Nonlinear Site Effects in Physics-Based Ground Motion Simulations of the 2010–2011 Canterbury Earthquake Sequence. Earthquake Spectra, 36 (2), 856879.CrossRefGoogle Scholar
DeBock, D. J., Garrison, J. W., Kim, K. Y., and Liel, A. B. 2014. Incorporation of Spatial Correlations between Building Response Parameters in Regional Seismic Loss Assessment. Bulletin of the Seismological Society of America, 104 (1), 214228.CrossRefGoogle Scholar
DeMets, C., Gordon, R. G., Argus, D. F., and Stein, S. 1990. Current Plate Motions. Geophysical Journal International, 101 (2), 425478.CrossRefGoogle Scholar
Der Kiureghian, A. 2005. Non-Ergodicity and PEER’s Framework Formula. Earthquake Engineering and Structural Dynamics, 34 (13), 16431652.CrossRefGoogle Scholar
Der Kiureghian, A., and Ditlevsen, O. 2008. Aleatory or Epistemic? Does It Matter? Structural Safety, 31 (2), 105112.CrossRefGoogle Scholar
Detweiler, S. T., and Wein, A. M. 2017. The HayWired Earthquake Scenario. USGS Numbered Series 2017-5013. US Geological Survey, Reston, VA.CrossRefGoogle Scholar
Dieterich, J. H. 1979. Modeling of Rock Friction: 1. Experimental Results and Constitutive Equations. Journal of Geophysical Research, 84 (B5), 21612168.CrossRefGoogle Scholar
Dolsek, M. 2009. Incremental Dynamic Analysis with Consideration of Modeling Uncertainties. Earthquake Engineering & Structural Dynamics, 38 (6), 805825.CrossRefGoogle Scholar
Donahue, J. L., and Abrahamson, N. A. 2014. Simulation-Based Hanging Wall Effects. Earthquake Spectra, 30 (3), 12691284.CrossRefGoogle Scholar
Dorra, E. M., Stafford, P. J., and Elghazouli, A. Y. 2013. Earthquake Loss Estimation for Greater Cairo and the National Economic Implications. Bulletin of Earthquake Engineering, 11 (4), 12171257.CrossRefGoogle Scholar
Douglas, J. 2003. Earthquake Ground Motion Estimation Using Strong Motion Records: A Review of Equations for the Estimation of Peak Ground Acceleration and Response Spectral Ordinates. Earth Science Reviews, 61 , 43104.CrossRefGoogle Scholar
Douglas, J. 2019. Ground Motion Prediction Equations 1964–2018. Online Report www.gmpe.org.uk. University of Strathclyde, Glasgow.Google Scholar
Douglas, J., and Aochi, H. 2008. A Survey of Techniques for Predicting Earthquake Ground Motions for Engineering Purposes. Surveys in Geophysics, 29 (3), 187220.CrossRefGoogle Scholar
Douglas, J., and Aochi, H. 2016. Assessing Components of Ground-Motion Variability from Simulations for the Marmara Sea Region (Turkey). Bulletin of the Seismological Society of America, 106 (1), 300306.CrossRefGoogle Scholar
Douglas, J., and Boore, D. 2011. High-Frequency Filtering of Strong-Motion Records. Bulletin of Earthquake Engineering, 9 (2), 395409.CrossRefGoogle Scholar
Douglas, J., and Edwards, B. 2016. Recent and Future Developments in Earthquake Ground Motion Estimation. Earth-Science Reviews, 160 (Sept.), 203219.CrossRefGoogle Scholar
Douglas, J., Ulrich, T., Bertil, D., and Rey, J. 2014. Comparison of the Ranges of Uncertainty Captured in Different Seismic-Hazard Studies. Seismological Research Letters, 85 (5), 977985.CrossRefGoogle Scholar
Douglas, J., Ulrich, T., and Negulescu, C. 2013. Risk-Targeted Seismic Design Maps for Mainland France. Natural Hazards, 65 (3), 19992013.CrossRefGoogle Scholar
Dreger, D. S., and Jordan, T. H. 2015. Introduction to the Focus Section on Validation of the SCEC Broadband Platform V14.3 Simulation Methods. Seismological Research Letters, 86 (1), 1516.CrossRefGoogle Scholar
Eads, L., Miranda, E., Krawinkler, H., and Lignos, D. G. 2013. An Efficient Method for Estimating the Collapse Risk of Structures in Seismic Regions. Earthquake Engineering & Structural Dynamics, 42 (1), 2541.CrossRefGoogle Scholar
Eaton, J. P. 1992. Determination of Amplitude and Duration Magnitudes and Site Residual from Short-Period Seismographs in Northern California. Bulletin of the Seismological Society of America, 82 (2), 533579.CrossRefGoogle Scholar
Ebel, J. E., and Kafka, A. L. 1999. A Monte Carlo Approach to Seismic Hazard Analysis. Bulletin of the Seismological Society of America, 89 (4), 854866.CrossRefGoogle Scholar
Eberly, D. 2020. Distance between Point and Triangle in 3D. Geometric Tools, Online Report. www.geometrictools.com/Documentation/DistancePoint3Triangle3.pdf.Google Scholar
Edwards, B., and Fäh, D. 2013. A Stochastic Ground Motion Model for Switzerland. Bulletin of the Seismological Society of America, 103 (1), 7898.CrossRefGoogle Scholar
Edwards, B., Zurek, B., van Dedem, E., Stafford, P. J., Oates, S., van Elk, J., deMartin, B., and Bommer, J. J. 2019. Simulations for the Development of a Ground Motion Model for Induced Seismicity in the Groningen Gas Field, the Netherlands. Bulletin of Earthquake Engineering, 17 , 44414456.CrossRefGoogle Scholar
Ellingwood, B. R., and Kinali, K. 2009. Quantifying and Communicating Uncertainty in Seismic Risk Assessment. Structural Safety, 31 (2), 179187.CrossRefGoogle Scholar
Ellsworth, W. L., Matthews, M. V., Nadeau, R. M., Nishenko, S. P., Reasenberg, P. A., and Simpson, R. W. 1999. A Physically Based Earthquake Recurrence Model for Estimation of Long-Term Earthquake Probabilities. Open File Report 99-522.CrossRefGoogle Scholar
Elms, D. G. 2004. Structural Safety: Issues and Progress. Progress in Structural Engineering and Materials, 6 (2), 116126.CrossRefGoogle Scholar
EPRI. 1991. Standardization of the Cumulative Absolute Velocity. EPRI TR-100082-T2. Electric Power Research Institute, Palo Alto, CA.Google Scholar
Esposito, S., and Iervolino, I. 2011. PGA and PGV Spatial Correlation Models Based on European Multievent Datasets. Bulletin of the Seismological Society of America, 101 (5), 25322541.CrossRefGoogle Scholar
Evison, F. F., and Rhoades, D. A. 2004. Demarcation and Scaling of Long-Term Seismogenesis. Pure and Applied Geophysics, 161 (1), 2145.CrossRefGoogle Scholar
Felzer, K. R. 2013a. Appendix K: The UCERF3 Earthquake Catalog. Open File Report 2013-1165. United States Geological Survey.Google Scholar
Felzer, K. R. 2013b. Appendix L: Estimate of the Seismicity Rate and Magnitude-Frequency Distribution of Earthquakes in California from 1850 to 2011. Open File Report 2013-1165. United States Geological Survey.Google Scholar
Felzer, K. R., and Brodsky, E. E. 2005. Testing the Stress Shadow Hypothesis. Journal of Geophysical Research: Solid Earth, 110 (B5), 702.CrossRefGoogle Scholar
Felzer, K. R., and Brodsky, E. E. 2006. Decay of Aftershock Density with Distance Indicates Triggering by Dynamic Stress. Nature, 441 (7094), 735738.CrossRefGoogle ScholarPubMed
FEMA. 2005. Improvement of Nonlinear Static Seismic Procedures. FEMA-440. Federal Emergency Management Agency, FEMA, Washington, DC.Google Scholar
FEMA. 2009. Quantification of Building Seismic Performance Factors (FEMA P695, ATC-63). FEMA P695. Federal Emergency Management Agency, prepared by the Applied Technology Council.Google Scholar
FEMA. 2012. Seismic Performance Assessment of Buildings. FEMA P-58. Prepared by Applied Technology Council for the Federal Emergency Management Agency.Google Scholar
FEMA. 2015. Hazus-MH 2.1. Multi-hazard Loss Estimation Methodology Technical and User Manuals. Federal Emergency Management Agency.Google Scholar
Field, E. H. 2015. “All Models Are Wrong, but Some Are Useful.” Seismological Research Letters, 86 (2A), 291293.CrossRefGoogle Scholar
Field, E. H., Arrowsmith, R. J., Biasi, G. P., Bird, P., Dawson, T. E., Felzer, K. R., Jackson, D. D., Johnson, K. M., Jordan, T. H., Madden, C., Michael, A. J., Milner, K. R., Page, M. T., Parsons, T., Powers, P. M., Shaw, B. E., Thatcher, W. R., Weldon, R. J., and Zeng, Y. 2014. Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3)—The Time-Independent Model. Bulletin of the Seismological Society of America, 104 (3), 11221180.CrossRefGoogle Scholar
Field, E. H., Biasi, G. P., Bird, P., Dawson, T. E., Felzer, K. R., Jackson, D. D., Johnson, K. M., Jordan, T. H., Madden, C., Michael, A. J., Milner, K. R., Page, M. T., Parsons, T., Powers, P. M., Shaw, B. E., Thatcher, W. R., Weldon, R. J. I., and Zeng, Y. 2013. Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3): The Time-Independent Model. Open File Report 2013-1165. United States Geological Survey.Google Scholar
Field, E. H., Biasi, G. P., Bird, P., Dawson, T. E., Felzer, K. R., Jackson, D. D., Johnson, K. M., Jordan, T. H., Madden, C., Michael, A. J., Milner, K. R., Page, M. T., Parsons, T., Powers, P. M., Shaw, B. E., Thatcher, W. R., Weldon, R. J., and Zeng, Y. 2015. Long-Term Time-Dependent Probabilities for the Third Uniform California Earthquake Rupture Forecast (UCERF3). Bulletin of the Seismological Society of America, 105 (2A), 511543.Google Scholar
Field, E. H., Dawson, T. E., Felzer, K. R., Frankel, A. D., Gupta, V., Jordan, T. H., Parsons, T., Petersen, M. D., Stein, R. S., Weldon, R. J., and Wills, C. J. 2009. Uniform California Earthquake Rupture Forecast, Version 2 (UCERF 2). Bulletin of the Seismological Society of America, 99 (4), 20532107.CrossRefGoogle Scholar
Field, E. H., and Jordan, T. H. 2015. Time-Dependent Renewal-Model Probabilities When Date of Last Earthquake Is Unknown. Bulletin of the Seismological Society of America, 105 (1), 459463.CrossRefGoogle Scholar
Field, E. H., Jordan, T. H., and Cornell, C. A. 2003. OpenSHA: A Developing Community-Modeling Environment for Seismic Hazard Analysis. Seismological Research Letters, 74 (4), 406419.CrossRefGoogle Scholar
Field, E. H., Jordan, T. H., Page, M. T., Milner, K. R., Shaw, B. E., Dawson, T. E., Biasi, G. P., Parsons, T., Hardebeck, J. L., Michael, A. J., Weldon, R. J. I., Powers, P. M., Johnson, K. M., Zeng, Y., Felzer, K. R., van der Elst, N., Madden, C., Arrowsmith, R., Werner, M. J., and Thatcher, W. R. 2017a. A Synoptic View of the Third Uniform California Earthquake Rupture Forecast (UCERF3). Bulletin of the Seismological Society of America, 88 (5), 12591267.Google Scholar
Field, E. H., Milner, K. R., Hardebeck, J. L., Page, M. T., van der Elst, N., Jordan, T. H., Michael, A. J., Shaw, B. E., and Werner, M. J. 2017b. A Spatiotemporal Clustering Model for the Third Uniform California Earthquake Rupture Forecast (UCERF3-ETAS): Toward an Operational Earthquake Forecast. Bulletin of the Seismological Society of America, 107 (3), 10491081.CrossRefGoogle Scholar
Field, E. H., and Page, M. T. 2011. Estimating Earthquake-Rupture Rates on a Fault or Fault System. Bulletin of the Seismological Society of America, 101 (1), 7992.CrossRefGoogle Scholar
Finn, W. D. L., Ventura, C. E., and Wu, G. 1993. Analysis of Ground Motions at Treasure Island Site during the 1989 Loma Prieta Earthquake. Soil Dynamics and Earthquake Engineering, 12 (7), 383390.CrossRefGoogle Scholar
Foulser-Piggott, R., and Goda, K. 2015. Ground-Motion Prediction Models for Arias Intensity and Cumulative Absolute Velocity for Japanese Earthquakes Considering Single-Station Sigma and Within-Event Spatial Correlation. Bulletin of the Seismological Society of America, 105 (4), 19031918.CrossRefGoogle Scholar
Foulser-Piggott, R., and Stafford, P. J. 2012. A Predictive Model for Arias Intensity at Multiple Sites and Consideration of Spatial Correlations. Earthquake Engineering & Structural Dynamics, 41 (3), 431451.CrossRefGoogle Scholar
Fox, M. J., Stafford, P. J., and Sullivan, T. J. 2016. Seismic Hazard Disaggregation in Performance-Based Earthquake Engineering: Occurrence or Exceedance? Earthquake Engineering & Structural Dynamics, 45 (5), 835842.CrossRefGoogle Scholar
Frankel, A. 1995. Simulating Strong Motions of Large Earthquakes Using Recordings of Small Earthquakes: The Loma Prieta Mainshock as a Test Case. Bulletin of the Seismological Society of America, 85 (4), 11441160.CrossRefGoogle Scholar
Frankel, A., and Vidale, J. 1992. A Three-Dimensional Simulation of Seismic Waves in the Santa Clara Valley, California, from a Loma Prieta Aftershock. Bulletin of the Seismological Society of America, 82 (5), 20452074.Google Scholar
Frankel, A., Wirth, E., Marafi, N., Vidale, J., and Stephenson, W. 2018. Broadband Synthetic Seismograms for Magnitude 9 Earthquakes on the Cascadia Megathrust Based on 3D Simulations and Stochastic Synthetics, Part 1: Methodology and Overall Results. Bulletin of the Seismological Society of America, 108 (5A), 23472369.CrossRefGoogle Scholar
Fukushima, Y. 1996. Scaling Relations for Strong Ground Motion Prediction Models with M2 Terms. Bulletin of the Seismological Society of America, 86 (2), 329336.CrossRefGoogle Scholar
Gardner, J. K., and Knopoff, L. 1974. Is the Sequence of Earthquakes in Southern California, with Aftershocks Removed, Poissonian? Bulletin of the Seismological Society of America, 64 (5), 13631367.CrossRefGoogle Scholar
Gardoni, P., Der Kiureghian, A., and Mosalam, K. M. 2002. Probabilistic Capacity Models and Fragility Estimates for Reinforced Concrete Columns Based on Experimental Observations. Journal of Engineering Mechanics, 128 (10), 10241038.CrossRefGoogle Scholar
Gasparini, D., and Vanmarcke, E. H. 1976. SIMQKE: A Program for Artificial Motion Generation. MIT Department of Civil Engineering, Cambridge, MA.Google Scholar
Gatz, D. F., and Smith, L. 1995. The Standard Error of a Weighted Mean Concentration—I. Bootstrapping vs Other Methods. Atmospheric Environment, 29 (11), 11851193.CrossRefGoogle Scholar
Geller, R. J. 2011. Shake-up Time for Japanese Seismology. Nature, 472 (Apr.), 407.CrossRefGoogle ScholarPubMed
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. 2013. Bayesian Data Analysis, 3rd ed. Chapman and Hall/CRC.CrossRefGoogle Scholar
Gentle, J. E. 2003. Random Number Generation and Monte Carlo Methods, 2nd ed. New York: Springer-Verlag.Google Scholar
Gerstenberger, M. C., Rhoades, D. A., and McVerry, G. H. 2016. A Hybrid Time-Dependent Probabilistic Seismic-Hazard Model for Canterbury, New Zealand. Seismological Research Letters, 87 (6), 13111318.CrossRefGoogle Scholar
Ghafory-Ashtiany, M., Mousavi, M., and Azarbakht, A. 2011. Strong Ground Motion Record Selection for the Reliable Prediction of the Mean Seismic Collapse Capacity of a Structure Group. Earthquake Engineering & Structural Dynamics, 40 (6), 691708.CrossRefGoogle Scholar
Gledhill, K., Ristau, J., Reyners, M., Fry, B., and Holden, C. 2011. The Darfield (Canterbury, New Zealand) Mw 7.1 Earthquake of September 2010: A Preliminary Seismological Report. Seismological Research Letters, 82 (3), 378386.CrossRefGoogle Scholar
Goda, K. 2011. Interevent Variability of Spatial Correlation of Peak Ground Motions and Response Spectra. Bulletin of the Seismological Society of America, 101 (5), 25222531.CrossRefGoogle Scholar
Goda, K., and Atkinson, G. M. 2010. Intraevent Spatial Correlation of Ground-Motion Parameters Using SK-Net Data. Bulletin of the Seismological Society of America, 100 (6), 30553067.CrossRefGoogle Scholar
Goda, K., and Atkinson, G. M. 2014. Variation of Source-to-Site Distance for Megathrust Subduction Earthquakes: Effects on Ground Motion Prediction Equations. Earthquake Spectra, 30 (2), 845866.CrossRefGoogle Scholar
Goda, K., and Hong, H. P. 2008. Spatial Correlation of Peak Ground Motions and Response Spectra. Bulletin of the Seismological Society of America, 98 (1), 354365.CrossRefGoogle Scholar
González Ortega, J. A., González García, J. J., and Sandwell, D. T. 2018. Interseismic Velocity Field and Seismic Moment Release in Northern Baja California, Mexico. Seismological Research Letters, 89 (2A), 526533.CrossRefGoogle Scholar
Goovaerts, P. 1997. Geostatistics for Natural Resources Evaluation. Applied Geostatistics Series. New York: Oxford University Press.Google Scholar
Gospodinov, D. 2017. Spatio-Temporal Evolution of Aftershock Energy Release Following the 1989, Mw6.9, Loma Prieta Earthquake in California. Acta Geophysica, 65 (3), 565573.CrossRefGoogle Scholar
Graves, R. 1993. Modeling Three-Dimensional Site Response Effects in the Marina District Basin, San Francisco, California. Bulletin of the Seismological Society of America, 83 (4), 10421063.CrossRefGoogle Scholar
Graves, R., Jordan, T. H., Callaghan, S., Deelman, E., Field, E., Juve, G., Kesselman, C., Maechling, P., Mehta, G., Milner, K., et al. 2011a. CyberShake: A Physics-Based Seismic Hazard Model for Southern California. Pure and Applied Geophysics, 168 (3–4), 367381.CrossRefGoogle Scholar
Graves, R., Jordan, T., Callaghan, S., Deelman, E., Field, E., Juve, G., Kesselman, C., Maechling, P., Mehta, G., Milner, K., Okaya, D., Small, P., and Vahi, K. 2011b. CyberShake: A Physics-Based Seismic Hazard Model for Southern California. Pure and Applied Geophysics, 168 (3), 367381.CrossRefGoogle Scholar
Graves, R., and Pitarka, A. 2015. Refinements to the Graves and Pitarka (2010) Broadband Ground-Motion Simulation Method. Seismological Research Letters, 86 (1), 7580.CrossRefGoogle Scholar
Graves, R., and Pitarka, A. 2016. Kinematic Ground-Motion Simulations on Rough Faults Including Effects of 3D Stochastic Velocity Perturbations. Bulletin of the Seismological Society of America, 106 (5), 21362153.CrossRefGoogle Scholar
Graves, R. W. 1996. Simulating Seismic Wave Propagation in 3D Elastic Media Using Staggered-Grid Finite Differences. Bulletin of the Seismological Society of America, 86 (4), 10911106.Google Scholar
Graves, R. W., and Pitarka, A. 2010. Broadband Ground-Motion Simulation Using a Hybrid Approach. Bulletin of the Seismological Society of America, 100 (5A), 20952123.CrossRefGoogle Scholar
Gregor, N., Abrahamson, N. A., Atkinson, G. M., Boore, D. M., Bozorgnia, Y., Campbell, K. W., Chiou, B. S.-J., Idriss, I. M., Kamai, R., Seyhan, E., Silva, W., Stewart, J. P., and Youngs, R. 2014. Comparison of NGA-West2 GMPEs. Earthquake Spectra, 30 (3), 11791197.CrossRefGoogle Scholar
Grossi, P., Kunreuther, H., and Patel, C. C. 2005. Catastrophe Modeling: A New Approach to Managing Risk. Springer.CrossRefGoogle Scholar
Guatteri, M., Mai, P. M., and Beroza, G. C. 2004. A Pseudo-Dynamic Approximation to Dynamic Rupture Models for Strong Ground Motion Prediction. Bulletin of the Seismological Society of America, 94 (6), 20512063.CrossRefGoogle Scholar
Gulerce, Z., and Abrahamson, N. A. 2011. Site-Specific Design Spectra for Vertical Ground Motion. Earthquake Spectra, 27 (4), 10231047.CrossRefGoogle Scholar
Gutenberg, B., and Richter, C. F. 1944. Frequency of Earthquakes in California. Bulletin of the Seismological Society of America, 34 (4), 185188.CrossRefGoogle Scholar
Haarala, M., and Orosco, L. 2016. Analysis of Gutenberg-Richter b-Value and Mmax. Part I: Exact Solution of Kijko–Sellevoll Estimator of Mmax. Cuadernos de Ingeniería, Nueva Serie, 9 , 5177.Google Scholar
Hale, C., Abrahamson, N., and Bozorgnia, Y. 2018. Probabilistic Seismic Hazard Analysis Code Verification. PEER Report 2018/03. Berkeley, CA.Google Scholar
Halsey, L. G., Curran-Everett, D., Vowler, S. L., and Drummond, G. B. 2015. The Fickle P Value Generates Irreproducible Results. Nature Methods, 12 (3), 179185.CrossRefGoogle ScholarPubMed
Han, Y., and Davidson, R. A. 2012. Probabilistic Seismic Hazard Analysis for Spatially Distributed Infrastructure. Earthquake Engineering & Structural Dynamics, 41 (15), 21412158.Google Scholar
Hancock, J., and Bommer, J. J. 2006. A State-of-Knowledge Review of the Influence of Strong-Motion Duration on Structural Damage. Earthquake Spectra, 22 , 827.CrossRefGoogle Scholar
Hancock, J., and Bommer, J. J. 2007. Using Spectral Matched Records to Explore the Influence of Strong-Motion Duration on Inelastic Structural Response. Soil Dynamics and Earthquake Engineering, 27 (4), 291299.CrossRefGoogle Scholar
Hancock, J., Bommer, J. J., and Stafford, P. J. 2008. Numbers of Scaled and Matched Accelerograms Required for Inelastic Dynamic Analyses. Earthquake Engineering & Structural Dynamics, 37 (14), 15851607.CrossRefGoogle Scholar
Hanks, T., and McGuire, R. 1981. The Character of High-Frequency Strong Ground Motion. Bulletin of the Seismological Society of America, 71 (6), 20712095.CrossRefGoogle Scholar
Hanks, T. C. 1977. Earthquake Stress Drops, Ambient Tectonic Stresses and Stresses That Drive Plate Motions. Pure and Applied Geophysics, 115 , 441458.CrossRefGoogle Scholar
Hanks, T. C., and Abrahamson, N. 2008. A Brief History of Extreme Ground Motions. Seismological Research Letters, 79 , 282283.Google Scholar
Hanks, T. C., Abrahamson, N. A., Boore, D. M., Coppersmith, K. J., and Knepprath, N. E. 2009. Implementation of the SSHAC Guidelines for Level 3 and 4 PSHAs—Experience Gained from Actual Applications. Open-File Report 2009-1093. US Geological Survey.CrossRefGoogle Scholar
Hanks, T. C., and Bakun, W. H. 2002. A Bilinear Source-Scaling Model for M-logA Observations of Continental Earthquakes. Bulletin of the Seismological Society of America, 92 (5), 18411846.CrossRefGoogle Scholar
Hanks, T. C., and Bakun, W. H. 2008. M-logA Observations for Recent Large Earthquakes. Bulletin of the Seismological Society of America, 98 (1), 490494.CrossRefGoogle Scholar
Hanks, T. C., Beroza, G. C., and Toda, S. 2012. Have Recent Earthquakes Exposed Flaws in or Misunderstandings of Probabilistic Seismic Hazard Analysis? Seismological Research Letters, 83 (5), 759764.CrossRefGoogle Scholar
Hanks, T. C., and Kanamori, H. 1979. A Moment Magnitude Scale. Journal of Geophysical Research, 84 (B5), 2348.CrossRefGoogle Scholar
Harichandran, R. S., Hawwari, A., and Sweidan, B. N. 1996. Response of Long-Span Bridges to Spatially Varying Ground Motion. Journal of Structural Engineering, 122 (5), 476484.CrossRefGoogle Scholar
Hartford, D. N. D. 2009. Legal Framework Considerations in the Development of Risk Acceptance Criteria. Structural Safety, 31 (2), 118123.CrossRefGoogle Scholar
Hartzell, S., Frankel, A., Liu, P., Zeng, Y., and Rahman, S. 2011. Model and Parametric Uncertainty in Source-Based Kinematic Models of Earthquake Ground Motion. Bulletin of the Seismological Society of America, 101 (5), 24312452.CrossRefGoogle Scholar
Hartzell, S., Harmsen, S., and Frankel, A. 2010. Effects of 3D Random Correlated Velocity Perturbations on Predicted Ground Motions. Bulletin of the Seismological Society of America, 100 (4), 14151426.CrossRefGoogle Scholar
Hartzell, S., Harmsen, S., Frankel, A., and Larsen, S. 1999. Calculation of Broadband Time Histories of Ground Motion: Comparison of Methods and Validation Using Strong-Ground Motion from the 1994 Northridge Earthquake. Bulletin of the Seismological Society of America, 89 (6), 14841504.Google Scholar
Hashash, Y. M., Hook, J. J., Schmidt, B., John, I., and Yao, C. 2001. Seismic Design and Analysis of Underground Structures. Tunnelling and Underground Space Technology, 16 (4), 247293.CrossRefGoogle Scholar
Hastie, T., Tibshirani, R., and Friedman, J. 2001. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. New York: Springer.CrossRefGoogle Scholar
Hawkes, A. G., and Adamopoulos, L. 1973. Cluster Models for Earthquakes: Regional Comparisons. Bulletin of the International Statistical Institute, 45 (3), 454461.Google Scholar
Hayes, G. P., Earle, P. S., Benz, H. M., Wald, D. J., Briggs, R. W., and the USGS/NEIC Earthquake Response Team. 2011. 88 Hours: The U.S. Geological Survey National Earthquake Information Center Response to the 11 March 2011 Mw 9.0 Tohoku Earthquake. Seismological Research Letters, 82 (4), 481493.CrossRefGoogle Scholar
Headquarters for Earthquake Research Promotion. 2005. National Seismic Hazard Maps for Japan. www.jishin.go.jp/main/index-e.html.Google Scholar
Heaton, T. H. 1990. Evidence for and Implications of Self-Healing Pulses of Slip in Earthquake Rupture. Physics of the Earth and Planetary Interiors, 64 (1), 120.CrossRefGoogle Scholar
Heresi, P., and Miranda, E. 2019. Uncertainty in Intraevent Spatial Correlation of Elastic Pseudo-Acceleration Spectral Ordinates. Bulletin of Earthquake Engineering, 17 (3), 10991115.CrossRefGoogle Scholar
Holt, W. E., and Haines, A. J. 1995. The Kinematics of Northern South Island, New Zealand, Determined from Geologic Strain Rates. Journal of Geophysical Research: Solid Earth, 100 (B9), 1799118010.CrossRefGoogle Scholar
Hough, S. E., and Anderson, J. G. 1988. High-Frequency Spectra Observed at Anza, California: Implications for Q Structure. Bulletin of the Seismological Society of America, 78 (2), 692707.CrossRefGoogle Scholar
Husen, S., and Hardebeck, J. 2010. Earthquake Location Accuracy. Community Online Resource for Statistical Seismicity Analysis, CORSSA, www.corssa.org.Google Scholar
Hutchings, L. 1994. Kinematic Earthquake Models and Synthesized Ground Motion Using Empirical Green’s Functions. Bulletin of the Seismological Society of America, 84 (4), 10281050.Google Scholar
Ibarra, L. F., and Krawinkler, H. 2005. Global Collapse of Frame Structures under Seismic Excitations. 152. John A. Blume Earthquake Engineering Center, Stanford, CA.Google Scholar
Idriss, I., and Boulanger, R. 2008. Soil Liquefaction during Earthquakes. Earthquake Engineering Research Institute.Google Scholar
Idriss, I., and Seed, H. 1968. Seismic Response of Horizontal Soil Layers. Journal of Soil Mechanics and Foundations (ASCE), 94 (SM4), 10031031.CrossRefGoogle Scholar
Iervolino, I., De Luca, F., and Cosenza, E. 2010. Spectral Shape-Based Assessment of SDOF Nonlinear Response to Real, Adjusted and Artificial Accelerograms. Engineering Structures, 32 (9), 27762792.CrossRefGoogle Scholar
Iervolino, I., Giorgio, M., and Polidoro, B. 2014. Sequence-Based Probabilistic Seismic Hazard Analysis. Bulletin of the Seismological Society of America, 104 (2), 10061012.CrossRefGoogle Scholar
Imperatori, W., and Mai, P. M. 2013. Broad-band Near-Field Ground Motion Simulations in 3-Dimensional Scattering Media. Geophysical Journal International, 192 (2), 725744.CrossRefGoogle Scholar
Imperatori, W., and Mai, P. M. 2015. The Role of Topography and Lateral Velocity Heterogeneities on Near-Source Scattering and Ground-Motion Variability. Geophysical Journal International, 202 (3), 21632181.CrossRefGoogle Scholar
Imtiaz, A., Causse, M., Chaljub, E., and Cotton, F. 2015. Is Ground-Motion Variability Distance Dependent? Insight from Finite-Source Rupture Simulations. Bulletin of the Seismological Society of America, 105 (2A), 950962.CrossRefGoogle Scholar
Inoue, T., and Cornell, C. A. 1990. Seismic Hazard Analysis of Multi-Degree-of-Freedom Structures. RMS-8. Reliability of Marine Structures, Stanford, CA.Google Scholar
Ishihara, K., and Cubrinovski, M. 2005. Characteristics of Ground Motion in Liquefied Deposits during Earthquakes. Journal of Earthquake Engineering, 9 (S1), 115.CrossRefGoogle Scholar
Jaeger, J. C., Cook, N. G. W., and Zimmerman, R. W. 2007. Fundamentals of Rock Mechanics. Blackwell Publishing.Google Scholar
Jaiswal, K., Wald, D., and D’Ayala, D. 2011b. Developing Empirical Collapse Fragility Functions for Global Building Types. Earthquake Spectra, 27 (3), 775795.CrossRefGoogle Scholar
Jaiswal, K. S., Aspinall, W., Perkins, D., Wald, D., and Porter, K. A. 2012. Use of Expert Judgment Elicitation to Estimate Seismic Vulnerability of Selected Building Types. In: 15th World Conference on Earthquake Engineering.Google Scholar
Jaiswal, K. S., Wald, D. J., Earle, P. S., Porter, K. A., and Hearne, M. 2011a. Earthquake Casualty Models within the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) System. Pages 8394 of: Spence, R., So, E., and Scawthorn, C. (eds.), Human Casualties in Earthquakes: Progress in Modelling and Mitigation. Advances in Natural and Technological Hazards Research. Dordrecht: Springer Netherlands.CrossRefGoogle Scholar
Jalayer, F. 2003. Direct Probabilistic Seismic Analysis: Implementing Non-linear Dynamic Assessments. PhD thesis, Dept. of Civil and Environmental Engineering, Stanford University.Google Scholar
Jayaram, N., and Baker, J. W. 2008. Statistical Tests of the Joint Distribution of Spectral Acceleration Values. Bulletin of the Seismological Society of America, 98 (5), 22312243.CrossRefGoogle Scholar
Jayaram, N., and Baker, J. W. 2009. Correlation Model for Spatially Distributed Ground-Motion Intensities. Earthquake Engineering & Structural Dynamics, 38 (15), 16871708.CrossRefGoogle Scholar
Jayaram, N., and Baker, J. W. 2010a. Considering Spatial Correlation in Mixed-Effects Regression, and Impact on Ground-Motion Models. Bulletin of the Seismological Society of America, 100 (6), 32953303.CrossRefGoogle Scholar
Jayaram, N., and Baker, J. W. 2010b. Efficient Sampling and Data Reduction Techniques for Probabilistic Seismic Lifeline Risk Assessment. Earthquake Engineering & Structural Dynamics, 39 (10), 11091131.Google Scholar
Jayaram, N., Lin, T., and Baker, J. W. 2011. A Computationally Efficient Ground-Motion Selection Algorithm for Matching a Target Response Spectrum Mean and Variance. Earthquake Spectra, 27 (3), 797815.CrossRefGoogle Scholar
Jayaram, N., Park, J., Bazzurro, P., and Tothong, P. 2010. Estimation of Spatial Correlation between Spectral Accelerations Using Simulated Ground-Motion Time Histories. In: 9th US National and 10th Canadian Conference on Earthquake Engineering.Google Scholar
Jayaram, N., Shome, N., and Rahnama, M. 2012. Development of Earthquake Vulnerability Functions for Tall Buildings. Earthquake Engineering & Structural Dynamics, 41 (11), 14951514.CrossRefGoogle Scholar
Jeon, S.-S., and O’Rourke, T. D. 2005. Northridge Earthquake Effects on Pipelines and Residential Buildings. Bulletin of the Seismological Society of America, 95 (1), 294318.CrossRefGoogle Scholar
Johnston, A. C., Coppersmith, K. J., Kanter, L. R., and Cornell, C. A. 1994. The Earthquakes of Stable Continental Regions. EPRI Report TR-102261s-V1-V5. Electric Power Research Institute, Palo Alto, CA.Google Scholar
Jordan, T. H. 2006. Earthquake Predictability, Brick by Brick. Seismological Research Letters, 77 (1), 36.CrossRefGoogle Scholar
Journel, A. G., and Huijbregts, C. J. 1978. Mining Geostatistics. London: Academic Press.Google Scholar
Kagan, Y. Y. 2006. Why Does Theoretical Physics Fail to Explain and Predict Earthquake Occurrence? Pages 303362 of: Bhattacharyya, P., and Chakrabarti, B. K. (eds.), Modelling Critical and Catastrophic Phenomena in Geoscience. Springer.CrossRefGoogle Scholar
Kagan, Y. Y., and Knopoff, L. 1981. Stochastic Synthesis of Earthquake Catalogs. Journal of Geophysical Research: Solid Earth, 86 (B4), 28532862.CrossRefGoogle Scholar
Kagan, Y. Y., and Jackson, D. D. 2013. Tohoku Earthquake: A Surprise? Bulletin of the Seismological Society of America, 103 (2B), 11811194.CrossRefGoogle Scholar
Kamai, R., Abrahamson, N. A., and Silva, W. J. 2014. Nonlinear Horizontal Site Amplification for Constraining the NGA-West2 GMPEs. Earthquake Spectra, 30 (3), 12231240.CrossRefGoogle Scholar
Kanamori, H., Mori, J., Hauksson, E., Heaton, T. H., Hutton, L. K., and Jones, L. M. 1993. Determination of Earthquake Energy Release and ML Using Terrascope. Bulletin of the Seismological Society of America, 83 (2), 330346.Google Scholar
Katsanos, E. I., Sextos, A. G., and Manolis, G. D. 2010. Selection of Earthquake Ground Motion Records: A State-of-the-Art Review from a Structural Engineering Perspective. Soil Dynamics and Earthquake Engineering, 30 (4), 157169.CrossRefGoogle Scholar
Kawase, H. 1996. The Cause of the Damage Belt in Kobe: “The Basin-Edge Effect,” Constructive Interference of the Direct S-Wave with the Basin-Induced Diffracted/Rayleigh Waves. Seismological Research Letters, 67 (5), 2534.CrossRefGoogle Scholar
Keefer, D. L., and Bodily, S. E. 1983. Three-Point Approximations for Continuous Random Variables. Management Science, 29 (5), 595609.CrossRefGoogle Scholar
Kennedy, R. P. 2011. Performance-Goal Based (Risk Informed) Approach for Establishing the SSE Site Specific Response Spectrum for Future Nuclear Power Plants. Nuclear Engineering and Design, 241 (3), 648656.CrossRefGoogle Scholar
Kennedy, R. P., Cornell, C. A., Campbell, R. D., Kaplan, S., and Perla, H. F. 1980. Probabilistic Seismic Safety Study of an Existing Nuclear Power Plant. Nuclear Engineering and Design, 59 (2), 315338.CrossRefGoogle Scholar
Kennedy, R. P., and Ravindra, M. K. 1984. Seismic Fragilities for Nuclear Power Plant Risk Studies. Nuclear Engineering and Design, 79 (1), 4768.CrossRefGoogle Scholar
Kennedy, R., and Short, S. 1994. Basis for Seismic Provisions of DOE-STD-1020. UCRL-CR-111478 and BNL-52418. Lawrence Livermore National Laboratory and Brookhaven National Laboratory.CrossRefGoogle Scholar
Kijko, A. 2004. Estimation of the Maximum Earthquake Magnitude, Mmax. Pure and Applied Geophysics, 161 , 16551681.CrossRefGoogle Scholar
Kijko, A., and Graham, G. 1998. Parametric-Historic Procedure for Probabilistic Seismic Hazard Analysis. Part I: Estimation of Maximum Regional Magnitude Mmax. Pure and Applied Geophysics, 152 , 413442.CrossRefGoogle Scholar
Kijko, A., and Sellevoll, M. A. 1989. Estimation of Earthquake Hazard Parameters from Incomplete Data Files. Part I. Utilization of Extreme and Complete Catalog with Different Threshold Magnitudes. Bulletin of the Seismological Society of America, 79 (3), 645654.CrossRefGoogle Scholar
King, G. C. P., Stein, R. S., and Lin, J. 1994. Static Stress Changes and the Triggering of Earthquakes. Bulletin of the Seismological Society of America, 84 (3), 935953.Google Scholar
Kircher, C. A., Nassar, A. A., Kustu, O., and Holmes, W. T. 1997. Development of Building Damage Functions for Earthquake Loss Estimation. Earthquake Spectra, 13 (4), 663682.CrossRefGoogle Scholar
Kircher, C. A., Seligson, H. A., Bouabid, J., and Morrow, G. C. 2006. When the Big One Strikes Again: Estimated Losses Due to a Repeat of the 1906 San Francisco Earthquake. Earthquake Spectra, 22 (S2), 297339.CrossRefGoogle Scholar
Kiremidjian, A. S., Stergiou, E., and Lee, R. 2007. Issues in Seismic Risk Assessment of Transportation Networks. Pages 461480 of: Earthquake Geotechnical Engineering. Springer.CrossRefGoogle Scholar
Klein, F. 2006. Y2000 Shadow Format & NCSN Data Codes. Online Report www.ncedc.org/ftp/pub/doc/ncsn/shadow2000.pdf. Northern California Earthquake Data Center.Google Scholar
Klinger, Y., Sieh, K., Altunel, E., Akoglu, A., Barka, A., Dawson, T., Gonzalez, T., Meltzner, A., and Rockwell, T. 2003. Paleoseismic Evidence of Characteristic Slip on the Western Segment of the North Anatolian Fault, Turkey. Bulletin of the Seismological Society of America, 93 (6), 23172332.CrossRefGoogle Scholar
Komatitsch, D., and Tromp, J. 1999. Introduction to the Spectral Element Method for Three-Dimensional Seismic Wave Propagation. Geophysical Journal International, 139 (3), 806822.CrossRefGoogle Scholar
Konno, K., and Ohmachi, T. 1998. Ground-Motion Characteristics Estimated From Spectral Ratio between Horizontal and Vertical Components of Microtremor. Bulletin of the Seismological Society of America, 88 (1), 228241.CrossRefGoogle Scholar
Kotha, S. R., Bindi, D., and Cotton, F. 2017. Site-Corrected Magnitude- and Region-Dependent Correlations of Horizontal Peak Spectral Amplitudes. Earthquake Spectra, 33 (4), 14151432.CrossRefGoogle Scholar
Kottke, A., and Rathje, E. M. 2008. A Semi-Automated Procedure for Selecting and Scaling Recorded Earthquake Motions for Dynamic Analysis. Earthquake Spectra, 24 (4), 911932.CrossRefGoogle Scholar
Kottke, A. R., and Rathje, E. M. 2009. Technical Manual for Strata. PEER Report 2008/10. Pacific Earthquake Engineering Research Center.Google Scholar
Kottke, A. R., and Rathje, E. M. 2013. Comparison of Time Series and Random-Vibration Theory Site-Response Methods. Bulletin of the Seismological Society of America, 103 (3), 21112127.CrossRefGoogle Scholar
Kramer, S. L. 1996. Geotechnical Earthquake Engineering. Prentice Hall.Google Scholar
Kramer, S. L., and Mitchell, R. A. 2006. Ground Motion Intensity Measures for Liquefaction Hazard Evaluation. Earthquake Spectra, 22 (2), 413438.CrossRefGoogle Scholar
Krawinkler, H., and Miranda, E. 2004. Performance-Based Earthquake Engineering. In: Bozorgnia, Y., and Bertero, V. V. (eds.), Earthquake Engineering: From Engineering Seismology to Performance-Based Engineering. Boca Raton, FL: CRC Press.Google Scholar
Krayer von Krauss, M. P., Casman, E. A., and Small, M. J. 2004. Elicitation of Expert Judgments of Uncertainty in the Risk Assessment of Herbicide-Tolerant Oilseed Crops. Risk Analysis: An International Journal, 24 (6), 15151527.CrossRefGoogle ScholarPubMed
Ktenidou, O.-J., Cotton, F., Abrahamson, N. A., and Anderson, J. G. 2014. Taxonomy of κ:A Review of Definitions and Estimation Approaches Targeted to Applications. Seismological Research Letters, 85 (1), 135146.CrossRefGoogle Scholar
Kuehn, N. M., and Abrahamson, N. A. 2018. The Effect of Uncertainty in Predictor Variables on the Estimation of Ground-Motion Prediction Equations. Bulletin of the Seismological Society of America, 108 (1), 358370.CrossRefGoogle Scholar
Kuehn, N. M., and Abrahamson, N. A. 2020. Spatial Correlations of Ground Motion for Non-ergodic Seismic Hazard Analysis. Earthquake Engineering & Structural Dynamics, 49 (1), 423.CrossRefGoogle Scholar
Kuehn, N. M., Abrahamson, N. A., and Baltay, A. 2016. Estimating Spatial Correlations between Earthquake Source, Path and Site Effects for Non-ergodic Seismic Hazard Analysis. In: Annual Meeting of the Seismological Society of America.Google Scholar
Kuehn, N. M., Abrahamson, N. A., and Walling, M. 2019. Incorporating Non-ergodic Path Effects into the NGA West 2 Ground-Motion Prediction Equations. Bulletin of the Seismological Society of America, 109 (2), 575585.CrossRefGoogle Scholar
Kulkarni, R. B., Youngs, R. R., and Coppersmith, K. J. 1984. Assessment of Confidence Intervals for Results of Seismic Hazard Analysis. Pages 263–270 of: Proceedings of the Eighth World Conference on Earthquake Engineering, vol. 1.Google Scholar
Kullback, S., and Leibler, R. A. 1951. On Information and Sufficiency. The Annals of Mathematical Statistics, 22 (1), 7986.CrossRefGoogle Scholar
Kutner, M. H., Nachtsheim, C., and Neter, J. 2004. Applied Linear Regression Models, 4th ed. Boston: McGraw-Hill/Irwin.Google Scholar
Kwak, D. Y., Stewart, J. P., Brandenberg, S. J., and Mikami, A. 2016a. Characterization of Seismic Levee Fragility Using Field Performance Data. Earthquake Spectra, 32 (1), 193215.CrossRefGoogle Scholar
Kwak, D. Y., Stewart, J. P., Brandenberg, S. J., and Mikami, A. 2016b. Seismic Levee System Fragility Considering Spatial Correlation of Demands and Component Fragilities. Earthquake Spectra, 32 (4), 22072228.CrossRefGoogle Scholar
Kwok, A. O., and Stewart, J. P. 2006. Evaluation of the Effectiveness of Theoretical 1D Amplification Factors for Earthquake Ground-Motion Prediction. Bulletin of the Seismological Society of America, 96 (4A), 14221436.CrossRefGoogle Scholar
Lallemant, D., and Kiremidjian, A. 2015. A Beta Distribution Model for Characterizing Earthquake Damage State Distribution. Earthquake Spectra, 31 (3), 13371352.CrossRefGoogle Scholar
Landwehr, N., Kuehn, N. M., Scheffer, T., and Abrahamson, N. 2016. A Nonergodic Ground-Motion Model for California with Spatially Varying Coefficients. Bulletin of the Seismological Society of America, 106 (6), 25742583.CrossRefGoogle Scholar
Lay, T., and Wallace, T. C. 1995. Modern Global Seismology. Academic Press.Google Scholar
Lee, R., and Kiremidjian, A. 2007. Uncertainty and Correlation for Loss Assessment of Spatially Distributed Systems. Earthquake Spectra, 23 (4), 753770.CrossRefGoogle Scholar
Lee, R. L., Bradley, B. A., Ghisetti, F. C., and Thomson, E. M. 2017. Development of a 3D Velocity Model of the Canterbury, New Zealand, Region for Broadband Ground-Motion Simulation. Bulletin of the Seismological Society of America, 107 (5), 21312150.CrossRefGoogle Scholar
Lee, R. L., Bradley, B. A., Stafford, P. J., Graves, R. W., and Rodriguez-Marek, A. 2020. Hybrid Broadband Ground Motion Simulation Validation of Small Magnitude Earthquakes in Canterbury, New Zealand. Earthquake Spectra, 36 (2), 673699.CrossRefGoogle Scholar
Leonard, M. 2010. Earthquake Fault Scaling: Self-Consistent Relating of Rupture Length, Width, Average Displacement, and Moment Release. Bulletin of the Seismological Society of America, 100 (5A), 19711988.CrossRefGoogle Scholar
Leonard, M. 2014. Self-Consistent Earthquake Fault-Scaling Relations: Update and Extension to Stable Continental Strike-Slip Faults. Bulletin of the Seismological Society of America, 104 (6), 29532965.CrossRefGoogle Scholar
Liel, A., Haselton, C., Deierlein, G. G., and Baker, J. W. 2009. Incorporating Modeling Uncertainties in the Assessment of Seismic Collapse Risk of Buildings. Structural Safety, 31 (2), 197211.CrossRefGoogle Scholar
Lienkaemper, J. J. 2002. A Record of Large Earthquakes on the Southern Hayward Fault for the Past 500 Years. Bulletin of the Seismological Society of America, 92 (7), 26372658.CrossRefGoogle Scholar
Lienkaemper, J. J., and Borchardt, G. 1996. Holocene Slip Rate of the Hayward Fault at Union City, California. Journal of Geophysical Research: Solid Earth, 101 (B3), 60996108.CrossRefGoogle Scholar
Lienkaemper, J. J., and Williams, P. L. 2007. A Record of Large Earthquakes on the Southern Hayward Fault for the Past 1800 Years. Bulletin of the Seismological Society of America, 97 (6), 18031819.CrossRefGoogle Scholar
Lin, T., Harmsen, S. C., Baker, J. W., and Luco, N. 2013c. Conditional Spectrum Computation Incorporating Multiple Causal Earthquakes and Ground-Motion Prediction Models. Bulletin of the Seismological Society of America, 103 (2A), 11031116.CrossRefGoogle Scholar
Lin, T., Haselton, C. B., and Baker, J. W. 2013a. Conditional Spectrum-Based Ground Motion Selection. Part I: Hazard Consistency for Risk-Based Assessments. Earthquake Engineering & Structural Dynamics, 42 (12), 18471865.CrossRefGoogle Scholar
Lin, T., Haselton, C. B., and Baker, J. W. 2013b. Conditional spectrum-based ground motion selection. Part II: Intensity-based assessments and evaluation of alternative target spectra. Earthquake Engineering & Structural Dynamics, 42 (12), 18671884.CrossRefGoogle Scholar
Liu, P., Archuleta, R. J., and Hartzell, S. H. 2006. Prediction of Broadband Ground-Motion Time Histories: Hybrid Low/High-Frequency Method with Correlated Random Source Parameters. Bulletin of the Seismological Society of America, 96 (6), 21182130.CrossRefGoogle Scholar
Loth, C., and Baker, J. W. 2013. A Spatial Cross-Correlation Model for Ground Motion Spectral Accelerations at Multiple Periods. Earthquake Engineering & Structural Dynamics, 42 (3), 397417.CrossRefGoogle Scholar
Luco, N., Bachman, R. E., Crouse, C. B., Harris, J. R., Hooper, J. D., Kircher, C. A., Caldwell, P. J., and Rukstales, K. S. 2015. Updates to Building-Code Maps for the 2015 NEHRP Recommended Seismic Provisions. Earthquake Spectra, 31 (S1), S245S271.CrossRefGoogle Scholar
Luco, N., and Bazzurro, P. 2007. Does Amplitude Scaling of Ground Motion Records Result in Biased Nonlinear Structural Drift Responses? Earthquake Engineering & Structural Dynamics, 36 (13), 18131835.CrossRefGoogle Scholar
Luco, N., and Cornell, C. 2007. Structure-Specific Scalar Intensity Measures for Near-Source and Ordinary Earthquake Ground Motions. Earthquake Spectra, 23 (2), 357392.CrossRefGoogle Scholar
Luco, N., Ellingwood, B. R., Hamburger, R. O., Hooper, J. D., Kimball, J. K., and Kircher, C. A. 2007. Risk-Targeted versus Current Seismic Design Maps for the Conterminous United States. In: Proceedings of the 2007 Structural Engineers Association of California (SEAOC) Convention.Google Scholar
Lutes, L. D., and Sarkani, S. 2004. Random Vibrations: Analysis of Structural and Mechanical Systems. Burlington, MA: Butterworth-Heinemann.Google Scholar
Macedo, J., Abrahamson, N., and Bray, J. D. 2019. Arias Intensity Conditional Scaling Ground-Motion Models for Subduction Zones. Bulletin of the Seismological Society of America, 109 (4), 13431357.CrossRefGoogle Scholar
Mackie, K., and Stojadinovic, B. 2005. Comparison of Incremental Dynamic, Cloud, and Stripe Methods for Computing Probabilistic Seismic Demand Models. In: ASCE Structures Congress.CrossRefGoogle Scholar
Madariaga, R. 1977. Implications of Stress-Drop Models of Earthquakes for the Inversion of Stress Drop from Seismic Observations. Pure and Applied Geophysics, 115 , 301316.CrossRefGoogle Scholar
Magistrale, H., and Day, S. 1999. 3D Simulations of Multi-segment Thrust Fault Rupture. Geophysical Research Letters, 26 (14), 20932096.CrossRefGoogle Scholar
Mai, P. M., and Beroza, G. C. 2002. A Spatial Random Field Model to Characterize Complexity in Earthquake Slip. Journal of Geophysical Research, 107 (10.1029), 2001.CrossRefGoogle Scholar
Mai, P. M., and Beroza, G. C. 2003. A Hybrid Method for Calculating Near-Source, Broadband Seismograms: Application to Strong Motion Prediction. Physics of the Earth and Planetary Interiors, 137 (1), 18.Google Scholar
Mai, P. M., Galis, M., Thingbaijam, K. K. S., Vyas, J. C., and Dunham, E. M. 2017. Accounting for Fault Roughness in Pseudo-Dynamic Ground-Motion Simulations. Pure and Applied Geophysics, 174 (9), 34193450.CrossRefGoogle Scholar
Mai, P. M., Imperatori, W., and Olsen, K. B. 2010. Hybrid Broadband Ground-Motion Simulations: Combining Long-Period Deterministic Synthetics with High-Frequency Multiple S-to-S Backscattering. Bulletin of the Seismological Society of America, 100 (5A), 21242142.CrossRefGoogle Scholar
Mai, P. M., Spudich, P., and Boatwrigth, J. 2005. Hypocenter Locations in Finite-Source Rupture Models. Bulletin of the Seismological Society of America, 95 (3), 965980.CrossRefGoogle Scholar
Mak, S., and Schorlemmer, D. 2016. A Comparison between the Forecast by the United States National Seismic Hazard Maps with Recent Ground-Motion Records. Bulletin of the Seismological Society of America, 106 (4), 18171831.CrossRefGoogle Scholar
Mancini, S., Segou, M., Werner, M. J., and Parsons, T. 2020. The Predictive Skills of Elastic Coulomb Rate-and-State Aftershock Forecasts during the 2019 Ridgecrest, California, Earthquake Sequence. Bulletin of the Seismological Society of America, 110 (4), 17361751.CrossRefGoogle Scholar
Marafi, N. A., Berman, J. W., and Eberhard, M. O. 2016. Ductility-Dependent Intensity Measure That Accounts for Ground-Motion Spectral Shape and Duration. Earthquake Engineering & Structural Dynamics, 45 (4), 653672.CrossRefGoogle Scholar
Markhvida, M., Ceferino, L., and Baker, J. W. 2018. Modeling Spatially Correlated Spectral Accelerations at Multiple Periods Using Principal Component Analysis and Geostatistics. Earthquake Engineering & Structural Dynamics, 47 (5), 11071123.CrossRefGoogle Scholar
Marone, C. 1998. The Effect of Loading Rate on Static Friction and the Rate of Fault Healing during the Earthquake Cycle. Nature, 391 , 6972.CrossRefGoogle Scholar
Marzocchi, W., and Jordan, T. H. 2014. Testing for Ontological Errors in Probabilistic Forecasting Models of Natural Systems. Proceedings of the National Academy of Sciences, 111 (33), 1197311978.CrossRefGoogle ScholarPubMed
Marzocchi, W., and Jordan, T. H. 2017. A Unified Probabilistic Framework for Seismic Hazard Analysis. Bulletin of the Seismological Society of America, 107 (6), 27382744.CrossRefGoogle Scholar
Matasovic, N., and Hashash, Y. 2012. Practices and Procedures for Site-Specific Evaluations of Earthquake Ground Motions: A Synthesis of Highway Practice. National Academies of Sciences, Engineering, and Medicine. Washington, DC.Google Scholar
Matthews, M. V., Ellsworth, W. L., and Reasenberg, P. A. 2002. A Brownian Model for Recurrent Earthquakes. Bulletin of the Seismological Society of America, 92 (6), 22332250.CrossRefGoogle Scholar
Maufroy, E., Chaljub, E., Hollender, F., Kristek, J., Moczo, P., Klin, P., Priolo, E., Iwaki, A., Iwata, T., Etienne, V., De Martin, F., Theodoulidis, N. P., Manakou, M., GuyonnetBenaize, C., Pitilakis, K., and Bard, P. 2015. Earthquake Ground Motion in the Mygdonian Basin, Greece: The E2VP Verification and Validation of 3D Numerical Simulation up to 4Hz. Bulletin of the Seismological Society of America, 105 (3), 13981418.CrossRefGoogle Scholar
Mazzieri, I., Stupazzini, M., Guidotti, R., and Smerzini, C. 2013. SPEED: SPectral Elements in Elastodynamics with Discontinuous Galerkin: A Non-Conforming Approach for 3D Multi-scale Problems. International Journal for Numerical Methods in Engineering, 95 (12), 9911010.CrossRefGoogle Scholar
McCalpin, J. P. 2009. Paleoseismology, 2nd ed. International Geophysics Series, vol. 95. Academic Press.Google Scholar
McGinty, P. 2001. Preparation of the New Zealand Earthquake Catalogue for a Probabilistic Seismic Hazard Analysis. Bulletin of the New Zealand Society for Earthquake Engineering, 34 (1), 6067.CrossRefGoogle Scholar
McGuire, R., Cornell, C., and Toro, G. 2005a. The Case for Mean Seismic Hazard. Earthquake Spectra, 21 (3), 879886.CrossRefGoogle Scholar
McGuire, R. K. 1995. Probabilistic Seismic Hazard Analysis and Design Earthquakes: Closing the Loop. Bulletin of the Seismological Society of America, 85 (5), 12751284.CrossRefGoogle Scholar
McGuire, R. K. 2004. Seismic Hazard and Risk Analysis. Berkeley, CA Earthquake Engineering Research Institute.Google Scholar
McGuire, R. K., Cornell, C. A., and Toro, G. R. 2005b. The Case for Using Mean Seismic Hazard. Earthquake Spectra, 21 (3), 879886.CrossRefGoogle Scholar
Melchers, R. E. 2007. Structural Reliability Theory in the Context of Structural Safety. Civil Engineering and Environmental Systems, 24 (1), 5569.CrossRefGoogle Scholar
Michael, A. J., and Werner, M. J. 2018. Preface to the Focus Section on the Collaboratory for the Study of Earthquake Predictability (CSEP): New Results and Future Directions. Seismological Research Letters, 89 (4), 12261228.CrossRefGoogle Scholar
Miller, A. C., and Rice, T. R. 1983. Discrete Approximations of Probability Distributions. Management Science, 29 (3), 352362.CrossRefGoogle Scholar
Ming, D., Huang, C., Peters, G. W., and Galasso, C. 2019. An Advanced Estimation Algorithm for Ground-Motion Models with Spatial Correlation. Bulletin of the Seismological Society of America, 109 (2), 541566.CrossRefGoogle Scholar
Miyazawa, M., and Mori, J. 2009. Test of Seismic Hazard Map from 500Years of Recorded Intensity Data in Japan. Bulletin of the Seismological Society of America, 99 (6), 31403149.CrossRefGoogle Scholar
Moehle, J., and Deierlein, G. G. 2004. A Framework Methodology for Performance-Based Earthquake Engineering. In: Proceedings, 13th World Conference on Earthquake Engineering.Google Scholar
Moehle, J. P., Hamburger, R. O., Baker, J. W., Bray, J. D., Crouse, C. B., Deierlein, G. G., Hooper, J. D., Lew, M., Maffei, J. R., Mahin, S. A., Malley, J., Naeim, F., Stewart, J. P., and Wallace, J. W. 2017. Guidelines for Performance-Based Seismic Design of Tall Buildings Version 2.0. PEER Report 2017/06. Berkeley, CA.Google Scholar
Mohr, O. 1914. Abhandlugen aus dem Gebiete der Technische Mechanik, 2nd ed. Berlin: Ernst und Sohn.Google Scholar
Molkenthin, C., Scherbaum, F., Griewank, A., Kuehn, N., Stafford, P. J., and Leovey, H. 2015. Sensitivity of Probabilistic Seismic Hazard Obtained by Algorithmic Differentiation: A Feasability Study. Bulletin of the Seismological Society of America, 105 (3), 18101822.CrossRefGoogle Scholar
Mosca, I., Console, R., and D’Addezio, G. 2012. Renewal Models of Seismic Recurrence Applied to Paleoseismological and Historical Observations. Tectonophysics, 564565, 5467.CrossRefGoogle Scholar
Moss, R. 2011. Reduced Sigma of Ground-Motion Prediction Equations through Uncertainty Propagation. Bulletin of the Seismological Society of America, 101 (1), 250257.CrossRefGoogle Scholar
Motazedian, D., and Atkinson, G. M. 2005. Stochastic Finite-Fault Modeling Based on a Dynamic Corner Frequency. Bulletin of the Seismological Society of America, 95 (3), 9951010.CrossRefGoogle Scholar
Musson, R. 2010. Ground Motion and Probabilistic Hazard. Bulletin of Earthquake Engineering, 7 (3), 575589.CrossRefGoogle Scholar
Musson, R. 2012b. On the Nature of Logic Trees in Probabilistic Seismic Hazard Assessment. Earthquake Spectra, 28 (3), 12911296.CrossRefGoogle Scholar
Musson, R., and Winter, P. 2012. Objective Assessment of Source Models for Seismic Hazard Studies: With a Worked Example from UK Data. Bulletin of Earthquake Engineering, 10 (2), 367378.CrossRefGoogle Scholar
Musson, R. M. W. 2000. The Use of Monte Carlo Simulations for Seismic Hazard Assessment in the U.K. Annals of Geophysics, 43 (1), 19.CrossRefGoogle Scholar
Musson, R. M. W. 2005. Against Fractiles. Earthquake Spectra, 21 (3), 887891.CrossRefGoogle Scholar
Musson, R. M. W. 2012a. PSHA Validated by Quasi Observational Means. Seismological Research Letters, 83 (1), 130134.CrossRefGoogle Scholar
Myung, I. J. 2003. Tutorial on Maximum Likelihood Estimation. Journal of Mathematical Psychology, 47 (1), 90100.CrossRefGoogle Scholar
National Institute of Standards and Technology. 2012. Selecting and Scaling Earthquake Ground Motions for Performing Response-History Analyses. NIST Report NIST GCR 11-917-15. National Institute of Standards and Technology.Google Scholar
National Research Council. 1996. Understanding Risk: Informing Decisions in a Democratic Society. National Academy Press.Google Scholar
NCEDC. 2014. Northern California Earthquake Data Center. UC Berkeley Seismological Laboratory.Google Scholar
NIST. 2011. Selecting and Scaling Earthquake Ground Motions for Performing Response-History Analyses. NIST GCR 11-917-15. Prepared by the NEHRP Consultants Joint Venture for the National Institute of Standards and Technology, Gaithersburg, MD.Google Scholar
NIST. 2012. Soil–Structure Interaction for Building Structures. Prepared by NEHRP Consultants Joint Venture (a Partnership of the Applied Technology Council and the Consortium of Universities for Research in Earthquake Engineering) GCR 12-917-21. National Institute of Standards and Technology, Gaithersburg, MD.Google Scholar
NRC. 1975. Reactor Safety Study. An Assessment of Accident Risks in US Commercial Nuclear Power Plants. Executive Summary. WASH-1400. United States Nuclear Regulatory Commission.Google Scholar
NRC. 2012. Practical Implementation Guidelines for SSHAC Level 3 and 4 Hazard Studies. US Nuclear Regulatory Commission NUREG-2117. Washington, DC.Google Scholar
NRC. 2018. Updated Implementation Guidelines for SSHAC Hazard Studies. US Nuclear Regulatory Commission NUREG-2213. Washington, DC.Google Scholar
NUREG. 1983. PRA Procedures Guide—A Guide to the Performance of Probabilistic Risk Assessment for Nuclear Power Plants. NUREG/CR-2300. Division of Engineering Technology Office of Nuclear Regulatory Research, US Nuclear Regulatory Commission, Washington, DC.Google Scholar
NZS. 2004. Structural Design Actions–Part 5: Earthquake Design Actions. NZS 1170.5:2004. Standards New Zealand.Google Scholar
Oberkampf, W. L., Trucano, T. G., and Hirsch, C. 2004. Verification, Validation, and Predictive Capability in Computational Engineering and Physics. Applied Mechanics Reviews, 57 (5), 345384.CrossRefGoogle Scholar
Ogata, Y. 1988. Statistical Models for Earthquake Occurrences and Residual Analysis for Point Processes. Journal of the American Statistical Association, 83 (401), 927.CrossRefGoogle Scholar
Okada, Y. 1992. Internal Deformation Due to Shear and Tensile Faults in a Half-Space. Bulletin of the Seismological Society of America, 82 (2), 10181040.CrossRefGoogle Scholar
Olami, Z., Feder, H. J. S., and Christensen, K. 1992. Self-Organized Criticality in a Continuous, Nonconservative Cellular Automaton Modeling Earthquakes. Physical Review Letters, 68 (8), 12441248.CrossRefGoogle Scholar
Olsen, K. 2000. Site Amplification in the Los Angeles Basin from Three-Dimensional Modelling of Ground Motions. Bulletin of the Seismological Society of America, 90 (6B), S77S94.CrossRefGoogle Scholar
Olsen, K., and Takedatsu, R. 2015. The SDSU Broadband Ground-Motion Generation Module BBtoolbox Version 1.5. Seismological Research Letters, 86 (1), 8188.CrossRefGoogle Scholar
Olsen, K. B., and Archuleta, R. J. 1996. Three-Dimensional Simulation of Earthquakes on the Los Angeles Fault System. Bulletin of the Seismological Society of America, 86 (3), 575596.Google Scholar
Olsen, K. B., Pechmann, J. C., and Schuster, G. T. 1995. Simulation of 3D Elastic Wave Propagation in the Salt Lake Basin. Bulletin of the Seismological Society of America, 85 (6), 16881710.CrossRefGoogle Scholar
Omori, F. 1894. On After-Shocks. Seismological Journal of Japan, 19 , 7180.Google Scholar
Ordaz, M., and Reyes, C. 1999. Earthquake Hazard in Mexico City: Observations versus Computations. Bulletin of the Seismological Society of America, 89 (5), 13791383.CrossRefGoogle Scholar
Ou, G.-B., and Herrmann, R. B. 1990. A Statistical Model for Ground Motion Produced by Earthquakes at Local and Regional Distances. Bulletin of the Seismological Society of America, 80 (6A), 13971417.CrossRefGoogle Scholar
Pagani, M., Monelli, D., Weatherill, G., Danciu, L., Crowley, H., Silva, V., Henshaw, P., Butler, L., Nastasi, M., Panzeri, L., et al. 2014. OpenQuake Engine: An Open Hazard (and Risk) Software for the Global Earthquake Model. Seismological Research Letters, 85 (3), 692702.CrossRefGoogle Scholar
Page, M., and Felzer, K. 2015. Southern San Andreas Fault Seismicity Is Consistent with the Gutenberg–Richter Magnitude–Frequency Distribution. Bulletin of the Seismological Society of America, 105 (4), 20702080.CrossRefGoogle Scholar
Page, M. T., and van der Elst, N. J. 2018. TuringStyle Tests for UCERF3 Synthetic Catalogs. Bulletin of the Seismological Society of America, 108 (2), 729741.CrossRefGoogle Scholar
Pagni, C. A., and Lowes, L. N. 2006. Fragility Functions for Older Reinforced Concrete Beam-Column Joints. Earthquake Spectra, 22 (1), 215238.CrossRefGoogle Scholar
Papaspiliou, M., Kontoe, S., and Bommer, J. J. 2012. An Exploration of Incorporating Site Response into PSHA—Part I: Issues Related to Site Response Analysis Methods. Soil Dynamics and Earthquake Engineering, 42 (Nov.), 302315.CrossRefGoogle Scholar
Park, C. B., Miller, R. D., and Xia, J. 1999. Multichannel Analysis of Surface Waves. Geophysics, 64 (3), 800808.CrossRefGoogle Scholar
Park, J., Bazzurro, P., and Baker, J. W. 2007. Modeling Spatial Correlation of Ground Motion Intensity Measures for Regional Seismic Hazard and Portfolio Loss Estimation. In: 10th International Conference on Application of Statistics and Probability in Civil Engineering (ICASP10).Google Scholar
Parsons, T. 2008. Earthquake Recurrence on the South Hayward Fault Is Most Consistent with a Time Dependent, Renewal Process. Geophysical Research Letters, 35 (21), B08313.CrossRefGoogle Scholar
Parsons, T., Console, R., Falcone, G., Murru, M., and Yamashina, K. 2012. Comparison of Characteristic and Gutenberg–Richter Models for Time-Dependent M 7.9 Earthquake Probability in the Nankai-Tokai Subduction Zone, Japan. Geophysical Journal International, 190 (3), 16731688.CrossRefGoogle Scholar
Parsons, T., and Geist, E. L. 2009. Is There a Basis for Preferring Characteristic Earthquakes over a Gutenberg–Richter Distribution in Probabilistic Earthquake Forecasting? Bulletin of the Seismological Society of America, 99 (3), 20122019.CrossRefGoogle Scholar
Parsons, T., Johnson, K. M., Bird, P., Bormann, J., Dawson, T. E., Field, E. H., Hammond, W. C., Herring, T. A., McCaffrey, R., Shen, Z.-K., Thatcher, W. R., Weldon, R. J. I., and Zeng, Y. 2013. Appendix C: Deformation Models for UCERF3. Open File Report 2013-1165. United States Geological Survey.Google Scholar
Pate-Cornell, M. E. 1994. Quantitative Safety Goals for Risk Management of Industrial Facilities. Structural Safety, 13 (3), 145157.CrossRefGoogle Scholar
Petersen, M. D., Frankel, A. D., Harmsen, S. C., Mueller, C. S., Haller, K. M., Wheeler, R. L., Wesson, R. L., Zeng, Y., Boyd, O. S., Perkins, D. M., Luco, N., Field, E. H., Wills, C. J., and Rukstales, K. S. 2008. Documentation for the 2008 Update of the United States National Seismic Hazard Maps. Open-File Report 2008–1128. US Geological Survey.CrossRefGoogle Scholar
Petersen, M. D., Moschetti, M. P., Powers, P. M., Mueller, C. S., Haller, K. M., Frankel, A. D., Zeng, Y., Rezaeian, S., Harmsen, S. C., Boyd, O. S., Field, E. H., Chen, R., Rukstales, K. S., Luco, N., Wheeler, R. L., Williams, R. A., and Olsen, A. H. 2014. Documentation for the 2014 Update of the United States National Seismic Hazard Maps. Open-File Report 2014–1091. US Geological Survey.CrossRefGoogle Scholar
Petersen, M. D., Mueller, C. S., Moschetti, M. P., Hoover, S. M., Shumway, A. M., McNamara, D. E., Williams, R. A., Llenos, A. L., Ellsworth, W. L., Michael, A. J., Rubinstein, J. L., McGarr, A. F., and Rukstales, K. S. 2017. 2017 One-Year Seismic-Hazard Forecast for the Central and Eastern United States from Induced and Natural Earthquakes. Seismological Research Letters, 88 (3), 772783.CrossRefGoogle Scholar
Peterson, J. R., and Hutt, C. R. 2014. World-Wide Standardized Seismograph Network: A Data Users Guide. Open File Report 2014-1218. United States Geological Survey.Google Scholar
Porter, K. 2020. A Beginner’s Guide to Fragility, Vulnerability, and Risk. University of Colorado Boulder.Google Scholar
Porter, K., Jones, L., Cox, D., Goltz, J., Hudnut, K., Mileti, D., Perry, S., Ponti, D., Reichle, M., Rose, A. Z., Scawthorn, C. R., Seligson, H. A., Shoaf, K. I., Treiman, J., and Wein, A. 2011. The ShakeOut Scenario: A Hypothetical Mw7.8 Earthquake on the Southern San Andreas Fault. Earthquake Spectra, 27 (2), 239261.CrossRefGoogle Scholar
Porter, K., Kennedy, R., and Bachman, R. 2007. Creating Fragility Functions for Performance-Based Earthquake Engineering. Earthquake Spectra, 23 (2), 471489.CrossRefGoogle Scholar
Porter, K. A., Kiremidjian, A., and LeGrue, J. 2001. Assembly-Based Vulnerability of Buildings and Its Use in Performance Evaluation. Earthquake Spectra, 17 (2), 291313.CrossRefGoogle Scholar
Powers, P. M., and Field, E. H. 2013. Appendix O: Gridded Seismicity Sources. Open File Report 2013-1165. United States Geological Survey.Google Scholar
Prevost, J. 1978. Plasticity Theory for Soil Stress–Strain Behaviour. Journal of Engineering Mechanics (ASCE), 104 (5), 11771194.Google Scholar
Proakis, J., and Manolakis, D. 1996. Digital Signal Processing: Principles, Algorithms, and Applications, 3rd ed. Prentice-Hall.Google Scholar
Qi, H., and Sun, D. 2006. A Quadratically Convergent Newton Method for Computing the Nearest Correlation Matrix. SIAM Journal on Matrix Analysis and Applications, 28 (2), 360385.CrossRefGoogle Scholar
Ramírez-Guzmaán, L., Boyd, O. S., Hartzell, S., and Williams, R. A. 2012. Seismic Velocity Model of the Central United States (Version 1): Description and Simulation of the 18 April 2008 Mt. Carmel, Illinois, Earthquake. Bulletin of the Seismological Society of America, 102 (6), 26222645.CrossRefGoogle Scholar
Raoof, M., Herrmann, R. B., and Malagnini, L. 1999. Attenuation and Excitation of Three-Component Ground Motion in Southern California. Bulletin of the Seismological Society of America, 89 (4), 888902.CrossRefGoogle Scholar
Reasenberg, P. 1985. Second-Order Moment of Central California Seismicity, 1969–1982. Journal of Geophysical Research: Solid Earth, 90 (B7), 54795495.CrossRefGoogle Scholar
Reasenberg, P. A., and Jones, L. M. 1989. Earthquake Hazard after a Mainshock in California. Science, 243 (4895), 11731176.CrossRefGoogle ScholarPubMed
Reasenberg, P. A., and Jones, L. M. 1990. California Aftershock Hazard Forecasts. Science, 247 (4940), 345346.CrossRefGoogle ScholarPubMed
Reasenberg, P. A., and Jones, L. M. 1994. Earthquake Aftershocks: Update. Science, 265 (5176), 12511252.CrossRefGoogle ScholarPubMed
Reiter, L. 1990. Earthquake Hazard Analysis: Issues and Insights. New York: Columbia University Press.Google Scholar
Restrepo, D., Bielak, J., Serrano, R., Goómez, J., and Jaramillo, J. 2016. Effects of Realistic Topography on the Ground Motion of the Colombian Andes: A Case Study at the Aburrá Valley, Antioquia. Geophysical Journal International, 204 (3), 18011816.CrossRefGoogle Scholar
Rezaeian, S., and Der Kiureghian, A. 2008. A Stochastic Ground Motion Model with Separable Temporal and Spectral Nonstationarities. Earthquake Engineering & Structural Dynamics, 37 (13), 15651584.CrossRefGoogle Scholar
Rezaeian, S., and Der Kiureghian, A. 2011. Simulation of Orthogonal Horizontal Ground Motion Components for Specified Earthquake and Site Characteristics. Earthquake Engineering & Structural Dynamics, 41 (2), 335353.CrossRefGoogle Scholar
Rezaeian, S., Petersen, M. D., Moschetti, M. P., Powers, P., Harmsen, S. C., and Frankel, A. D. 2014. Implementation of NGA-West2 Ground Motion Models in the 2014 U.S. National Seismic Hazard Maps. Earthquake Spectra, 30 (3), 13191333.CrossRefGoogle Scholar
Rhoades, D. 1997. Estimation of Attenuation Relations for Strong-Motion Data Allowing for Individual Earthquake Magnitude Uncertainties. Bulletin of the Seismological Society of America, 87 (6), 16741678.CrossRefGoogle Scholar
Rhoades, D., Liukis, M., Christophersen, A., and Gerstenberger, M. 2016. Retrospective Tests of Hybrid Operational Earthquake Forecasting Models for Canterbury. Geophysical Journal International, 204 (1), 440456.CrossRefGoogle Scholar