A semi-analytical formulation for accounting uncertainties of hazard parameters in structural seismic reliability analysis

Abstract The probabilistic seismic hazard analysis (PSHA), is currently one of the most used approaches worldwide for assessing seismic hazard, and represents the mostly used approach adopted for the development of seismic maps. PSHA relies on strong mathematical bases, and it is a correct application of the Total Probability Theorem; it is thus able to combine three main sources of uncertainty, e.g. the earthquake magnitude, the source-to-site distance and the corresponding ground-shaking scenario. As a consequence, because of its intrinsic nature, also model parameters can be sources of variability, since most of the time they are extrapolated from historical data. Thus, this work wants to give a contribution on the debated problem of uncertainty in seismic hazard estimates, by proposing a semi-analytical formulation able to include uncertainties arising from model parameters, treating them, in turn, as random variables. The proposed formulation adopts the reliability index and its standard deviation for computing hazard curves characterized by an assumed probability to be underestimated. In the second part of the work, the formulation is applied to a case study represented by an existing bridge, showing its practical use and investigating how different levels of knowledge of seismic hazard model input parameters, can impact the outcomes of a classical structural seismic reliability or risk analysis carried out without taking into account such specific issue.

[1]  B. E. Shaw,et al.  Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3)—The Time‐Independent Model , 2014 .

[2]  C. Allin Cornell,et al.  The Case for Using Mean Seismic Hazard , 2005 .

[3]  Julian J. Bommer,et al.  The Use and Misuse of Logic Trees in Probabilistic Seismic Hazard Analysis , 2008 .

[4]  Julian J. Bommer,et al.  Sensitivity of PSHA results to ground motion prediction relations and logic-tree weights , 2005 .

[5]  C. Allin Cornell,et al.  Probabilistic Basis for 2000 SAC Federal Emergency Management Agency Steel Moment Frame Guidelines , 2002 .

[6]  Julian J. Bommer,et al.  Probability and Uncertainty in Seismic Hazard Analysis , 2005 .

[7]  Roger M.W. Musson.  On the Nature of Logic Trees in Probabilistic Seismic Hazard Assessment , 2012 .

[8]  Massimiliano Stucchi,et al.  A seismic source zone model for the seismic hazard assessment of the Italian territory , 2008 .

[9]  Warner Marzocchi,et al.  Accounting for Epistemic Uncertainty in PSHA: Logic Tree and Ensemble Modeling , 2014 .

[10]  Julian J. Bommer,et al.  Sigma: Issues, Insights, and Challenges , 2009 .

[11]  C. Cornell.  Engineering seismic risk analysis , 1968 .

[12]  P. Bazzurro,et al.  Disaggregation of Probabilistic Ground-Motion Hazard in Italy , 2009 .

[13]  H. Crowley,et al.  Seismic Hazard Assessment (2003–2009) for the Italian Building Code , 2011 .

[14]  R. Park,et al.  Flexural Members with Confined Concrete , 1971 .

[15]  Robin K. McGuire,et al.  Effects of uncertainty in seismicity on estimates of seismic hazard for the east coast of the United States , 1977 .

[16]  R. Mcguire,et al.  Statistical uncertainties in seismic hazard evaluations in the United States , 1981 .

[17]  R. M. W. Musson.  Against Fractiles , 2005 .

[18]  Iunio Iervolino,et al.  Sequence‐Based Probabilistic Seismic Hazard Analysis , 2014 .

[19]  Reginald DesRoches,et al.  Seismic fragility of typical bridges in moderate seismic zones , 2004 .

[20]  Julian J. Bommer,et al.  Challenges of Building Logic Trees for Probabilistic Seismic Hazard Analysis , 2012 .

[21]  Julian J. Bommer,et al.  Why Do Modern Probabilistic Seismic-Hazard Analyses Often Lead to Increased Hazard Estimates? , 2006 .

[22]  Thomas H. Jordan,et al.  A Unified Probabilistic Framework for Seismic Hazard Analysis , 2017 .

[23]  D. Bindi,et al.  Ground motion prediction equations derived from the Italian strong motion database , 2011 .

[24]  Armen Der Kiureghian,et al.  MEASURES OF STRUCTURAL SAFETY UNDER IMPERFECT STATES OF KNOWLEDGE , 1989 .

[25]  Iunio Iervolino,et al.  Aftershocks’ Effect on Structural Design Actions in Italy , 2018, Bulletin of the Seismological Society of America.

[26]  Armen Der Kiureghian,et al.  Probabilistic Capacity Models and Fragility Estimates for Reinforced Concrete Columns based on Experimental Observations , 2002 .