@article{BindiKothaWeatherilletal.2018, author = {Bindi, Dino and Kotha, Sreeram Reddy and Weatherill, Graeme and Lanzano, Giovanni and Luzi, Lucia and Cotton, Fabrice}, title = {The pan-European engineering strong motion (ESM) flatfile}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {17}, journal = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, number = {2}, publisher = {Springer}, address = {Dordrecht}, issn = {1570-761X}, doi = {10.1007/s10518-018-0466-x}, pages = {583 -- 602}, year = {2018}, abstract = {We present the results of a consistency check performed over the flatfile extracted from the engineering strong motion (ESM) database. The flatfile includes 23,014 recordings from 2179 earthquakes in the magnitude range from 3.5 to 7.8 that occurred since the 1970s in Europe and Middle East, as presented in the companion article by Lanzano et al. (Bull Earthq Eng, 2018a). The consistency check is developed by analyzing different residual distributions obtained from ad-hoc ground motion prediction equations for the absolute spectral acceleration (SA), displacement and Fourier amplitude spectra (FAS). Only recordings from earthquakes shallower than 40 km are considered in the analysis. The between-event, between-station and event-and-station corrected residuals are computed by applying a mixed-effect regression. We identified those earthquakes, stations, and recordings showing the largest deviations from the GMPE median predictions, and also evaluated the statistical uncertainty on the median model to get insights on the applicable magnitude-distance ranges and the usable period (or frequency) range. We observed that robust median predictions are obtained up to 8 s for SA and up to 20 Hz for FAS, although median predictions for Mw ≥ 7 show significantly larger uncertainties with 'bumps' starting above 5 s for SA and below 0.3 Hz for FAS. The between-station variance dominates over the other residual variances, and the dependence of the between-station residuals on logarithm of Vs30 is well-described by a piece-wise linear function with period-dependent slopes and hinge velocity around 580 m/s. Finally, we compared the between-event residuals obtained by considering two different sources of moment magnitude. The results show that, at long periods, the between-event terms from the two regressions have a weak correlation and the overall between-event variability is dissimilar, highlighting the importance of magnitude source in the regression results.}, language = {en} } @article{KothaBazzurroPagani2018, author = {Kotha, Sreeram Reddy and Bazzurro, Paolo and Pagani, Marco}, title = {Effects of epistemic uncertainty in seismic hazard estimates on building portfolio losses}, series = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute}, volume = {34}, journal = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute}, number = {1}, publisher = {Earthquake Engineering Research Institute}, address = {Oakland}, issn = {8755-2930}, doi = {10.1193/020515EQS020M}, pages = {217 -- 236}, year = {2018}, abstract = {In catastrophe risk modeling, a defensible estimation of impact severity and its likelihood of occurrence to a portfolio of assets can only be made through a rigorous treatment of uncertainty and the consideration of multiple alternative models. This approach, however, requires repeating lengthy calculations multiple times. To limit the demand on computational time and resources, a frequent practice in the industry is to estimate the distribution of earthquake-induced portfolio losses using a simulated catalog of events from a single representative mean ground motion hazard model for the region. This simplified approach is faster but may provide biased estimates of the likelihood of occurrence of the large and infrequent losses that drive many risk mitigation decisions. Investigation through case studies of different portfolios of assets located in the San Francisco Bay Region shows the potential for both a bias in the mean loss estimates and an underestimation of their central 70\% interpercentile. We propose a simplified and computationally practical approach that reduces the bias in the mean portfolio loss estimates. This approach does not improve the estimate of the interpercentile range, however, a quantity of no direct practical use.}, language = {en} } @article{KothaCottonBindi2018, author = {Kotha, Sreeram Reddy and Cotton, Fabrice and Bindi, Dino}, title = {A new approach to site classification}, series = {Soil Dynamics and Earthquake Engineering}, volume = {110}, journal = {Soil Dynamics and Earthquake Engineering}, publisher = {Elsevier}, address = {Oxford}, issn = {0267-7261}, doi = {10.1016/j.soildyn.2018.01.051}, pages = {318 -- 329}, year = {2018}, abstract = {With increasing amount of strong motion data, Ground Motion Prediction Equation (GMPE) developers are able to quantify empirical site amplification functions (delta S2S(s)) from GMPE residuals, for use in site-specific Probabilistic Seismic Hazard Assessment. In this study, we first derive a GMPE for 5\% damped Pseudo Spectral Acceleration (g) of Active Shallow Crustal earthquakes in Japan with 3.4 <= M-w <= 7.3 and 0 <= R-JB <= 600km. Using k-mean spectral clustering technique, we then classify our estimated delta S2S(s)(T = 0.01 - 2s) of 588 wellcharacterized sites, into 8 site clusters with distinct mean site amplification functions, and within-cluster site-tosite variability similar to 50\% smaller than the overall dataset variability (phi(S2S)). Following an evaluation of existing schemes, we propose a revised data-driven site classification characterized by kernel density distributions of V-s30, V-s10, H-800, and predominant period (T-G) of the site clusters.}, language = {en} }