@article{DelavaudScherbaumKuehnetal.2009, author = {Delavaud, Elise and Scherbaum, Frank and Kuehn, Nicolas and Riggelsen, Carsten}, title = {Information-theoretic selection of ground-motion prediction equations for seismic hazard analysis : an applicability study using Californian data}, issn = {0037-1106}, doi = {10.1785/0120090055}, year = {2009}, abstract = {Considering the increasing number and complexity of ground-motion prediction equations available for seismic hazard assessment, there is a definite need for an efficient, quantitative, and robust method to select and rank these models for a particular region of interest. In a recent article, Scherbaum et al. (2009) have suggested an information- theoretic approach for this purpose that overcomes several shortcomings of earlier attempts at using data-driven ground- motion prediction equation selection procedures. The results of their theoretical study provides evidence that in addition to observed response spectra, macroseismic intensity data might be useful for model selection and ranking. We present here an applicability study for this approach using response spectra and macroseismic intensities from eight Californian earthquakes. A total of 17 ground-motion prediction equations, from different regions, for response spectra, combined with the equation of Atkinson and Kaka (2007) for macroseismic intensities are tested for their relative performance. The resulting data-driven rankings show that the models that best estimate ground motion in California are, as one would expect, Californian and western U. S. models, while some European models also perform fairly well. Moreover, the model performance appears to be strongly dependent on both distance and frequency. The relative information of intensity versus response spectral data is also explored. The strong correlation we obtain between intensity-based rankings and spectral-based ones demonstrates the great potential of macroseismic intensities data for model selection in the context of seismic hazard assessment.}, language = {en} } @article{GianniotisKuehnScherbaum2014, author = {Gianniotis, Nikolaos and Kuehn, Nicolas and Scherbaum, Frank}, title = {Manifold aligned ground motion prediction equations for regional datasets}, series = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology}, volume = {69}, journal = {Computers \& geosciences : an international journal devoted to the publication of papers on all aspects of geocomputation and to the distribution of computer programs and test data sets ; an official journal of the International Association for Mathematical Geology}, publisher = {Elsevier}, address = {Oxford}, issn = {0098-3004}, doi = {10.1016/j.cageo.2014.04.014}, pages = {72 -- 77}, year = {2014}, abstract = {Inferring a ground-motion prediction equation (GMPE) for a region in which only a small number of seismic events has been observed is a challenging task. A response to this data scarcity is to utilise data from other regions in the hope that there exist common patterns in the generation of ground motion that can contribute to the development of a GMPE for the region in question. This is not an unreasonable course of action since we expect regional GMPEs to be related to each other. In this work we model this relatedness by assuming that the regional GMPEs occupy a common low-dimensional manifold in the space of all possible GMPEs. As a consequence, the GMPEs are fitted in a joint manner and not independent of each other, borrowing predictive strength from each other's regional datasets. Experimentation on a real dataset shows that the manifold assumption displays better predictive performance over fitting regional GMPEs independent of each other. (C) 2014 Elsevier Ltd. All rights reserved.}, language = {en} } @article{KuehnScherbaum2016, author = {Kuehn, Nicolas M. and Scherbaum, Frank}, title = {A partially non-ergodic ground-motion prediction equation for Europe and the Middle East}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {14}, journal = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, publisher = {Springer}, address = {Dordrecht}, issn = {1570-761X}, doi = {10.1007/s10518-016-9911-x}, pages = {2629 -- 2642}, year = {2016}, abstract = {A partially non-ergodic ground-motion prediction equation is estimated for Europe and the Middle East. Therefore, a hierarchical model is presented that accounts for regional differences. For this purpose, the scaling of ground-motion intensity measures is assumed to be similar, but not identical in different regions. This is achieved by assuming a hierarchical model, where some coefficients are treated as random variables which are sampled from an underlying global distribution. The coefficients are estimated by Bayesian inference. This allows one to estimate the epistemic uncertainty in the coefficients, and consequently in model predictions, in a rigorous way. The model is estimated based on peak ground acceleration data from nine different European/Middle Eastern regions. There are large differences in the amount of earthquakes and records in the different regions. However, due to the hierarchical nature of the model, regions with only few data points borrow strength from other regions with more data. This makes it possible to estimate a separate set of coefficients for all regions. Different regionalized models are compared, for which different coefficients are assumed to be regionally dependent. Results show that regionalizing the coefficients for magnitude and distance scaling leads to better performance of the models. The models for all regions are physically sound, even if only very few earthquakes comprise one region.}, language = {en} } @article{BoraScherbaumKuehnetal.2016, author = {Bora, Sanjay Singh and Scherbaum, Frank and Kuehn, Nicolas and Stafford, Peter}, title = {On the Relationship between Fourier and Response Spectra: Implications for the Adjustment of Empirical Ground-Motion Prediction Equations (GMPEs)}, series = {Bulletin of the Seismological Society of America}, volume = {106}, journal = {Bulletin of the Seismological Society of America}, publisher = {Seismological Society of America}, address = {Albany}, issn = {0037-1106}, doi = {10.1785/0120150129}, pages = {1235 -- 1253}, year = {2016}, abstract = {The functional form of empirical response spectral ground-motion prediction equations (GMPEs) is often derived using concepts borrowed from Fourier spectral modeling of ground motion. As these GMPEs are subsequently calibrated with empirical observations, this may not appear to pose any major problems in the prediction of ground motion for a particular earthquake scenario. However, the assumption that Fourier spectral concepts persist for response spectra can lead to undesirable consequences when it comes to the adjustment of response spectral GMPEs to represent conditions not covered in the original empirical data set. In this context, a couple of important questions arise, for example, what are the distinctions and/or similarities between Fourier and response spectra of ground motions? And, if they are different, then what is the mechanism responsible for such differences and how do adjustments that are made to Fourier amplitude spectrum (FAS) manifest in response spectra? The present article explores the relationship between the Fourier and response spectrum of ground motion by using random vibration theory (RVT). With a simple Brune (1970, 1971) source model, RVT-generated acceleration spectra for a fixed magnitude and distance scenario are used. The RVT analyses reveal that the scaling of low oscillator-frequency response spectral ordinates can be treated as being equivalent to the scaling of the corresponding Fourier spectral ordinates. However, the high oscillator-frequency response spectral ordinates are controlled by a rather wide band of Fourier spectral ordinates. In fact, the peak ground acceleration, counter to the popular perception that it is a reflection of the high-frequency characteristics of ground motion, is controlled by the entire Fourier spectrum of ground motion. Additionally, this article demonstrates how an adjustment made to FAS is similar or different to the same adjustment made to response spectral ordinates. For this purpose, two cases: adjustments to the stress parameter (Delta sigma) (source term), and adjustments to the attributes reflecting site response (V-S - kappa(0)) are considered.}, language = {en} } @article{LandwehrKuehnSchefferetal.2016, author = {Landwehr, Niels and Kuehn, Nicolas M. and Scheffer, Tobias and Abrahamson, Norman A.}, title = {A Nonergodic Ground-Motion Model for California with Spatially Varying Coefficients}, series = {Bulletin of the Seismological Society of America}, volume = {106}, journal = {Bulletin of the Seismological Society of America}, publisher = {Seismological Society of America}, address = {Albany}, issn = {0037-1106}, doi = {10.1785/0120160118}, pages = {2574 -- 2583}, year = {2016}, abstract = {Traditional probabilistic seismic-hazard analysis as well as the estimation of ground-motion models (GMMs) is based on the ergodic assumption, which means that the distribution of ground motions over time at a given site is the same as their spatial distribution over all sites for the same magnitude, distance, and site condition. With a large increase in the number of recorded ground-motion data, there are now repeated observations at given sites and from multiple earthquakes in small regions, so that assumption can be relaxed. We use a novel approach to develop a nonergodic GMM, which is cast as a varying-coefficient model (VCM). In this model, the coefficients are allowed to vary by geographical location, which makes it possible to incorporate effects of spatially varying source, path, and site conditions. Hence, a separate set of coefficients is estimated for each source and site coordinate in the data set. The coefficients are constrained to be similar for spatially nearby locations. This is achieved by placing a Gaussian process prior on the coefficients. The amount of correlation is determined by the data. The spatial correlation structure of the model allows one to extrapolate the varying coefficients to a new location and trace the corresponding uncertainties. The approach is illustrated with the Next Generation Attenuation-West2 data set, using only Californian records. The VCM outperforms a traditionally estimated GMM in terms of generalization error and leads to a reduction in the aleatory standard deviation by similar to 40\%, which has important implications for seismic-hazard calculations. The scaling of the model with respect to its predictor variables such as magnitude and distance is physically plausible. The epistemic uncertainty associated with the predicted ground motions is small in places where events or stations are close and large where data are sparse.}, language = {en} } @article{HaendelvonSpechtKuehnetal.2015, author = {H{\"a}ndel, Annabel and von Specht, Sebastian and Kuehn, Nicolas M. and Scherbaum, Frank}, title = {Mixtures of ground-motion prediction equations as backbone models for a logic tree: an application to the subduction zone in Northern Chile}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {13}, 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/s10518-014-9636-7}, pages = {483 -- 501}, year = {2015}, abstract = {In probabilistic seismic hazard analysis, different ground-motion prediction equations (GMPEs) are commonly combined within a logic tree framework. The selection of appropriate GMPEs, however, is a non-trivial task, especially for regions where strong motion data are sparse and where no indigenous GMPE exists because the set of models needs to capture the whole range of ground-motion uncertainty. In this study we investigate the aggregation of GMPEs into a mixture model with the aim to infer a backbone model that is able to represent the center of the ground-motion distribution in a logic tree analysis. This central model can be scaled up and down to obtain the full range of ground-motion uncertainty. The combination of models into a mixture is inferred from observed ground-motion data. We tested the new approach for Northern Chile, a region for which no indigenous GMPE exists. Mixture models were calculated for interface and intraslab type events individually. For each source type we aggregated eight subduction zone GMPEs using mainly new strong-motion data that were recorded within the Plate Boundary Observatory Chile project and that were processed within this study. We can show that the mixture performs better than any of its component GMPEs, and that it performs comparable to a regression model that was derived for the same dataset. The mixture model seems to represent the median ground motions in that region fairly well. It is thus able to serve as a backbone model for the logic tree.}, language = {en} } @article{DouglasAkkarAmerietal.2014, author = {Douglas, John and Akkar, Sinan and Ameri, Gabriele and Bard, Pierre-Yves and Bindi, Dino and Bommer, Julian J. and Bora, Sanjay Singh and Cotton, Fabrice and Derras, Boumediene and Hermkes, Marcel and Kuehn, Nicolas Martin and Luzi, Lucia and Massa, Marco and Pacor, Francesca and Riggelsen, Carsten and Sandikkaya, M. Abdullah and Scherbaum, Frank and Stafford, Peter J. and Traversa, Paola}, title = {Comparisons among the five ground-motion models developed using RESORCE for the prediction of response spectral accelerations due to earthquakes in Europe and the Middle East}, series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, volume = {12}, journal = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering}, number = {1}, publisher = {Springer}, address = {Dordrecht}, issn = {1570-761X}, doi = {10.1007/s10518-013-9522-8}, pages = {341 -- 358}, year = {2014}, abstract = {This article presents comparisons among the five ground-motion models described in other articles within this special issue, in terms of data selection criteria, characteristics of the models and predicted peak ground and response spectral accelerations. Comparisons are also made with predictions from the Next Generation Attenuation (NGA) models to which the models presented here have similarities (e.g. a common master database has been used) but also differences (e.g. some models in this issue are nonparametric). As a result of the differing data selection criteria and derivation techniques the predicted median ground motions show considerable differences (up to a factor of two for certain scenarios), particularly for magnitudes and distances close to or beyond the range of the available observations. The predicted influence of style-of-faulting shows much variation among models whereas site amplification factors are more similar, with peak amplification at around 1s. These differences are greater than those among predictions from the NGA models. The models for aleatory variability (sigma), however, are similar and suggest that ground-motion variability from this region is slightly higher than that predicted by the NGA models, based primarily on data from California and Taiwan.}, language = {en} } @article{AlAtikAbrahamsonBommeretal.2010, author = {Al Atik, Linda and Abrahamson, Norman A. and Bommer, Julian J. and Scherbaum, Frank and Cotton, Fabrice and Kuehn, Nicolas}, title = {The variability of ground-motion prediction models and its components}, issn = {0895-0695}, doi = {10.1785/gssrl.81.5.794}, year = {2010}, language = {en} } @article{MolkenthinScherbaumGriewanketal.2014, author = {Molkenthin, Christian and Scherbaum, Frank and Griewank, Andreas and Kuehn, Nicolas and Stafford, Peter}, title = {A Study of the sensitivity of response spectral amplitudes on seismological parameters using algorithmic differentiation}, series = {Bulletin of the Seismological Society of America}, volume = {104}, journal = {Bulletin of the Seismological Society of America}, number = {5}, publisher = {Seismological Society of America}, address = {Albany}, issn = {0037-1106}, doi = {10.1785/0120140022}, pages = {2240 -- 2252}, year = {2014}, abstract = {Response spectra are of fundamental importance in earthquake engineering and represent a standard measure in seismic design for the assessment of structural performance. However, unlike Fourier spectral amplitudes, the relationship of response spectral amplitudes to seismological source, path, and site characteristics is not immediately obvious and might even be considered counterintuitive for high oscillator frequencies. The understanding of this relationship is nevertheless important for seismic-hazard analysis. The purpose of the present study is to comprehensively characterize the variation of response spectral amplitudes due to perturbations of the causative seismological parameters. This is done by calculating the absolute parameter sensitivities (sensitivity coefficients) defined as the partial derivatives of the model output with respect to its input parameters. To derive sensitivities, we apply algorithmic differentiation (AD). This powerful approach is extensively used for sensitivity analysis of complex models in meteorology or aerodynamics. To the best of our knowledge, AD has not been explored yet in the seismic-hazard context. Within the present study, AD was successfully implemented for a proven and extensively applied simulation program for response spectra (Stochastic Method SIMulation [SMSIM]) using the TAPENADE AD tool. We assess the effects and importance of input parameter perturbations on the shape of response spectra for different regional stochastic models in a quantitative way. Additionally, we perform sensitivity analysis regarding adjustment issues of groundmotion prediction equations.}, language = {en} }