TY - JOUR A1 - Derras, Boumediene A1 - Bard, Pierre-Yves A1 - Cotton, Fabrice Pierre T1 - V-S30, slope, H-800 and f(0): performance of various site-condition proxies in reducing ground-motion aleatory variability and predicting nonlinear site response JF - Earth, planets and space N2 - The aim of this paper is to investigate the ability of various site-condition proxies (SCPs) to reduce ground-motion aleatory variability and evaluate how SCPs capture nonlinearity site effects. The SCPs used here are time-averaged shear-wave velocity in the top 30 m (V-S30), the topographical slope (slope), the fundamental resonance frequency (f(0)) and the depth beyond which V-s exceeds 800 m/s (H800). We considered first the performance of each SCP taken alone and then the combined performance of the 6 SCP pairs [V-S30-f(0)], [V-S30-H-800], [f(0)-slope], [H-800-slope], [V-S30-slope] and [f(0)-H-800]. This analysis is performed using a neural network approach including a random effect applied on a KiK-net subset for derivation of ground-motion prediction equations setting the relationship between various ground-motion parameters such as peak ground acceleration, peak ground velocity and pseudo-spectral acceleration PSA (T), and Mw, RJB, focal depth and SCPs. While the choice of SCP is found to have almost no impact on the median groundmotion prediction, it does impact the level of aleatory uncertainty. VS30 is found to perform the best of single proxies at short periods (T < 0.6 s), while f(0) and H-800 perform better at longer periods; considering SCP pairs leads to significant improvements, with particular emphasis on [V-S30-H-800] and [f(0)-slope] pairs. The results also indicate significant nonlinearity on the site terms for soft sites and that the most relevant loading parameter for characterising nonlinear site response is the "stiff" spectral ordinate at the considered period. KW - Aleatory variability KW - Site-condition proxies KW - KiK-net KW - Neural networks KW - GMPE KW - Nonlinear site response Y1 - 2017 U6 - https://doi.org/10.1186/s40623-017-0718-z SN - 1880-5981 VL - 69 SP - 1623 EP - 1629 PB - Springer CY - Heidelberg ER - TY - GEN A1 - Derras, Boumédiène A1 - Bard, Pierre-Yves A1 - Cotton, Fabrice Pierre T1 - VS30, slope, H800 and f0 BT - performance of various site-condition proxies in reducing ground-motion aleatory variability and predicting nonlinear site response T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - The aim of this paper is to investigate the ability of various site-condition proxies (SCPs) to reduce ground-motion aleatory variability and evaluate how SCPs capture nonlinearity site effects. The SCPs used here are time-averaged shear-wave velocity in the top 30 m (VS30), the topographical slope (slope), the fundamental resonance frequency (f0) and the depth beyond which Vs exceeds 800 m/s (H800). We considered first the performance of each SCP taken alone and then the combined performance of the 6 SCP pairs [VS30–f0], [VS30–H800], [f0–slope], [H800–slope], [VS30–slope] and [f0–H800]. This analysis is performed using a neural network approach including a random effect applied on a KiK-net subset for derivation of ground-motion prediction equations setting the relationship between various ground-motion parameters such as peak ground acceleration, peak ground velocity and pseudo-spectral acceleration PSA (T), and Mw, RJB, focal depth and SCPs. While the choice of SCP is found to have almost no impact on the median groundmotion prediction, it does impact the level of aleatory uncertainty. VS30 is found to perform the best of single proxies at short periods (T < 0.6 s), while f0 and H800 perform better at longer periods; considering SCP pairs leads to significant improvements, with particular emphasis on [VS30–H800] and [f0–slope] pairs. The results also indicate significant nonlinearity on the site terms for soft sites and that the most relevant loading parameter for characterising nonlinear site response is the “stiff” spectral ordinate at the considered period. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 817 KW - aleatory variability KW - site-condition proxies KW - KiK-net KW - neural networks KW - GMPE KW - nonlinear site response Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427071 SN - 1866-8372 IS - 817 ER - TY - JOUR A1 - Douglas, John A1 - Akkar, Sinan A1 - Ameri, Gabriele A1 - Bard, Pierre-Yves A1 - Bindi, Dino A1 - Bommer, Julian J. A1 - Bora, Sanjay Singh A1 - Cotton, Fabrice Pierre A1 - Derras, Boumediene A1 - Hermkes, Marcel A1 - Kuehn, Nicolas Martin A1 - Luzi, Lucia A1 - Massa, Marco A1 - Pacor, Francesca A1 - Riggelsen, Carsten A1 - Sandikkaya, M. Abdullah A1 - Scherbaum, Frank A1 - Stafford, Peter J. A1 - Traversa, Paola T1 - 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 JF - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering N2 - 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. KW - Strong-motion data KW - Ground-motion models KW - Ground-motion prediction equations KW - Style of faulting KW - Site amplification KW - Aleatory variability KW - Epistemic uncertainty KW - Europe KW - Middle East Y1 - 2014 U6 - https://doi.org/10.1007/s10518-013-9522-8 SN - 1570-761X SN - 1573-1456 VL - 12 IS - 1 SP - 341 EP - 358 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Derras, Boumediene A1 - Bard, Pierre-Yves A1 - Cotton, Fabrice Pierre T1 - Site-Condition Proxies, Ground Motion Variability, and Data-Driven GMPEs: Insights from the NGA-West2 and RESORCE Data Sets JF - Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute N2 - We compare the ability of various site-condition proxies (SCPs) to reduce the aleatory variability of ground motion prediction equations (GMPEs). Three SCPs (measured V-S30, inferred V-S30, local topographic slope) and two accelerometric databases (RESORCE and NGA-West2) are considered. An artificial neural network (ANN) approach including a random-effect procedure is used to derive GMPEs setting the relationship between peak ground acceleration (PGA), peak ground velocity (PGV), pseudo-spectral acceleration [PSA(T)], and explanatory variables (M-w, R-JB, and V-S30 or Slope). The analysis is performed using both discrete site classes and continuous proxy values. All "non-measured" SCPs exhibit a rather poor performance in reducing aleatory variability, compared to the better performance of measured V-S30. A new, fully data-driven GMPE based on the NGA-West2 is then derived, with an aleatory variability value depending on the quality of the SCP. It proves very consistent with previous GMPEs built on the same data set. Measuring V-S30 allows for benefit from an aleatory variability reduction up to 15%. Y1 - 2016 U6 - https://doi.org/10.1193/060215EQS082M SN - 8755-2930 SN - 1944-8201 VL - 32 SP - 2027 EP - 2056 PB - Earthquake Engineering Research Institute CY - Oakland ER -