@article{DerrasBardCotton2017,
  author    = {Derras, Boumediene and Bard, Pierre-Yves and Cotton, Fabrice Pierre},
  title     = {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},
  series = {Earth, planets and space},
  volume    = {69},
  journal   = {Earth, planets and space},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {1880-5981},
  doi       = {10.1186/s40623-017-0718-z},
  pages     = {1623 -- 1629},
  year      = {2017},
  abstract  = {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.},
  language  = {en}
}
@misc{DerrasBardCotton2017,
  author    = {Derras, Boum{\´e}di{\`e}ne and Bard, Pierre-Yves and Cotton, Fabrice Pierre},
  title     = {VS30, slope, H800 and f0},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {817},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42707},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427071},
  pages     = {23},
  year      = {2017},
  abstract  = {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.},
  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 Pierre 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{DerrasBardCotton2016,
  author    = {Derras, Boumediene and Bard, Pierre-Yves and Cotton, Fabrice Pierre},
  title     = {Site-Condition Proxies, Ground Motion Variability, and Data-Driven GMPEs: Insights from the NGA-West2 and RESORCE Data Sets},
  series = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute},
  volume    = {32},
  journal   = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute},
  publisher = {Earthquake Engineering Research Institute},
  address   = {Oakland},
  issn      = {8755-2930},
  doi       = {10.1193/060215EQS082M},
  pages     = {2027 -- 2056},
  year      = {2016},
  abstract  = {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\%.},
  language  = {en}
}