@article{BommerCoppersmithCoppersmithetal.2015,
  author    = {Bommer, Julian J. and Coppersmith, Kevin J. and Coppersmith, Ryan T. and Hanson, Kathryn L. and Mangongolo, Azangi and Neveling, Johann and Rathje, Ellen M. and Rodriguez-Marek, Adrian and Scherbaum, Frank and Shelembe, Refilwe and Stafford, Peter J. and Strasser, Fleur O.},
  title     = {A SSHAC Level 3 Probabilistic Seismic Hazard Analysis for a New-Build Nuclear Site in South Africa},
  series = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute},
  volume    = {31},
  journal   = {Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute},
  number    = {2},
  publisher = {Earthquake Engineering Research Institute},
  address   = {Oakland},
  issn      = {8755-2930},
  doi       = {10.1193/060913EQS145M},
  pages     = {661 -- 698},
  year      = {2015},
  abstract  = {A probabilistic seismic hazard analysis has been conducted for a potential nuclear power plant site on the coast of South Africa, a country of low-to-moderate seismicity. The hazard study was conducted as a SSHAC Level 3 process, the first application of this approach outside North America. Extensive geological investigations identified five fault sources with a non-zero probability of being seismogenic. Five area sources were defined for distributed seismicity, the least active being the host zone for which the low recurrence rates for earthquakes were substantiated through investigations of historical seismicity. Empirical ground-motion prediction equations were adjusted to a horizon within the bedrock at the site using kappa values inferred from weak-motion analyses. These adjusted models were then scaled to create new equations capturing the range of epistemic uncertainty in this region with no strong motion recordings. Surface motions were obtained by convolving the bedrock motions with site amplification functions calculated using measured shear-wave velocity profiles.},
  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{MolkenthinScherbaumGriewanketal.2015,
  author    = {Molkenthin, Christian and Scherbaum, Frank and Griewank, Andreas and K{\"u}hn, Nicolas and Stafford, Peter J. and Leovey, Hernan},
  title     = {Sensitivity of Probabilistic Seismic Hazard Obtained by Algorithmic Differentiation: A Feasibility Study},
  series = {Bulletin of the Seismological Society of America},
  volume    = {105},
  journal   = {Bulletin of the Seismological Society of America},
  number    = {3},
  publisher = {Seismological Society of America},
  address   = {Albany},
  issn      = {0037-1106},
  doi       = {10.1785/0120140294},
  pages     = {1810 -- 1822},
  year      = {2015},
  abstract  = {Probabilistic seismic-hazard analysis (PSHA) is the current tool of the trade used to estimate the future seismic demands at a site of interest. A modern PSHA represents a complex framework that combines different models with numerous inputs. It is important to understand and assess the impact of these inputs on the model output in a quantitative way. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters, and obtaining insight about the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs; however, obtaining the derivatives of complex models can be challenging. In this study, we show how differential sensitivity analysis of a complex framework such as PSHA can be carried out using algorithmic/automatic differentiation (AD). AD has already been successfully applied for sensitivity analyses in various domains such as oceanography and aerodynamics. First, we demonstrate the feasibility of the AD methodology by comparing AD-derived sensitivities with analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. Second, we derive sensitivities via AD for a more complex PSHA study using a stochastic simulation approach for the prediction of ground motions. The presented approach is general enough to accommodate more advanced PSHA studies of greater complexity.},
  language  = {en}
}