@article{ArnoldKraus,
  author    = {Arnold, Robert and Kraus, Matthias},
  title     = {On the nonstationary identification of climate-influenced loads for the semi-probabilistic approach using measured and projected data},
  series = {Cogent Engineering},
  volume    = {2022},
  journal   = {Cogent Engineering},
  number    = {Volume 9, issue 1, article 2143061},
  editor    = {Pham, Duc},
  publisher = {Taylor \& Francis},
  address   = {London},
  doi       = {10.1080/23311916.2022.2143061},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20221117-47363},
  pages     = {1 -- 26},
  abstract  = {A safe and economic structural design based on the semi-probabilistic concept requires statistically representative safety elements, such as characteristic values, design values, and partial safety factors. Regarding climate loads, the safety levels of current design codes strongly reflect experiences based on former measurements and investigations assuming stationary conditions, i.e. involving constant frequencies and intensities. However, due to climate change, occurrence of corresponding extreme weather events is expected to alter in the future influencing the reliability and safety of structures and their components. Based on established approaches, a systematically refined data-driven methodology for the determination of design parameters considering nonstationarity as well as standardized targets of structural reliability or safety, respectively, is therefore proposed. The presented procedure picks up fundamentals of European standardization and extends them with respect to nonstationarity by applying a shifting time window method. Taking projected snow loads into account, the application of the method is exemplarily demonstrated and various influencing parameters are discussed.},
  subject      = {Reliabilit{\"a}t},
  language  = {en}
}