On the nonstationary identification of climate-influenced loads for the semi-probabilistic approach using measured and projected data
- 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. involvingA 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.…
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Gefördert durch das Programm Open Access Publizieren der DFG und den Publikationsfonds der Bauhaus-Universität Weimar.
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| Document Type: | Article |
|---|---|
| Author: | M. Sc. Robert ArnoldORCiD, Prof. Dr.-Ing Matthias KrausORCiDGND |
| DOI (Cite-Link): | https://doi.org/10.1080/23311916.2022.2143061Cite-Link |
| URN (Cite-Link): | https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20221117-47363Cite-Link |
| URL: | https://doi.org/10.1080/23311916.2022.2143061 |
| Parent Title (English): | Cogent Engineering |
| Publisher: | Taylor & Francis |
| Place of publication: | London |
| Editor: | Duc Pham |
| Language: | English |
| Date of Publication (online): | 2022/11/09 |
| Date of first Publication: | 2022/11/09 |
| Release Date: | 2022/11/17 |
| Publishing Institution: | Bauhaus-Universität Weimar |
| Institutes and partner institutions: | Fakultät Bauingenieurwesen / Professur Stahl- und Hybridbau |
| Volume: | 2022 |
| Issue: | Volume 9, issue 1, article 2143061 |
| Pagenumber: | 26 |
| First Page: | 1 |
| Last Page: | 26 |
| Tag: | OA-Publikationsfonds2022 Extreme value distribution; First Order Reliability Method; climate loads; nonstationarity; semi-probabilistic concept |
| GND Keyword: | Reliabilität |
| Dewey Decimal Classification: | 600 Technik, Medizin, angewandte Wissenschaften |
| BKL-Classification: | 56 Bauwesen |
| Open Access Publikationsfonds: | Open-Access-Publikationsfonds 2022 |
| Licence (German): |  Creative Commons 4.0 - Namensnennung-Nicht kommerziell-Keine Bearbeitung (CC BY-NC-ND 4.0) |