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Statistical data for system-based reliability analysis of stainless steel structures with hollow sections
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- Arrayago Luquin, Itsaso|||0000-0002-0054-9322
- Rasmussen, Kim J.R.
- Real Saladrigas, Esther|||0000-0003-1723-3380
Current codes for steel structures, including AISC 360-10, AS4100 and Eurocode 3, are in the process of evolving from the current member-based design method to direct system-based approaches that allow evaluating the strength of structures directly from numerical simulations. However, these codes do not provide adequate safety factors nor reliability requirements for structural systems. Thus, it is necessary to build a rigorous structural reliability framework to investigate acceptable target reliability indices for structural systems and to provide adequate system safety factors. While this framework has been developed based on advanced Finite Element analysis for carbon steel structures in recent years in the form of the Direct Design Method (DDM), it does not exist for stainless steel structures. This paper presents the first step towards developing a system-based reliability framework for stainless steel structures by providing statistical distributions of the key parameters governing the strength of systems composed of stainless steel cold-formed hollow sections. The distributions are based on a comprehensive database collected from the literature including data on the main sources of uncertainty: geometric properties, imperfections and material parameters., The project leading to this research has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement No. 842395.
DOI: http://hdl.handle.net/2117/351930, https://dx.doi.org/10.1002/cepa.1457
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HANDLE: http://hdl.handle.net/2117/351930, https://dx.doi.org/10.1002/cepa.1457
UPCommons. Portal del coneixement obert de la UPC
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Ver en: http://hdl.handle.net/2117/351930, https://dx.doi.org/10.1002/cepa.1457
UPCommons. Portal del coneixement obert de la UPC
oai:upcommons.upc.edu:2117/351930
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