8-MW wind turbine tower computational shell buckling benchmark. Part 1: An international ‘round-robin’ exercise

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Sadowski, A.J.; Seidel, M.; Al-Lawati, H.; Azizi, E.; Balscheit, H. et al.: 8-MW wind turbine tower computational shell buckling benchmark. Part 1: An international ‘round-robin’ exercise. In: Engineering Failure Analysis 148 (2023), 107124. DOI: https://doi.org/10.1016/j.engfailanal.2023.107124

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Abstract: 
An assessment of the elastic-plastic buckling limit state for multi-strake wind turbine support towers poses a particular challenge for the modern finite element analyst, who must competently navigate numerous modelling choices related to the tug-of-war between meshing and computational cost, the use of solvers that are robust to highly nonlinear behaviour, the potential for multiple near-simultaneously critical failure locations, the complex issue of imperfection sensitivity and finally the interpretation of the data into a safe and economic design. This paper reports on an international ‘round-robin’ exercise conducted in 2022 aiming to take stock of the computational shell buckling expertise around the world which attracted 29 submissions. Participants were asked to perform analyses of increasing complexity on a standardised benchmark of an 8-MW multi-strake steel wind turbine support tower segment, from a linear elastic stress analysis to a linear bifurcation analysis to a geometrically and materially nonlinear buckling analysis with imperfections. The results are a showcase of the significant shell buckling expertise now available in both industry and academia. This paper is the first of a pair. The second paper presents a detailed reference solution to the benchmark, including an illustration of the Eurocode-compliant calibration of two important imperfection forms.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2023
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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1 image of flag of United States United States 7 41.18%
2 image of flag of Germany Germany 5 29.41%
3 image of flag of No geo information available No geo information available 2 11.76%
4 image of flag of Netherlands Netherlands 1 5.88%
5 image of flag of Indonesia Indonesia 1 5.88%
6 image of flag of China China 1 5.88%

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