Enhanced Deterministic Performance of Panels Using Stochastic Variations of Geometric and Material Parameters

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van den Broek, S.; Minera, S.; Pirrera, A.; Weaver, P.M.; Jansen, E.; Rolfes, R.: Enhanced Deterministic Performance of Panels Using Stochastic Variations of Geometric and Material Parameters. In. AIAA Scitech 2019 Forum. Reston, VA : American Institute of Aeronautics and Astronautics, 2019, AIAA 2019-0511. DOI: https://doi.org/10.2514/1.J058962

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Sum total of downloads: 94

The effect of stochastic variation in material and geometric properties on structural performance is important for robust design. Knowledge of such effects can be acquired by applying variation patterns to a structure using random fields through a Monte Carlo analysis. The output is postprocessed to show the correlation pattern between the stochastic variation of a structural property and a chosen mechanical response measure. The resulting patterns are used to identify areas most susceptible to variations, as well as areas which have the most potential to increase structural performance by varying the material parameter or geometry. By using these maps of local sensitivity to variations with respect to the structural response it is possible to redistribute material properties or geometry to promote certain behavior. This is demonstrated on a flat plate and curved panel, by either varying the Young's modulus, or thickness of the structure to increase the linear buckling load. In both of these variations the average property is set to remain the same as the original structure. Applying the redistribution increased the linear buckling load by up to 29%
License of this version: CC BY 3.0 DE
Document Type: BookPart
Publishing status: acceptedVersion
Issue Date: 2020-01-29
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 23 24.47%
2 image of flag of United Kingdom United Kingdom 17 18.09%
3 image of flag of United States United States 13 13.83%
4 image of flag of China China 9 9.57%
5 image of flag of Czech Republic Czech Republic 8 8.51%
6 image of flag of Russian Federation Russian Federation 5 5.32%
7 image of flag of Netherlands Netherlands 4 4.26%
8 image of flag of India India 3 3.19%
9 image of flag of Portugal Portugal 2 2.13%
10 image of flag of Italy Italy 2 2.13%
    other countries 8 8.51%

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