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Session: Aeroelastic design 1
Session starts: Tuesday 18 June, 16:00
Presentation starts: 16:00
Room: Room 1.2

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Carlo Aquilini (Airbus Defence and Space GmbH)
Gabriele Grasso (Airbus Defence and Space GmbH)
Cyrille Vidy (Airbus Defence and Space GmbH)

Abstract:
Multivariate random loads may arise from either a stationary Gaussian process, like stochastic or continuous gust, or from a random process, such as buffet. Buffet phenomena are important when the separated air flow induces strong fluctuating pressures on aircraft components. These loads need careful assessment during aircraft design, especially for fighters flying at high angles of attack and in the transonic regime, as well as for general aviation and transport aircraft. This paper introduces an exact method for Aeroelastic design, specifically focusing on determining distributions of deterministic quasi-static nodal loads from integrated load cases obtained from the stochastic problem. Quasi-static load distributions are required by the stress office in order to size the affected structural components. The methodology outlined in this paper builds on the work by Aquilini & Parisse [1], which provides a comprehensive method for predicting n-dimensional combined loads in the presence of massively separated flows. The methodology in [1] obtains a finite number of design load cases, by discretizing the n-dimensional design ellipsoid of equal probability with a semiregular polyhedron, a transformed small rhombicuboctahedron. The present paper extends and concludes the work in [1] by determining distributions of deterministic nodal loads for each selected load case. The exactness of this method allows it to be applied to any load case that satisfies the equation of the multidimensional design load envelope. Thus, the load case selection is not confined to the vertices of the small rhombicuboctahedron but can utilize any discretisation of the ellipsoid. Moreover, this approach is versatile applicable not only to buffeting but also to various stochastic problems, like continuous turbulence. To manage load case complexity, a reduction strategy is suggested, contributing to obtaining a reasonable and meaningful number of design load cases. The paper concludes with examples showcasing the successful application of this method in real-world scenarios and its impact on the traditional Aeroelastic design. [1] Aquilini, C. and Parisse, D. (2017). A Method for Predicting Multivariate Random Loads and a Discrete Approximation of the Multidimensional Design Load Envelope. IFASD 2017