Characterization of nonlinear slosh loads in aircraft remains a challenging problem. This work benchmarks a frozen fuel mass model against computational fluid dynamics data across a complete flight envelope. Thereafter, a novel surrogate reduced-order model aimed at improving on frozen fuel mass predictions is proposed. For a given tank geometry, the surrogate reduced-order model employs computational fluid dynamics simulations from which limit state slosh loads may be computed. These are calculated as a function of the mode of excitation (vertical or lateral), fill level, excitation frequency, and excitation amplitude. The resulting response surface is then described via a kriging interpolation-based surrogate reduced-order model. The surrogate is combined with a novel metric for the amplification factor (the ratio of the actual load to that induced by a frozen fuel mass) to predict the transient slosh-induced force due to arbitrary gust-type excitations. The latter is characterized as a priori in terms of acceleration amplitude and frequency via Fourier decomposition. It is demonstrated that the proposed surrogate reduced-order model improves the accuracy in predicting lateral slosh-induced loads by an average of 150% as compared to a frozen fuel mass model for a range of excitations, while being conservative.


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    Titel :

    Novel Nonlinear Fuel Slosh Surrogate Reduced-Order Model for Aircraft Loads Prediction


    Beteiligte:

    Erschienen in:

    Journal of Aircraft ; 55 , 3 ; 1004-1013


    Erscheinungsdatum :

    2017-10-19


    Format / Umfang :

    10 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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