A multidisciplinary optimization (MDO) method has been developed to design a computational fluid dynamics (CFD) based low-boom configuration that can be obtained from a Pareto solution of a low-fidelity multiobjective MDO problem with mission constraints. This paper refines the developed MDO method using multifidelity models for CFD-based multiobjective MDO. The refined MDO method can generate a low-boom configuration that satisfies the mission requirements, has the lowest takeoff gross weight and the longest range for the low-boom mission, trims the low-boom cruise flight with fuel redistributions, and has a reversed equivalent area distribution closely matching a low-boom target with ground noise level below 70 PLdB. The validity of the refined MDO method is demonstrated by a design study of a low-boom supersonic transport that carries 40 passengers, flies a low-boom mission with cruise Mach of 1.7 and range of 3500 nm, and cruises overwater at Mach 1.8 with range of 3882 nm. Moreover, the refined MDO method eliminates the difference between the assumed cruise weight for CFD-based low-boom inverse design optimization and the estimated cruise weight of the optimal inverse design solution with respect to the mission requirements.


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    Titel :

    Multiobjective Multidisciplinary Optimization of Low-Boom Supersonic Transports Using Multifidelity Models


    Beteiligte:
    Wu Li (Autor:in) / Karl Geiselhart (Autor:in)

    Kongress:

    AIAA SciTech Forum 2022 ; 2022 ; San Diego, CA, US


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch