Non-linear modelling for Multi-Disciplinary and Multi-Objective Optimization of a complete aircraft

The aerospace engineering typically deals with multidisciplinary complex systems, and narrow margins of the design parameters make necessary the introduction of multi-objective approaches in order to pick the best design. Genetic algorithms, in addition to gradient-based ones, allow to evaluate Pareto frontiers, i.e. the set of best trade-offs, thanks to the current satisfactory level of computer performance. In the present paper, an integrated Multidisciplinary Design Optimization (MDO) has been used to solve a Multi-Objective Optimization (MOO) problem for a notional regional aircraft comprised of fuselage, tail and wing, where the optimization criteria are minimal structural weight, maximum aerodynamic efficiency and maximum mission range, taking into account also of aeroelastic constraints. Non-linear analyses have been further applied to evaluate the aerodynamic performance (i.e. the aerodynamic efficiency is computed as the ratio of lift and drag coefficients) for a more fidelity evaluation of the induced drag in the optimization process by using a free-wake approach.